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package com.ponkotuy.intercept import com.netaporter.uri.Uri import org.jboss.netty.handler.codec.http.{HttpResponse, HttpRequest} /** * * @author ponkotuy * Date: 14/02/18. */ trait Intercepter { def input(req: HttpRequest, res: HttpResponse, uri: Uri): Unit }
nekoworkshop/MyFleetGirls
client/src/main/scala/com/ponkotuy/intercept/Intercepter.scala
Scala
mit
270
package io.buoyant.namerd.storage.etcd import com.twitter.finagle.Path import io.buoyant.config.Parser import io.buoyant.config.types.Port import io.buoyant.namerd.DtabStoreConfig import org.scalatest.{FunSuite, OptionValues} class EtcdConfigTest extends FunSuite with OptionValues { test("sanity") { val store = EtcdConfig(None, None, Some(Path.read("/foo/bar"))).mkDtabStore } test("parse config") { val yaml = """|kind: io.l5d.etcd |experimental: true |pathPrefix: /foo/bar |host: etcd.dentist |port: 80 """.stripMargin val mapper = Parser.objectMapper(yaml, Iterable(Seq(EtcdDtabStoreInitializer))) val etcd = mapper.readValue[DtabStoreConfig](yaml).asInstanceOf[EtcdConfig] assert(etcd.host.value == "etcd.dentist") assert(etcd.port.value == Port(80)) assert(etcd.pathPrefix == Some(Path.read("/foo/bar"))) } }
hhtpcd/linkerd
namerd/storage/etcd/src/test/scala/io/buoyant/namerd/storage/etcd/EtcdConfigTest.scala
Scala
apache-2.0
904
package io.fintrospect.formats import org.scalatest.{FunSpec, Matchers} class MsgPackMsgTest extends FunSpec with Matchers { describe("MsgPackMsg") { it("can round trip to bytes and back again") { val letter = Letter(StreetAddress("bob"), StreetAddress("jim"), "rita") MsgPackMsg(letter).as[Letter] shouldBe letter } } }
daviddenton/fintrospect
msgpack/src/test/scala/io/fintrospect/formats/MsgPackMsgTest.scala
Scala
apache-2.0
349
package com.geishatokyo.diffsql.ast import com.geishatokyo.diffsql.Name import scala.language.implicitConversions /** * Created by takeshita on 14/02/14. */ case class DataType(name : Name, args : List[Int] = Nil){ def length : Int = args.head def precision : Tuple2[Int,Int] = args(0) -> args(1) def ===(dataType : DataType)(implicit eq : DataTypeEquality) = { if(dataType == null) false else eq.equal(this,dataType) } def !==(dataType : DataType)(implicit eq : DataTypeEquality) = { !(this === dataType) } override def toString: String = { if(args.isEmpty){ name.name }else{ s"${name.name}(${args.mkString(",")})" } } } object DataType{ implicit def fromString( simpleType : String) = DataType(simpleType) } trait DataTypeEquality{ def normalize(d: DataType): DataType = d def equal(d1 : DataType , d2 : DataType) : Boolean = { managedEqual( normalize(d1),normalize(d2)) } /** * Normalized data types are passed. * @param d1 * @param d2 * @return */ def managedEqual(d1 : DataType,d2 : DataType) : Boolean } object DataTypeEquality{ trait OnlyName extends DataTypeEquality{ def managedEqual(d1: DataType, d2: DataType) = { d1.name.toLowerCase() == d2.name.toLowerCase } } object OnlyName extends OnlyName trait NameAndLength extends DataTypeEquality{ def managedEqual(d1: DataType, d2: DataType): Boolean = { d1.name.toLowerCase == d2.name.toLowerCase && { d1.args == d2.args || d1.args.isEmpty || d2.args.isEmpty } } } object NameAndLength extends NameAndLength }
geishatokyo/diff-sql-table
parser/src/main/scala/com/geishatokyo/diffsql/ast/DataTypes.scala
Scala
mit
1,629
/* * Copyright (C) 2009-2017 Lightbend Inc. <https://www.lightbend.com> */ package scalaguide.http.scalabodyparsers { import akka.stream.ActorMaterializer import play.api.http.Writeable import play.api.libs.json.{Json, JsValue} import play.api.mvc._ import play.api.test._ import play.api.test.Helpers._ import org.specs2.mutable.Specification import org.junit.runner.RunWith import org.specs2.runner.JUnitRunner import scala.concurrent.Future import java.io.File import org.specs2.execute.AsResult @RunWith(classOf[JUnitRunner]) class ScalaBodyParsersSpec extends Specification with Controller { def helloRequest = FakeRequest("POST", "/").withJsonBody(Json.obj("name" -> "foo")) "A scala body parser" should { "parse request as json" in { import scala.concurrent.ExecutionContext.Implicits.global //#access-json-body def save = Action { request => val body: AnyContent = request.body val jsonBody: Option[JsValue] = body.asJson // Expecting json body jsonBody.map { json => Ok("Got: " + (json \\ "name").as[String]) }.getOrElse { BadRequest("Expecting application/json request body") } } //#access-json-body testAction(save, helloRequest) } "body parser json" in { //#body-parser-json def save = Action(parse.json) { request => Ok("Got: " + (request.body \\ "name").as[String]) } //#body-parser-json testAction(save, helloRequest) } "body parser tolerantJson" in { //#body-parser-tolerantJson def save = Action(parse.tolerantJson) { request => Ok("Got: " + (request.body \\ "name").as[String]) } //#body-parser-tolerantJson testAction(save, helloRequest) } "body parser file" in { //#body-parser-file def save = Action(parse.file(to = new File("/tmp/upload"))) { request => Ok("Saved the request content to " + request.body) } //#body-parser-file testAction(save, helloRequest.withSession("username" -> "player")) } "body parser combining" in { val save = scalaguide.http.scalabodyparsers.full.Application.save testAction(save, helloRequest.withSession("username" -> "player")) } "body parser limit text" in { val text = "hello" //#body-parser-limit-text // Accept only 10KB of data. def save = Action(parse.text(maxLength = 1024 * 10)) { request => Ok("Got: " + text) } //#body-parser-limit-text testAction(save, FakeRequest("POST", "/").withTextBody("foo")) } "body parser limit file" in { running() { app => implicit val mat = ActorMaterializer()(app.actorSystem) val storeInUserFile = scalaguide.http.scalabodyparsers.full.Application.storeInUserFile //#body-parser-limit-file // Accept only 10KB of data. def save = Action(parse.maxLength(1024 * 10, storeInUserFile)) { request => Ok("Saved the request content to " + request.body) } //#body-parser-limit-file val result = call(save, helloRequest.withSession("username" -> "player")) status(result) must_== OK } } "forward the body" in new WithApplication() { //#forward-body import javax.inject._ import play.api.mvc._ import play.api.libs.streams._ import play.api.libs.ws._ import scala.concurrent.ExecutionContext import akka.util.ByteString class MyController @Inject() (ws: WSClient)(implicit ec: ExecutionContext) { def forward(request: WSRequest): BodyParser[WSResponse] = BodyParser { req => Accumulator.source[ByteString].mapFuture { source => request .withBody(StreamedBody(source)) .execute() .map(Right.apply) } } def myAction = Action(forward(ws.url("https://example.com"))) { req => Ok("Uploaded") } } //#forward-body ok } "parse the body as csv" in new WithApplication() { import scala.concurrent.ExecutionContext.Implicits.global //#csv import play.api.mvc._ import play.api.libs.streams._ import akka.util.ByteString import akka.stream.scaladsl._ val csv: BodyParser[Seq[Seq[String]]] = BodyParser { req => // A flow that splits the stream into CSV lines val sink: Sink[ByteString, Future[Seq[Seq[String]]]] = Flow[ByteString] // We split by the new line character, allowing a maximum of 1000 characters per line .via(Framing.delimiter(ByteString("\\n"), 1000, allowTruncation = true)) // Turn each line to a String and split it by commas .map(_.utf8String.trim.split(",").toSeq) // Now we fold it into a list .toMat(Sink.fold(Seq.empty[Seq[String]])(_ :+ _))(Keep.right) // Convert the body to a Right either Accumulator(sink).map(Right.apply) } //#csv testAction(Action(csv)(req => Ok(req.body(1)(2))), FakeRequest("POST", "/").withTextBody("1,2\\n3,4,foo\\n5,6")) } } def testAction[A: Writeable](action: EssentialAction, request: => FakeRequest[A], expectedResponse: Int = OK) = { assertAction(action, request, expectedResponse) { result => success } } def assertAction[A: Writeable, T: AsResult](action: EssentialAction, request: => FakeRequest[A], expectedResponse: Int = OK)(assertions: Future[Result] => T) = { running() { app => implicit val mat = ActorMaterializer()(app.actorSystem) val result = call(action, request) status(result) must_== expectedResponse assertions(result) } } } package scalaguide.http.scalabodyparsers.full { import akka.util.ByteString import play.api.libs.streams.Accumulator import play.api.mvc._ object Application extends Controller { def file(to: File) = parse.file(to) //#body-parser-combining val storeInUserFile = parse.using { request => request.session.get("username").map { user => file(to = new File("/tmp/" + user + ".upload")) }.getOrElse { sys.error("You don't have the right to upload here") } } def save = Action(storeInUserFile) { request => Ok("Saved the request content to " + request.body) } //#body-parser-combining } object CodeShow { //#action trait Action[A] extends (Request[A] => Result) { def parser: BodyParser[A] } //#action //#request trait Request[+A] extends RequestHeader { def body: A } //#request //#body-parser trait BodyParser[+A] extends (RequestHeader => Accumulator[ByteString, Either[Result, A]]) //#body-parser } } }
aradchykov/playframework
documentation/manual/working/scalaGuide/main/http/code/ScalaBodyParsers.scala
Scala
apache-2.0
7,096
package org.veripacks.reader.dependencies import org.objectweb.asm.{Opcodes, ClassVisitor} class SourceFileNameVisitor extends ClassVisitor(Opcodes.ASM5) { var sourceFileName: String = _ override def visitSource(source: String, debug: String) { sourceFileName = source } }
adamw/veripacks
verifier/src/main/scala/org/veripacks/reader/dependencies/SourceFileNameVisitor.scala
Scala
apache-2.0
286
/* * Copyright (C) 2007-2008 Artima, Inc. All rights reserved. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * Example code from: * * Programming in Scala (First Edition, Version 6) * by Martin Odersky, Lex Spoon, Bill Venners * * http://booksites.artima.com/programming_in_scala */ package org.stairwaybook.simulation // // Same code as Simulator1, but built from code extracted from small // snippets within chapter instead of from long listings. // object Simulator2 { abstract class BasicCircuitSimulation extends Simulation { def InverterDelay: Int def AndGateDelay: Int def OrGateDelay: Int class Wire { private var sigVal = false private var actions: List[Action] = List() def getSignal = sigVal def setSignal(s: Boolean) = if (s != sigVal) { sigVal = s actions foreach (_ ()) } def addAction(a: Action) = { actions = a :: actions a() } } def inverter(input: Wire, output: Wire) = { def invertAction() { val inputSig = input.getSignal afterDelay(InverterDelay) { output setSignal !inputSig } } input addAction invertAction } def andGate(a1: Wire, a2: Wire, output: Wire) = { def andAction() = { val a1Sig = a1.getSignal val a2Sig = a2.getSignal afterDelay(AndGateDelay) { output setSignal (a1Sig & a2Sig) } } a1 addAction andAction a2 addAction andAction } def orGate(o1: Wire, o2: Wire, output: Wire) { def orAction() { val o1Sig = o1.getSignal val o2Sig = o2.getSignal afterDelay(OrGateDelay) { output setSignal (o1Sig | o2Sig) } } o1 addAction orAction o2 addAction orAction } def probe(name: String, wire: Wire) { def probeAction() { println(name +" "+ currentTime + " new-value = "+ wire.getSignal) } wire addAction probeAction } } abstract class Simulation { type Action = () => Unit case class WorkItem(time: Int, action: Action) private var curtime: Int = 0 def currentTime: Int = curtime private var agenda: List[WorkItem] = List() private def insert(ag: List[WorkItem], item: WorkItem): List[WorkItem] = { if (ag.isEmpty || item.time < ag.head.time) item :: ag else ag.head :: insert(ag.tail, item) } def afterDelay(delay: Int)(block: => Unit) { val item = WorkItem(currentTime + delay, () => block) agenda = insert(agenda, item) } private def next() { (agenda: @unchecked) match { case item :: rest => agenda = rest curtime = item.time item.action() } } def run() { afterDelay(0) { println("*** simulation started, time = "+ currentTime +" ***") } while (!agenda.isEmpty) next() } } abstract class CircuitSimulation extends BasicCircuitSimulation { def halfAdder(a: Wire, b: Wire, s: Wire, c: Wire) { val d, e = new Wire orGate(a, b, d) andGate(a, b, c) inverter(c, e) andGate(d, e, s) } def fullAdder(a: Wire, b: Wire, cin: Wire, sum: Wire, cout: Wire) { val s, c1, c2 = new Wire halfAdder(a, cin, s, c1) halfAdder(b, s, sum, c2) orGate(c1, c2, cout) } } } object MySimulation2 extends Simulator2.CircuitSimulation { def InverterDelay = 1 def AndGateDelay = 3 def OrGateDelay = 5 def main(args: Array[String]) { val input1, input2, sum, carry = new Wire probe("sum", sum) probe("carry", carry) halfAdder(input1, input2, sum, carry) input1 setSignal true run() input2 setSignal true run() } }
peachyy/scalastu
stateful-objects/Simulator2.scala
Scala
apache-2.0
4,394
package fr.univ_lille.cristal.emeraude.chasqui.core.synchronization import akka.actor.{Actor, ActorRef, ActorSystem, ExtendedActorSystem, Extension, ExtensionId, ExtensionIdProvider, Props} import akka.pattern.ask import akka.util.Timeout import fr.univ_lille.cristal.emeraude.chasqui.core.Node._ import fr.univ_lille.cristal.emeraude.chasqui.core._ import fr.univ_lille.cristal.emeraude.chasqui.core.synchronization.GlobalSynchronizerWithLocalQueueStrategy.{NotifyFinishedTime, RegisterNode} import scala.collection.mutable import scala.concurrent.{ExecutionContext, Future} import scala.util._ abstract class SynchronizerStrategyCompanion { def buildFor(system: ActorSystem): SynchronizerStrategy } object GlobalSynchronizerWithLocalQueueStrategy extends SynchronizerStrategyCompanion { override def buildFor(system: ActorSystem): SynchronizerStrategy = new GlobalSynchronizerWithLocalQueueStrategy(system) case class RegisterNode(node: ActorRef) case class NotifyFinishedTime(node: ActorRef, finishedQuantum: Long, messageQueueSize: Int, messageDelta: Int, incomingQuantum: Option[Long]) } class GlobalSynchronizerWithLocalQueueStrategy(system: ActorSystem) extends SynchronizerStrategy { private var sentMessagesInQuantum = 0 private var receivedMessagesInQuantum = 0 private val messageQueue = scala.collection.mutable.PriorityQueue[Message]()(Ordering.fromLessThan((s1, s2) => s1.getTimestamp > s2.getTimestamp)) def registerNode(node: Node): Unit = { this.getSynchronizerActor() ! RegisterNode(node.getActorRef) } def notifyFinishedTime(nodeActorRef: ActorRef, node: Node, t: Long, messageDelta: Int): Unit = { this.getSynchronizerActor() ! NotifyFinishedTime(nodeActorRef, t, this.messageQueue.size, messageDelta, node.getRealIncomingQuantum) } def getSynchronizerActor(): ActorRef = { GlobalSynchronizerWithLocalQueueStrategyAccessor(system).instance } override def handleSynchronizationMessage(message: SynchronizationMessage, sender: ActorRef, receiver: Node, t: Long): Unit = { //Nothing } override def sendMessage(senderNode: Node, receiverActor: ActorRef, messageTimestamp: Long, message: Any): Unit = { this.sentMessagesInQuantum += 1 receiverActor ! ScheduleMessage(message, messageTimestamp, senderNode.getActorRef) } override def scheduleMessage(receiverNode: Node, senderActor: ActorRef, messageTimestamp: Long, message: Any): Unit = { this.receivedMessagesInQuantum += 1 if (messageTimestamp < receiverNode.getCurrentSimulationTime) { //The message is in the past. //This is a Causality error unless it is a SynchronizationMessages if (!message.isInstanceOf[SynchronizationMessage]){ receiverNode.getCausalityErrorStrategy.handleCausalityError(messageTimestamp, receiverNode.getCurrentSimulationTime, receiverNode, senderActor, message) } return } if (receiverNode.getCurrentSimulationTime == messageTimestamp){ receiverNode.handleIncomingMessage(message, senderActor) } else { this.queueMessage(senderActor, messageTimestamp, message) } receiverNode.notifyFinishedQuantum() } private def queueMessage(senderActor: ActorRef, messageTimestamp: Long, message: Any) = { messageQueue += new Message(message, messageTimestamp, senderActor) } override def getMessageQueue: scala.collection.mutable.PriorityQueue[Message] = this.messageQueue } abstract class AbstractGlobalSynchronizerWithLocalQueueSingletonActor extends Actor { val nodes = new collection.mutable.HashSet[ActorRef]() def registerNode(node: ActorRef): Unit = { nodes += node } def notifyFinishedTime(nodeActorRef: ActorRef, t: Long, queueSize: Int, messageDelta: Int, incomingQuantum: Option[Long]): Unit override def receive: Receive = { case RegisterNode(node) => this.registerNode(node) case NotifyFinishedTime(node: ActorRef, finishedQuantum: Long, messageQueueSize: Int, messageDelta: Int, incomingQuantum: Option[Long]) => this.notifyFinishedTime(node, finishedQuantum, messageQueueSize, messageDelta, incomingQuantum) } } class GlobalSynchronizerWithLocalQueueSingletonActor extends AbstractGlobalSynchronizerWithLocalQueueSingletonActor { import scala.concurrent.duration._ implicit val ec = ExecutionContext.Implicits.global implicit lazy val timeout = Timeout(5 seconds) val nodeMessageDeltas = new mutable.HashMap[ActorRef, Int]() val nodeIncomingQuantums = new mutable.HashMap[ActorRef, Option[Long]]() val nodesFinishedThisQuantum = new collection.mutable.HashSet[ActorRef]() var messagesToBeProcessedFollowingQuantums: Int = 0 protected def allNodesAreReady(): Boolean = { nodes.forall(this.nodesFinishedThisQuantum.contains) } def getNextQuantum(): Option[Long] = { nodeIncomingQuantums.values.foldLeft[Option[Long]](None)( (accum, each) => if (accum.isEmpty) { each } else if (each.isEmpty) { accum } else { Some(accum.get.min(each.get)) } ) } def numberOfPendingMessagesInQuantum(): Int = nodeMessageDeltas.values.sum def setMessageDelta(nodeActorRef: ActorRef, messageDelta: Int) = { nodeMessageDeltas(nodeActorRef) = messageDelta } def setIncomingQuantum(nodeActorRef: ActorRef, incomingQuantum: Option[Long]) = { nodeIncomingQuantums(nodeActorRef) = incomingQuantum } def notifyFinishedTime(nodeActorRef: ActorRef, t: Long, queueSize: Int, messageDelta: Int, incomingQuantum: Option[Long]): Unit = { this.nodesFinishedThisQuantum += nodeActorRef this.setMessageDelta(nodeActorRef, messageDelta) this.setIncomingQuantum(nodeActorRef, incomingQuantum) this.messagesToBeProcessedFollowingQuantums += queueSize val allNodesReady = this.allNodesAreReady() val numberOfPendingMessagesInQuantum = this.numberOfPendingMessagesInQuantum() val existPendingMessages = this.messagesToBeProcessedFollowingQuantums != 0 if (allNodesReady && numberOfPendingMessagesInQuantum == 0 && existPendingMessages) { val maybeNextQuantum = this.getNextQuantum() if (maybeNextQuantum.isDefined) { val sequence = this.nodes.map(node => (node ? AdvanceSimulationTime(maybeNextQuantum.get)).asInstanceOf[Future[Int]]) Future.sequence(sequence) .onComplete { case Success(result) => { //TODO: println(s"Quantum achieved: ${maybeNextQuantum.get} with: $result") this.nodes.foreach(n => n ! ProcessNextQuantum) } case Failure(_) => { println("Error while resuming next quantum!") } } //Cleanup local state this.nodesFinishedThisQuantum.clear() this.nodeIncomingQuantums.clear() this.nodeMessageDeltas.clear() this.messagesToBeProcessedFollowingQuantums = 0 } else { //Finished? } } else { //println(s"Not ready to advance yet at t=$t. Nodes ready: $allNodesReady, all messages in quantum processed: $numberOfPendingMessagesInQuantum, existing pending messages: $existPendingMessages") } } } class GlobalSynchronizerWithLocalQueueSingleton(system: ActorSystem, props: Props, name: String) extends Extension { val instance: ActorRef = system.actorOf(props, name) } object GlobalSynchronizerWithLocalQueueStrategyAccessor extends ExtensionId[GlobalSynchronizerWithLocalQueueSingleton] with ExtensionIdProvider { final override def lookup = this final override def createExtension(system: ExtendedActorSystem) = new GlobalSynchronizerWithLocalQueueSingleton(system, instanceProps, instanceName) lazy val instanceProps = Props[GlobalSynchronizerWithLocalQueueSingletonActor] lazy val instanceName = "global-synchronizer-actor" }
guillep/chasqui
src/main/scala/fr/univ_lille/cristal/emeraude/chasqui/core/synchronization/GlobalSynchronizerWithLocalQueueStrategy.scala
Scala
mit
7,769
package pl.touk.nussknacker.ui.security.oauth2 import cats.data.NonEmptyList.one import com.typesafe.scalalogging.LazyLogging import io.circe.Decoder import io.circe.generic.extras.{Configuration, ConfiguredJsonCodec, JsonKey} import pl.touk.nussknacker.ui.security.oauth2.OAuth2ErrorHandler.{OAuth2AccessTokenRejection, OAuth2CompoundException} import sttp.client.{NothingT, SttpBackend} import scala.concurrent.duration.{Deadline, FiniteDuration} import scala.concurrent.{ExecutionContext, Future} class BaseOAuth2Service[ UserInfoData, AuthorizationData <: OAuth2AuthorizationData ](protected val clientApi: OAuth2ClientApi[UserInfoData, AuthorizationData]) (implicit ec: ExecutionContext) extends OAuth2Service[UserInfoData, AuthorizationData] with LazyLogging { final def obtainAuthorizationAndUserInfo(authorizationCode: String, redirectUri: String): Future[(AuthorizationData, UserInfoData)] = { for { authorizationData <- obtainAuthorization(authorizationCode, redirectUri) userInfo <- obtainUserInfo(authorizationData) } yield (authorizationData, userInfo) } final def checkAuthorizationAndObtainUserinfo(accessToken: String): Future[(UserInfoData, Option[Deadline])] = for { deadline <- introspectAccessToken(accessToken) userInfo <- obtainUserInfo(accessToken) } yield (userInfo, deadline) protected def obtainAuthorization(authorizationCode: String, redirectUri: String): Future[AuthorizationData] = clientApi.accessTokenRequest(authorizationCode, redirectUri) /* Override this method in a subclass making use of signed tokens or an introspection endpoint or use a CachingOAuthService wrapper so that only previously-stored (immediately after retrieval) tokens are accepted or do both. */ protected def introspectAccessToken(accessToken: String): Future[Option[Deadline]] = { Future.failed(OAuth2CompoundException(one(OAuth2AccessTokenRejection("The access token cannot be validated")))) } /* OAuth2 itself is not an authentication framework. However, we can treat it so. All we need is a restricted resource that provides information about a user only with his valid access token. The following two methods shall call such a resource. */ protected def obtainUserInfo(authorizationData: AuthorizationData): Future[UserInfoData] = obtainUserInfo(authorizationData.accessToken) protected def obtainUserInfo(accessToken: String): Future[UserInfoData] = clientApi.profileRequest(accessToken) } @ConfiguredJsonCodec case class DefaultOAuth2AuthorizationData ( @JsonKey("access_token") accessToken: String, @JsonKey("token_type") tokenType: String, @JsonKey("refresh_token") refreshToken: Option[String] = None, @JsonKey("expires_in") expirationPeriod: Option[FiniteDuration] = None ) extends OAuth2AuthorizationData object DefaultOAuth2AuthorizationData extends EpochSecondsCodecs { implicit val config: Configuration = Configuration.default } object BaseOAuth2Service { def apply[ UserInfoData: Decoder ](configuration: OAuth2Configuration)(implicit ec: ExecutionContext, backend: SttpBackend[Future, Nothing, NothingT]): BaseOAuth2Service[UserInfoData, DefaultOAuth2AuthorizationData] = new BaseOAuth2Service(OAuth2ClientApi[UserInfoData, DefaultOAuth2AuthorizationData](configuration)) }
TouK/nussknacker
security/src/main/scala/pl/touk/nussknacker/ui/security/oauth2/BaseOAuth2Service.scala
Scala
apache-2.0
3,329
/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.spark.ml.util import org.apache.spark.SparkFunSuite import org.apache.spark.ml._ import org.apache.spark.ml.evaluation.Evaluator import org.apache.spark.ml.feature.{Instance, LabeledPoint} import org.apache.spark.ml.linalg.{Vector, Vectors, VectorUDT} import org.apache.spark.ml.param.ParamMap import org.apache.spark.ml.param.shared.{HasFeaturesCol, HasLabelCol, HasWeightCol} import org.apache.spark.ml.recommendation.{ALS, ALSModel} import org.apache.spark.ml.tree.impl.TreeTests import org.apache.spark.sql.{DataFrame, Dataset, Row, SparkSession} import org.apache.spark.sql.functions._ import org.apache.spark.sql.types._ object MLTestingUtils extends SparkFunSuite { def checkCopyAndUids[T <: Estimator[_]](estimator: T, model: Model[_]): Unit = { assert(estimator.uid === model.uid, "Model uid does not match parent estimator") // copied model must have the same parent val copied = model.copy(ParamMap.empty) .asInstanceOf[Model[_]] assert(copied.parent == model.parent) assert(copied.parent.uid == model.parent.uid) } def checkNumericTypes[M <: Model[M], T <: Estimator[M]]( estimator: T, spark: SparkSession, isClassification: Boolean = true)(check: (M, M) => Unit): Unit = { val dfs = if (isClassification) { genClassifDFWithNumericLabelCol(spark) } else { genRegressionDFWithNumericLabelCol(spark) } val finalEstimator = estimator match { case weighted: Estimator[M] with HasWeightCol => weighted.set(weighted.weightCol, "weight") weighted case _ => estimator } val expected = finalEstimator.fit(dfs(DoubleType)) val actuals = dfs.keys.filter(_ != DoubleType).map { t => finalEstimator.fit(dfs(t)) } actuals.foreach(actual => check(expected, actual)) val dfWithStringLabels = spark.createDataFrame(Seq( ("0", 1, Vectors.dense(0, 2, 3), 0.0) )).toDF("label", "weight", "features", "censor") val thrown = intercept[IllegalArgumentException] { estimator.fit(dfWithStringLabels) } assert(thrown.getMessage.contains( "Column label must be of type NumericType but was actually of type StringType")) estimator match { case weighted: Estimator[M] with HasWeightCol => val dfWithStringWeights = spark.createDataFrame(Seq( (0, "1", Vectors.dense(0, 2, 3), 0.0) )).toDF("label", "weight", "features", "censor") weighted.set(weighted.weightCol, "weight") val thrown = intercept[IllegalArgumentException] { weighted.fit(dfWithStringWeights) } assert(thrown.getMessage.contains( "Column weight must be of type NumericType but was actually of type StringType")) case _ => } } def checkNumericTypes[T <: Evaluator](evaluator: T, spark: SparkSession): Unit = { val dfs = genEvaluatorDFWithNumericLabelCol(spark, "label", "prediction") val expected = evaluator.evaluate(dfs(DoubleType)) val actuals = dfs.keys.filter(_ != DoubleType).map(t => evaluator.evaluate(dfs(t))) actuals.foreach(actual => assert(expected === actual)) val dfWithStringLabels = spark.createDataFrame(Seq( ("0", 0d) )).toDF("label", "prediction") val thrown = intercept[IllegalArgumentException] { evaluator.evaluate(dfWithStringLabels) } assert(thrown.getMessage.contains( "Column label must be of type NumericType but was actually of type StringType")) } def genClassifDFWithNumericLabelCol( spark: SparkSession, labelColName: String = "label", featuresColName: String = "features", weightColName: String = "weight"): Map[NumericType, DataFrame] = { val df = spark.createDataFrame(Seq( (0, Vectors.dense(0, 2, 3)), (1, Vectors.dense(0, 3, 1)), (0, Vectors.dense(0, 2, 2)), (1, Vectors.dense(0, 3, 9)), (0, Vectors.dense(0, 2, 6)) )).toDF(labelColName, featuresColName) val types = Seq(ShortType, LongType, IntegerType, FloatType, ByteType, DoubleType, DecimalType(10, 0)) types.map { t => val castDF = df.select(col(labelColName).cast(t), col(featuresColName)) t -> TreeTests.setMetadata(castDF, 2, labelColName, featuresColName) .withColumn(weightColName, round(rand(seed = 42)).cast(t)) }.toMap } def genRegressionDFWithNumericLabelCol( spark: SparkSession, labelColName: String = "label", weightColName: String = "weight", featuresColName: String = "features", censorColName: String = "censor"): Map[NumericType, DataFrame] = { val df = spark.createDataFrame(Seq( (1, Vectors.dense(1)), (2, Vectors.dense(2)), (3, Vectors.dense(3)), (4, Vectors.dense(4)) )).toDF(labelColName, featuresColName) val types = Seq(ShortType, LongType, IntegerType, FloatType, ByteType, DoubleType, DecimalType(10, 0)) types.map { t => val castDF = df.select(col(labelColName).cast(t), col(featuresColName)) t -> TreeTests.setMetadata(castDF, 0, labelColName, featuresColName) .withColumn(censorColName, lit(0.0)) .withColumn(weightColName, round(rand(seed = 42)).cast(t)) }.toMap } def genEvaluatorDFWithNumericLabelCol( spark: SparkSession, labelColName: String = "label", predictionColName: String = "prediction"): Map[NumericType, DataFrame] = { val df = spark.createDataFrame(Seq( (0, 0d), (1, 1d), (2, 2d), (3, 3d), (4, 4d) )).toDF(labelColName, predictionColName) val types = Seq(ShortType, LongType, IntegerType, FloatType, ByteType, DoubleType, DecimalType(10, 0)) types .map(t => t -> df.select(col(labelColName).cast(t), col(predictionColName))) .toMap } /** * Given a DataFrame, generate two output DataFrames: one having the original rows oversampled * an integer number of times, and one having the original rows but with a column of weights * proportional to the number of oversampled instances in the oversampled DataFrames. */ def genEquivalentOversampledAndWeightedInstances( data: Dataset[LabeledPoint], seed: Long): (Dataset[Instance], Dataset[Instance]) = { import data.sparkSession.implicits._ val rng = new scala.util.Random(seed) val sample: () => Int = () => rng.nextInt(10) + 1 val sampleUDF = udf(sample) val rawData = data.select("label", "features").withColumn("samples", sampleUDF()) val overSampledData = rawData.rdd.flatMap { case Row(label: Double, features: Vector, n: Int) => Iterator.fill(n)(Instance(label, 1.0, features)) }.toDS() rng.setSeed(seed) val weightedData = rawData.rdd.map { case Row(label: Double, features: Vector, n: Int) => Instance(label, n.toDouble, features) }.toDS() (overSampledData, weightedData) } /** * Helper function for testing sample weights. Tests that oversampling each point is equivalent * to assigning a sample weight proportional to the number of samples for each point. */ def testOversamplingVsWeighting[M <: Model[M], E <: Estimator[M]]( data: Dataset[LabeledPoint], estimator: E with HasWeightCol, modelEquals: (M, M) => Unit, seed: Long): Unit = { val (overSampledData, weightedData) = genEquivalentOversampledAndWeightedInstances( data, seed) val weightedModel = estimator.set(estimator.weightCol, "weight").fit(weightedData) val overSampledModel = estimator.set(estimator.weightCol, "").fit(overSampledData) modelEquals(weightedModel, overSampledModel) } /** * Helper function for testing sample weights. Tests that injecting a large number of outliers * with very small sample weights does not affect fitting. The predictor should learn the true * model despite the outliers. */ def testOutliersWithSmallWeights[M <: Model[M], E <: Estimator[M]]( data: Dataset[LabeledPoint], estimator: E with HasWeightCol, numClasses: Int, modelEquals: (M, M) => Unit, outlierRatio: Int): Unit = { import data.sqlContext.implicits._ val outlierDS = data.withColumn("weight", lit(1.0)).as[Instance].flatMap { case Instance(l, w, f) => val outlierLabel = if (numClasses == 0) -l else numClasses - l - 1 List.fill(outlierRatio)(Instance(outlierLabel, 0.0001, f)) ++ List(Instance(l, w, f)) } val trueModel = estimator.set(estimator.weightCol, "").fit(data) val outlierModel = estimator.set(estimator.weightCol, "weight").fit(outlierDS) modelEquals(trueModel, outlierModel) } /** * Helper function for testing sample weights. Tests that giving constant weights to each data * point yields the same model, regardless of the magnitude of the weight. */ def testArbitrarilyScaledWeights[M <: Model[M], E <: Estimator[M]]( data: Dataset[LabeledPoint], estimator: E with HasWeightCol, modelEquals: (M, M) => Unit): Unit = { estimator.set(estimator.weightCol, "weight") val models = Seq(0.001, 1.0, 1000.0).map { w => val df = data.withColumn("weight", lit(w)) estimator.fit(df) } models.sliding(2).foreach { case Seq(m1, m2) => modelEquals(m1, m2)} } /** * Helper function for testing different input types for "features" column. Given a DataFrame, * generate three output DataFrames: one having vector "features" column with float precision, * one having double array "features" column with float precision, and one having float array * "features" column. */ def generateArrayFeatureDataset(dataset: Dataset[_], featuresColName: String = "features"): (Dataset[_], Dataset[_], Dataset[_]) = { val toFloatVectorUDF = udf { (features: Vector) => Vectors.dense(features.toArray.map(_.toFloat.toDouble))} val toDoubleArrayUDF = udf { (features: Vector) => features.toArray} val toFloatArrayUDF = udf { (features: Vector) => features.toArray.map(_.toFloat)} val newDataset = dataset.withColumn(featuresColName, toFloatVectorUDF(col(featuresColName))) val newDatasetD = newDataset.withColumn(featuresColName, toDoubleArrayUDF(col(featuresColName))) val newDatasetF = newDataset.withColumn(featuresColName, toFloatArrayUDF(col(featuresColName))) assert(newDataset.schema(featuresColName).dataType.equals(new VectorUDT)) assert(newDatasetD.schema(featuresColName).dataType.equals(new ArrayType(DoubleType, false))) assert(newDatasetF.schema(featuresColName).dataType.equals(new ArrayType(FloatType, false))) (newDataset, newDatasetD, newDatasetF) } }
bravo-zhang/spark
mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala
Scala
apache-2.0
11,403
/* * Shadowsocks - A shadowsocks client for Android * Copyright (C) 2014 <max.c.lv@gmail.com> * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. * * * ___====-_ _-====___ * _--^^^#####// \\\\#####^^^--_ * _-^##########// ( ) \\\\##########^-_ * -############// |\\^^/| \\\\############- * _/############// (@::@) \\\\############\\_ * /#############(( \\\\// ))#############\\ * -###############\\\\ (oo) //###############- * -#################\\\\ / VV \\ //#################- * -###################\\\\/ \\//###################- * _#/|##########/\\######( /\\ )######/\\##########|\\#_ * |/ |#/\\#/\\#/\\/ \\#/\\##\\ | | /##/\\#/ \\/\\#/\\#/\\#| \\| * ` |/ V V ` V \\#\\| | | |/#/ V ' V V \\| ' * ` ` ` ` / | | | | \\ ' ' ' ' * ( | | | | ) * __\\ | | | | /__ * (vvv(VVV)(VVV)vvv) * * HERE BE DRAGONS * */ package com.github.shadowsocks import com.biganiseed.reindeer.R import java.util import java.util.concurrent.TimeUnit import android.app.Application import com.github.shadowsocks.database.DBHelper import com.github.shadowsocks.utils.Utils import com.google.android.gms.analytics.GoogleAnalytics import com.google.android.gms.common.api.ResultCallback import com.google.android.gms.tagmanager.Container.FunctionCallMacroCallback import com.google.android.gms.tagmanager.{ContainerHolder, TagManager} class ShadowsocksApplication extends Application { lazy val dbHelper = new DBHelper(this) lazy val SIG_FUNC = "getSignature" var containerHolder: ContainerHolder = null lazy val tracker = GoogleAnalytics.getInstance(this).newTracker(R.xml.tracker) override def onCreate() { val tm = TagManager.getInstance(this) val pending = tm.loadContainerPreferNonDefault("GTM-NT8WS8", R.raw.gtm_default_container) val callback = new ResultCallback[ContainerHolder] { override def onResult(holder: ContainerHolder): Unit = { if (!holder.getStatus.isSuccess) { return } containerHolder = holder val container = holder.getContainer container.registerFunctionCallMacroCallback(SIG_FUNC, new FunctionCallMacroCallback { override def getValue(functionName: String, parameters: util.Map[String, AnyRef]): AnyRef = { if (functionName == SIG_FUNC) { Utils.getSignature(getApplicationContext) } null } }) } } pending.setResultCallback(callback, 2, TimeUnit.SECONDS) } }
alexliao/reshadow
src/main/scala/com/github/shadowsocks/ShadowsocksApplication.scala
Scala
gpl-3.0
3,403
/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.spark.sql.catalyst.expressions import java.sql.Timestamp import org.apache.spark.SparkFunSuite import org.apache.spark.sql.catalyst.analysis.SimpleAnalyzer import org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext import org.apache.spark.sql.catalyst.expressions.objects.AssertNotNull import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, Project} import org.apache.spark.sql.types._ class NullExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper { def testAllTypes(testFunc: (Any, DataType) => Unit): Unit = { testFunc(false, BooleanType) testFunc(1.toByte, ByteType) testFunc(1.toShort, ShortType) testFunc(1, IntegerType) testFunc(1L, LongType) testFunc(1.0F, FloatType) testFunc(1.0, DoubleType) testFunc(Decimal(1.5), DecimalType(2, 1)) testFunc(new java.sql.Date(10), DateType) testFunc(new java.sql.Timestamp(10), TimestampType) testFunc("abcd", StringType) } test("isnull and isnotnull") { testAllTypes { (value: Any, tpe: DataType) => checkEvaluation(IsNull(Literal.create(value, tpe)), false) checkEvaluation(IsNotNull(Literal.create(value, tpe)), true) checkEvaluation(IsNull(Literal.create(null, tpe)), true) checkEvaluation(IsNotNull(Literal.create(null, tpe)), false) } } test("AssertNotNUll") { val ex = intercept[RuntimeException] { evaluateWithoutCodegen(AssertNotNull(Literal(null))) }.getMessage assert(ex.contains("Null value appeared in non-nullable field")) } test("IsNaN") { checkEvaluation(IsNaN(Literal(Double.NaN)), true) checkEvaluation(IsNaN(Literal(Float.NaN)), true) checkEvaluation(IsNaN(Literal(math.log(-3))), true) checkEvaluation(IsNaN(Literal.create(null, DoubleType)), false) checkEvaluation(IsNaN(Literal(Double.PositiveInfinity)), false) checkEvaluation(IsNaN(Literal(Float.MaxValue)), false) checkEvaluation(IsNaN(Literal(5.5f)), false) } test("nanvl") { checkEvaluation(NaNvl(Literal(5.0), Literal.create(null, DoubleType)), 5.0) checkEvaluation(NaNvl(Literal.create(null, DoubleType), Literal(5.0)), null) checkEvaluation(NaNvl(Literal.create(null, DoubleType), Literal(Double.NaN)), null) checkEvaluation(NaNvl(Literal(Double.NaN), Literal(5.0)), 5.0) checkEvaluation(NaNvl(Literal(Double.NaN), Literal.create(null, DoubleType)), null) assert(NaNvl(Literal(Double.NaN), Literal(Double.NaN)). eval(EmptyRow).asInstanceOf[Double].isNaN) } test("coalesce") { testAllTypes { (value: Any, tpe: DataType) => val lit = Literal.create(value, tpe) val nullLit = Literal.create(null, tpe) checkEvaluation(Coalesce(Seq(nullLit)), null) checkEvaluation(Coalesce(Seq(lit)), value) checkEvaluation(Coalesce(Seq(nullLit, lit)), value) checkEvaluation(Coalesce(Seq(nullLit, lit, lit)), value) checkEvaluation(Coalesce(Seq(nullLit, nullLit, lit)), value) } val coalesce = Coalesce(Seq( Literal.create(null, ArrayType(IntegerType, containsNull = false)), Literal.create(Seq(1, 2, 3), ArrayType(IntegerType, containsNull = false)), Literal.create(Seq(1, 2, 3, null), ArrayType(IntegerType, containsNull = true)))) assert(coalesce.dataType === ArrayType(IntegerType, containsNull = true)) checkEvaluation(coalesce, Seq(1, 2, 3)) } test("SPARK-16602 Nvl should support numeric-string cases") { def analyze(expr: Expression): Expression = { val relation = LocalRelation() SimpleAnalyzer.execute(Project(Seq(Alias(expr, "c")()), relation)).expressions.head } val intLit = Literal.create(1, IntegerType) val doubleLit = Literal.create(2.2, DoubleType) val stringLit = Literal.create("c", StringType) val nullLit = Literal.create(null, NullType) val floatNullLit = Literal.create(null, FloatType) val floatLit = Literal.create(1.01f, FloatType) val timestampLit = Literal.create(Timestamp.valueOf("2017-04-12 00:00:00"), TimestampType) val decimalLit = Literal.create(BigDecimal.valueOf(10.2), DecimalType(20, 2)) assert(analyze(new Nvl(decimalLit, stringLit)).dataType == StringType) assert(analyze(new Nvl(doubleLit, decimalLit)).dataType == DoubleType) assert(analyze(new Nvl(decimalLit, doubleLit)).dataType == DoubleType) assert(analyze(new Nvl(decimalLit, floatLit)).dataType == DoubleType) assert(analyze(new Nvl(floatLit, decimalLit)).dataType == DoubleType) assert(analyze(new Nvl(timestampLit, stringLit)).dataType == StringType) assert(analyze(new Nvl(intLit, doubleLit)).dataType == DoubleType) assert(analyze(new Nvl(intLit, stringLit)).dataType == StringType) assert(analyze(new Nvl(stringLit, doubleLit)).dataType == StringType) assert(analyze(new Nvl(doubleLit, stringLit)).dataType == StringType) assert(analyze(new Nvl(nullLit, intLit)).dataType == IntegerType) assert(analyze(new Nvl(doubleLit, nullLit)).dataType == DoubleType) assert(analyze(new Nvl(nullLit, stringLit)).dataType == StringType) assert(analyze(new Nvl(floatLit, stringLit)).dataType == StringType) assert(analyze(new Nvl(floatLit, doubleLit)).dataType == DoubleType) assert(analyze(new Nvl(floatNullLit, intLit)).dataType == FloatType) } test("AtLeastNNonNulls") { val mix = Seq(Literal("x"), Literal.create(null, StringType), Literal.create(null, DoubleType), Literal(Double.NaN), Literal(5f)) val nanOnly = Seq(Literal("x"), Literal(10.0), Literal(Float.NaN), Literal(math.log(-2)), Literal(Double.MaxValue)) val nullOnly = Seq(Literal("x"), Literal.create(null, DoubleType), Literal.create(null, DecimalType.USER_DEFAULT), Literal(Float.MaxValue), Literal(false)) checkEvaluation(AtLeastNNonNulls(2, mix), true, EmptyRow) checkEvaluation(AtLeastNNonNulls(3, mix), false, EmptyRow) checkEvaluation(AtLeastNNonNulls(3, nanOnly), true, EmptyRow) checkEvaluation(AtLeastNNonNulls(4, nanOnly), false, EmptyRow) checkEvaluation(AtLeastNNonNulls(3, nullOnly), true, EmptyRow) checkEvaluation(AtLeastNNonNulls(4, nullOnly), false, EmptyRow) } test("Coalesce should not throw 64KiB exception") { val inputs = (1 to 2500).map(x => Literal(s"x_$x")) checkEvaluation(Coalesce(inputs), "x_1") } test("SPARK-22705: Coalesce should use less global variables") { val ctx = new CodegenContext() Coalesce(Seq(Literal("a"), Literal("b"))).genCode(ctx) assert(ctx.inlinedMutableStates.size == 1) } test("AtLeastNNonNulls should not throw 64KiB exception") { val inputs = (1 to 4000).map(x => Literal(s"x_$x")) checkEvaluation(AtLeastNNonNulls(1, inputs), true) } }
pgandhi999/spark
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/NullExpressionsSuite.scala
Scala
apache-2.0
7,564
/*********************************************************************** * Copyright (c) 2013-2022 Commonwealth Computer Research, Inc. * All rights reserved. This program and the accompanying materials * are made available under the terms of the Apache License, Version 2.0 * which accompanies this distribution and is available at * http://www.opensource.org/licenses/apache2.0.php. ***********************************************************************/ /* * Copyright (C) 2007 The Guava Authors * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.locationtech.geomesa.utils.stats import java.io.{InputStream, FilterInputStream, IOException} /** * Counting input stream from guava, extended to provide reset of count */ class CountingInputStream(in: InputStream) extends FilterInputStream(in) { private var count: Long = 0L private var mark: Long = -1 /** Returns the number of bytes read. */ def getCount: Long = count def resetCount(): Unit = count = 0L override def read: Int = { val result: Int = in.read if (result != -1) { count += 1 } result } override def read(b: Array[Byte], off: Int, len: Int): Int = { val result: Int = in.read(b, off, len) if (result != -1) { count += result } result } override def skip(n: Long): Long = { val result: Long = in.skip(n) count += result result } override def mark(readlimit: Int): Unit = { in.mark(readlimit) mark = count } override def reset(): Unit = { if (!in.markSupported) { throw new IOException("Mark not supported") } if (mark == -1) { throw new IOException("Mark not set") } in.reset() count = mark } }
locationtech/geomesa
geomesa-utils/src/main/scala/org/locationtech/geomesa/utils/stats/CountingInputStream.scala
Scala
apache-2.0
2,230
/** * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package kafka.manager.utils.zero81 import kafka.common.TopicAndPartition import kafka.manager.utils._ import kafka.manager.ActorModel.{TopicPartitionIdentity, TopicIdentity} import org.apache.curator.framework.CuratorFramework import org.apache.zookeeper.KeeperException.NodeExistsException import org.slf4j.LoggerFactory import scala.util.Try /** * Borrowed from kafka 0.8.1.1, adapted to use curator framework * https://git-wip-us.apache.org/repos/asf?p=kafka.git;a=blob;f=core/src/main/scala/kafka/admin/ReassignPartitionsCommand.scala */ import kafka.manager.utils.zero81.ReassignPartitionErrors._ class ReassignPartitionCommand(adminUtils: AdminUtils) { private[this] val logger = LoggerFactory.getLogger(this.getClass) def generateAssignment(brokerList: Seq[Int], currentTopicIdentity: TopicIdentity): Try[TopicIdentity] = { Try { val assignedReplicas = adminUtils.assignReplicasToBrokers( brokerList, currentTopicIdentity.partitions, currentTopicIdentity.replicationFactor) val newTpi: Map[Int, TopicPartitionIdentity] = currentTopicIdentity.partitionsIdentity.map { case (part, tpi) => val newReplicaSeq = assignedReplicas.get(part) checkCondition(newReplicaSeq.isDefined, MissingReplicaSetForPartition(part)) val newReplicaSet = newReplicaSeq.get.toSet checkCondition(newReplicaSeq.get.size == newReplicaSet.size, DuplicateFoundInReplicaSetForPartition(newReplicaSeq.get,part,currentTopicIdentity.topic)) (part, tpi.copy(replicas = newReplicaSeq.get)) } logger.info(s"Generated topic replica assignment topic=${currentTopicIdentity.topic}, $newTpi") TopicIdentity( currentTopicIdentity.topic, currentTopicIdentity.readVersion, currentTopicIdentity.partitions, newTpi, currentTopicIdentity.numBrokers, currentTopicIdentity.configReadVersion, currentTopicIdentity.config, currentTopicIdentity.deleteSupported, currentTopicIdentity.clusterConfig ) } } def validateAssignment(current: TopicIdentity, generated: TopicIdentity): Unit = { //perform validation checkCondition(generated.partitionsIdentity.nonEmpty, ReassignmentDataEmptyForTopic(current.topic)) checkCondition(current.partitions == generated.partitions, PartitionsOutOfSync(current.partitions, generated.partitions)) checkCondition(current.replicationFactor == generated.replicationFactor, ReplicationOutOfSync(current.replicationFactor, generated.replicationFactor)) } def getValidAssignments(currentTopicIdentity: Map[String, TopicIdentity], generatedTopicIdentity: Map[String, TopicIdentity]): Try[Map[TopicAndPartition, Seq[Int]]] = { Try { currentTopicIdentity.flatMap { case (topic, current) => generatedTopicIdentity.get(topic).fold { logger.info(s"No generated assignment found for topic=$topic, skipping") Map.empty[TopicAndPartition, Seq[Int]] } { generated => validateAssignment(current, generated) for { //match up partitions from current to generated (currentPart, currentTpi) <- current.partitionsIdentity generatedTpi <- generated.partitionsIdentity.get(currentPart) } yield { logger.info("Reassigning replicas for topic=%s, partition=%s, current=%s, generated=%s" .format(topic, currentPart, current.partitionsIdentity, generated.partitionsIdentity)) (TopicAndPartition(topic, currentPart), generatedTpi.replicas.toSeq) } } } } } def executeAssignment(curator: CuratorFramework, currentTopicIdentity: Map[String, TopicIdentity], generatedTopicIdentity: Map[String, TopicIdentity]): Try[Unit] = { getValidAssignments(currentTopicIdentity, generatedTopicIdentity).flatMap { validAssignments => Try { checkCondition(validAssignments.nonEmpty, NoValidAssignments) val jsonReassignmentData = ZkUtils.getPartitionReassignmentZkData(validAssignments) try { logger.info(s"Creating reassign partitions path ${ZkUtils.ReassignPartitionsPath} : $jsonReassignmentData") //validate parsing of generated json ReassignPartitionCommand.parsePartitionReassignmentZkData(jsonReassignmentData) ZkUtils.createPersistentPath(curator, ZkUtils.ReassignPartitionsPath, jsonReassignmentData) } catch { case ze: NodeExistsException => throwError(AlreadyInProgress) case e: Throwable => throwError(FailedToReassignPartitionReplicas(e)) } } } } } object ReassignPartitionCommand { def parsePartitionReassignmentZkData(json : String) : Map[TopicAndPartition, Seq[Int]] = { import org.json4s.JsonAST._ parseJson(json).findField(_._1 == "partitions") match { case Some((_, arr)) => val result : List[(TopicAndPartition, Seq[Int])] = for { JArray(elements) <- arr JObject(children) <- elements JField("topic", JString(t)) <- children JField("partition", JInt(i)) <- children JField("replicas", arr2) <- children JArray(assignments) <- arr2 } yield (TopicAndPartition(t,i.toInt),assignments.map(_.extract[Int])) checkCondition(result.nonEmpty, NoValidAssignments) result.foreach { case (tAndP, a) => checkCondition(a.nonEmpty, ReassignmentDataEmptyForTopic(tAndP.topic)) } result.toMap case None => throwError(NoValidAssignments) } } } object ReassignPartitionErrors { class MissingReplicaSetForPartition private[ReassignPartitionErrors](part: Int) extends UtilError(s"Failed to find new replica set for partition $part") class ReassignmentDataEmptyForTopic private[ReassignPartitionErrors](topic: String) extends UtilError(s"Partition reassignment data is empty for topic $topic") class PartitionsOutOfSync private[ReassignPartitionErrors](current: Int, generated: Int) extends UtilError( "Current partitions and generated partition replicas are out of sync current=%s, generated=%s , please regenerate" .format(current, generated)) class ReplicationOutOfSync private[ReassignPartitionErrors](current: Int, generated: Int) extends UtilError( "Current replication factor and generated replication factor for replicas are out of sync current=%s, generated=%s , please regenerate" .format(current, generated)) class NoValidAssignments private[ReassignPartitionErrors] extends UtilError("Cannot reassign partitions with no valid assignments!") class ReassignmentAlreadyInProgress private[ReassignPartitionErrors] extends UtilError("Partition reassignment currently in " + "progress for. Aborting operation") class FailedToReassignPartitionReplicas private[ReassignPartitionErrors] (t: Throwable) extends UtilError( s"Failed to reassign partition replicas ${t.getStackTrace.mkString("[","\\n","]")}") class DuplicateFoundInReplicaSetForPartition private[ReassignPartitionErrors](replicas: Seq[Int], part: Int, topic: String) extends UtilError( s"Duplicate found in replica set $replicas for partition $part for topic $topic" ) def MissingReplicaSetForPartition(part: Int) = new MissingReplicaSetForPartition(part) def ReassignmentDataEmptyForTopic(topic: String) = new ReassignmentDataEmptyForTopic(topic) def PartitionsOutOfSync(current: Int, generated: Int) = new PartitionsOutOfSync(current,generated) def ReplicationOutOfSync(current: Int, generated: Int) = new ReplicationOutOfSync(current,generated) val NoValidAssignments = new NoValidAssignments val AlreadyInProgress = new ReassignmentAlreadyInProgress def FailedToReassignPartitionReplicas(t: Throwable) = new FailedToReassignPartitionReplicas(t) def DuplicateFoundInReplicaSetForPartition(replicas: Seq[Int], part: Int, topic: String) = new DuplicateFoundInReplicaSetForPartition(replicas,part,topic) }
cvcal/kafka-manager
app/kafka/manager/utils/zero81/ReassignPartitionCommand.scala
Scala
apache-2.0
8,918
package controllers import play.api.mvc._ class Application extends Controller { def index: Action[AnyContent] = Action { Ok("Application started.") } }
SBP07/backend
app/controllers/Application.scala
Scala
gpl-2.0
165
/* *\\ ** Squants ** ** ** ** Scala Quantities and Units of Measure Library and DSL ** ** (c) 2013-2015, Gary Keorkunian ** ** ** \\* */ package squants.thermal import squants._ import squants.Platform.crossFormat import squants.energy.Joules import scala.util.{ Failure, Success, Try } /** * Represents a quantity of temperature * * Temperatures are somewhat unique in the world of quantities for a couple of reasons. * * First, different units (scales) have different "zero" values. This means that these scales * are not simple multiples of the others. There is a "zero offset" that must be applied to conversions * from one scale to another. * * Second, temperatures are often quoted as though they were quantities, when in fact they are just points * on a scale. Similar to a mile marker on a highway, the quantity represented is the number degrees (miles) * from a specific "zero" value on the scale. * * In fact an absolute quantity of thermodynamic temperature should be measured from absolute zero. * Thus, Kelvin, is the SI Base unit for temperature. * * The other scales supported here, Celsius and Fahrenheit, are known as empirical scales. * Of course, these scales set their respective zero values well above absolute zero. * This is done to provide a granular and reasonably sized ranges of values for dealing with everyday temperatures. * * This library supports another absolute scale, the Rankine scale. Rankine sets its zero at absolute zero, * but degrees are measure in Fahrenheit (as opposed to Celsius, as the Kelvin scale uses). * * In consideration of these more unique scale conversions, two conversion types are supported: Degrees and Scale. * * Scale based conversions DO adjust for the zero offset. * Thus 5 degrees C is the same as 41 degrees F on the thermometer. * * Degrees based conversions DO NOT adjust for the zero point. * Thus 5 degrees C|K is the same amount of temperature as 9 degrees F|R. * * When creating a temperature it is not important to consider these differences. * It is also irrelevant when performing operation on temperatures in the same scale. * However, when performing operations on two temperatures of different scales these factors do become important. * * The Quantity.to(unit) and Quantity.in(unit) methods are overridden to use Scale conversions for convenience * * The Ordered.compare method is implemented to use Scale conversions * * The Quantity.plus and Quantity.minus methods are implemented to treat right operands as Quantity of Degrees and not a scale Temperature. * Operands that differ in scale will use Degree conversions. * This supports mixed scale expressions: * * val temp = Fahrenheit(100) - Celsius(5) // returns Fahrenheit(91) * * This also supports declaring temperature ranges using typical nomenclature: * * val tempRange = 65.F +- 5.C // returns QuantityRange(56.0°F,74.0°F) * * The toDegrees(unit) methods are implemented to use Degree conversions. * * @author garyKeorkunian * @since 0.1 * * @param value the value of the temperature */ final class Temperature private (val value: Double, val unit: TemperatureScale) extends Quantity[Temperature] { def dimension = Temperature override def plus(that: Temperature): Temperature = Temperature(this.value + that.convert(unit, withOffset = false).value, unit) override def minus(that: Temperature): Temperature = Temperature(this.value - that.convert(unit, withOffset = false).value, unit) def *(that: ThermalCapacity) = Joules(this.toKelvinScale * that.toJoulesPerKelvin) override def toString: String = unit match { case Kelvin => super.toString case _ => crossFormat(value) + unit.symbol // Non-Kelvin units are treated in a special manner, they do not get a space between the value and symbol. } def toString(unit: TemperatureScale): String = in(unit).toString private def convert(toScale: TemperatureScale, withOffset: Boolean = true): Temperature = (unit, toScale, withOffset) match { case (Fahrenheit, Fahrenheit, _) ⇒ this case (Celsius, Celsius, _) ⇒ this case (Kelvin, Kelvin, _) ⇒ this case (Rankine, Rankine, _) ⇒ this case (Fahrenheit, Celsius, true) ⇒ Celsius(TemperatureConversions.fahrenheitToCelsiusScale(value)) case (Celsius, Fahrenheit, true) ⇒ Fahrenheit(TemperatureConversions.celsiusToFahrenheitScale(value)) case (Celsius, Kelvin, true) ⇒ Kelvin(TemperatureConversions.celsiusToKelvinScale(value)) case (Kelvin, Celsius, true) ⇒ Celsius(TemperatureConversions.kelvinToCelsiusScale(value)) case (Fahrenheit, Kelvin, true) ⇒ Kelvin(TemperatureConversions.fahrenheitToKelvinScale(value)) case (Kelvin, Fahrenheit, true) ⇒ Fahrenheit(TemperatureConversions.kelvinToFahrenheitScale(value)) case (Fahrenheit, Rankine, true) ⇒ Rankine(TemperatureConversions.fahrenheitToRankineScale(value)) case (Rankine, Fahrenheit, true) ⇒ Fahrenheit(TemperatureConversions.rankineToFahrenheitScale(value)) case (Celsius, Rankine, true) ⇒ Rankine(TemperatureConversions.celsiusToRankineScale(value)) case (Rankine, Celsius, true) ⇒ Celsius(TemperatureConversions.rankineToCelsiusScale(value)) case (Kelvin, Rankine, true) ⇒ Rankine(TemperatureConversions.kelvinToRankineScale(value)) case (Rankine, Kelvin, true) ⇒ Kelvin(TemperatureConversions.rankineToKelvinScale(value)) case (Fahrenheit, Celsius, false) ⇒ Celsius(TemperatureConversions.fahrenheitToCelsiusDegrees(value)) case (Celsius, Fahrenheit, false) ⇒ Fahrenheit(TemperatureConversions.celsiusToFahrenheitDegrees(value)) case (Celsius, Kelvin, false) ⇒ Kelvin(TemperatureConversions.celsiusToKelvinDegrees(value)) case (Kelvin, Celsius, false) ⇒ Celsius(TemperatureConversions.kelvinToCelsiusDegrees(value)) case (Fahrenheit, Kelvin, false) ⇒ Kelvin(TemperatureConversions.fahrenheitToKelvinDegrees(value)) case (Kelvin, Fahrenheit, false) ⇒ Fahrenheit(TemperatureConversions.kelvinToFahrenheitDegrees(value)) case (Fahrenheit, Rankine, false) ⇒ Rankine(TemperatureConversions.fahrenheitToRankineDegrees(value)) case (Rankine, Fahrenheit, false) ⇒ Fahrenheit(TemperatureConversions.rankineToFahrenheitDegrees(value)) case (Celsius, Rankine, false) ⇒ Rankine(TemperatureConversions.celsiusToRankineDegrees(value)) case (Rankine, Celsius, false) ⇒ Celsius(TemperatureConversions.rankineToCelsiusDegrees(value)) case (Kelvin, Rankine, false) ⇒ Rankine(TemperatureConversions.kelvinToRankineDegrees(value)) case (Rankine, Kelvin, false) ⇒ Kelvin(TemperatureConversions.rankineToKelvinDegrees(value)) } def in(unit: TemperatureScale) = convert(unit, withOffset = true) def inFahrenheit: Temperature = convert(Fahrenheit) def inCelsius: Temperature = convert(Celsius) def inKelvin: Temperature = convert(Kelvin) def to(unit: TemperatureScale) = toScale(unit) def toScale(unit: TemperatureScale) = convert(unit, withOffset = true).value def toFahrenheitScale = toScale(Fahrenheit) def toCelsiusScale = toScale(Celsius) def toKelvinScale = toScale(Kelvin) def toDegrees(unit: TemperatureScale) = convert(unit, withOffset = false).value def toFahrenheitDegrees = toDegrees(Fahrenheit) def toCelsiusDegrees = toDegrees(Celsius) def toKelvinDegrees = toDegrees(Kelvin) } /** * Temperature companion object */ object Temperature extends Dimension[Temperature] with BaseDimension { def apply[A](n: A, scale: TemperatureScale)(implicit num: Numeric[A]) = new Temperature(num.toDouble(n), scale) def apply(s: String): Try[Temperature] = { val regex = "([-+]?[0-9]*\\\\.?[0-9]+(?:[eE][-+]?[0-9]+)?) *°? *(f|F|c|C|k|K|r|R)".r s match { case regex(value, unit) => unit match { case "f" | "F" => Success(Fahrenheit(value.toDouble)) case "c" | "C" => Success(Celsius(value.toDouble)) case "k" | "K" => Success(Kelvin(value.toDouble)) case "r" | "R" => Success(Rankine(value.toDouble)) } case _ => Failure(QuantityParseException("Unable to parse Temperature", s)) } } def name = "Temperature" def primaryUnit = Kelvin def siUnit = Kelvin def units = Set(Kelvin, Fahrenheit, Celsius, Rankine) def dimensionSymbol = "Θ" } /** * Base trait for units of [[squants.thermal.Temperature]] */ sealed trait TemperatureScale extends UnitOfMeasure[Temperature] { def self: TemperatureScale def apply[A](n: A)(implicit num: Numeric[A]) = Temperature(num.toDouble(n), this) } object Celsius extends TemperatureScale { val symbol = "°C" val self = this protected def converterFrom = TemperatureConversions.celsiusToKelvinScale protected def converterTo = TemperatureConversions.kelvinToCelsiusScale def apply(temperature: Temperature): Temperature = temperature.inCelsius } object Fahrenheit extends TemperatureScale { val symbol = "°F" val self = this protected def converterFrom = TemperatureConversions.fahrenheitToKelvinScale protected def converterTo = TemperatureConversions.kelvinToFahrenheitScale def apply(temperature: Temperature): Temperature = temperature.inFahrenheit } object Kelvin extends TemperatureScale with PrimaryUnit with SiBaseUnit { val symbol = "K" val self = this def apply(temperature: Temperature): Temperature = temperature.inKelvin } object Rankine extends TemperatureScale { val symbol = "°R" val self = this protected def converterFrom = TemperatureConversions.rankineToKelvinScale protected def converterTo = TemperatureConversions.kelvinToRankineScale def apply(temperature: Temperature): Temperature = temperature.in(Rankine) } object TemperatureConversions { lazy val kelvin = Kelvin(1) lazy val fahrenheit = Fahrenheit(1) lazy val celsius = Celsius(1) lazy val rankine = Rankine(1) /* * Degree conversions are used to convert a quantity of degrees from one scale to another. * These conversions do not adjust for the zero offset. * Essentially they only do the 9:5 conversion between F degrees and C|K degrees */ def celsiusToFahrenheitDegrees(celsius: Double) = celsius * 9d / 5d def fahrenheitToCelsiusDegrees(fahrenheit: Double) = fahrenheit * 5d / 9d def celsiusToKelvinDegrees(celsius: Double) = celsius def kelvinToCelsiusDegrees(kelvin: Double) = kelvin def fahrenheitToKelvinDegrees(fahrenheit: Double) = fahrenheit * 5d / 9d def kelvinToFahrenheitDegrees(kelvin: Double) = kelvin * 9d / 5d def celsiusToRankineDegrees(celsius: Double) = celsius * 9d / 5d def rankineToCelsiusDegrees(rankine: Double) = rankine * 5d / 9d def fahrenheitToRankineDegrees(fahrenheit: Double) = fahrenheit def rankineToFahrenheitDegrees(rankine: Double) = rankine def kelvinToRankineDegrees(kelvin: Double) = kelvin * 9d / 5d def rankineToKelvinDegrees(rankine: Double) = rankine * 5d / 9d /* * Scale conversions are used to convert a "thermometer" temperature from one scale to another. * These conversions will adjust the result by the zero offset. * They are used to find the equivalent absolute temperature in the other scale. */ def celsiusToFahrenheitScale(celsius: Double) = celsius * 9d / 5d + 32d def fahrenheitToCelsiusScale(fahrenheit: Double) = (fahrenheit - 32d) * 5d / 9d def celsiusToKelvinScale(celsius: Double) = celsius + 273.15 def kelvinToCelsiusScale(kelvin: Double) = kelvin - 273.15 def fahrenheitToKelvinScale(fahrenheit: Double) = (fahrenheit + 459.67) * 5d / 9d def kelvinToFahrenheitScale(kelvin: Double) = kelvin * 9d / 5d - 459.67 def celsiusToRankineScale(celsius: Double) = (celsius + 273.15) * 9d / 5d def rankineToCelsiusScale(rankine: Double) = (rankine - 491.67) * 5d / 9d def fahrenheitToRankineScale(fahrenheit: Double) = fahrenheit + 459.67 def rankineToFahrenheitScale(rankine: Double) = rankine - 459.67 def kelvinToRankineScale(kelvin: Double) = kelvin * 9d / 5d def rankineToKelvinScale(rankine: Double) = rankine * 5d / 9d implicit class TemperatureConversions[A](n: A)(implicit num: Numeric[A]) { def C = Celsius(n) def celsius = Celsius(n) def degreesCelsius = Celsius(n) def F = Fahrenheit(n) def Fah = Fahrenheit(n) // F conflicts with (Float) in the console; Fah is provided as an alternative def fahrenheit = Fahrenheit(n) def degreesFahrenheit = Fahrenheit(n) def K = Kelvin(n) def kelvin = Kelvin(n) def degreesKelvin = Kelvin(n) def R = Rankine(n) def rankine = Rankine(n) def degreesRankine = Rankine(n) } implicit class TemperatureStringConversion(s: String) { def toTemperature = Temperature(s) } }
garyKeorkunian/squants
shared/src/main/scala/squants/thermal/Temperature.scala
Scala
apache-2.0
13,103
package com.emajliramokade package services package interfaces import api.model.EmailProvjera.Odgovor import email.Email import scala.concurrent.Future trait EmailSender { def send(email: Email): Future[Odgovor] }
element-doo/ekade
code/scala/Services/src/main/scala/com/emajliramokade/services/interfaces/EmailSender.scala
Scala
bsd-3-clause
219
case class B(var x: Int) { def succ(): Unit = { x = x + 1 } } object Test { def main(args: Array[String]): Unit = { val b = B(0) b match { case B(x) => //println(x) b.succ() println(x) } } }
yusuke2255/dotty
tests/run/t5158.scala
Scala
bsd-3-clause
246
package gitbucket.core.view import java.text.Normalizer import java.util.regex.Pattern import java.util.Locale import gitbucket.core.controller.Context import gitbucket.core.service.{RepositoryService, RequestCache} import gitbucket.core.util.StringUtil import io.github.gitbucket.markedj._ import io.github.gitbucket.markedj.Utils._ object Markdown { /** * Converts Markdown of Wiki pages to HTML. * * @param repository the repository which contains the markdown * @param enableWikiLink if true then wiki style link is available in markdown * @param enableRefsLink if true then issue reference (e.g. #123) is rendered as link * @param enableAnchor if true then anchor for headline is generated * @param enableTaskList if true then task list syntax is available * @param hasWritePermission true if user has writable to ths given repository * @param pages the list of existing Wiki pages */ def toHtml(markdown: String, repository: RepositoryService.RepositoryInfo, enableWikiLink: Boolean, enableRefsLink: Boolean, enableAnchor: Boolean, enableTaskList: Boolean = false, hasWritePermission: Boolean = false, pages: List[String] = Nil)(implicit context: Context): String = { // escape issue id val s = if(enableRefsLink){ markdown.replaceAll("(?<=(\\\\W|^))#(\\\\d+)(?=(\\\\W|$))", "issue:$2") } else markdown // escape task list val source = if(enableTaskList){ escapeTaskList(s) } else s val options = new Options() options.setSanitize(true) val renderer = new GitBucketMarkedRenderer(options, repository, enableWikiLink, enableRefsLink, enableAnchor, enableTaskList, hasWritePermission, pages) Marked.marked(source, options, renderer) } /** * Extends markedj Renderer for GitBucket */ class GitBucketMarkedRenderer(options: Options, repository: RepositoryService.RepositoryInfo, enableWikiLink: Boolean, enableRefsLink: Boolean, enableAnchor: Boolean, enableTaskList: Boolean, hasWritePermission: Boolean, pages: List[String]) (implicit val context: Context) extends Renderer(options) with LinkConverter with RequestCache { override def heading(text: String, level: Int, raw: String): String = { val id = generateAnchorName(text) val out = new StringBuilder() out.append("<h" + level + " id=\\"" + options.getHeaderPrefix + id + "\\" class=\\"markdown-head\\">") if(enableAnchor){ out.append("<a class=\\"markdown-anchor-link\\" href=\\"#" + id + "\\"></a>") out.append("<a class=\\"markdown-anchor\\" name=\\"" + id + "\\"></a>") } out.append(text) out.append("</h" + level + ">\\n") out.toString() } override def code(code: String, lang: String, escaped: Boolean): String = { "<pre class=\\"prettyprint" + (if(lang != null) s" ${options.getLangPrefix}${lang}" else "" )+ "\\">" + (if(escaped) code else escape(code, true)) + "</pre>" } override def list(body: String, ordered: Boolean): String = { var listType: String = null if (ordered) { listType = "ol" } else { listType = "ul" } if(body.contains("""class="task-list-item-checkbox"""")){ return "<" + listType + " class=\\"task-list\\">\\n" + body + "</" + listType + ">\\n" } else { return "<" + listType + ">\\n" + body + "</" + listType + ">\\n" } } override def listitem(text: String): String = { if(text.contains("""class="task-list-item-checkbox" """)){ return "<li class=\\"task-list-item\\">" + text + "</li>\\n" } else { return "<li>" + text + "</li>\\n" } } override def text(text: String): String = { // convert commit id and username to link. val t1 = if(enableRefsLink) convertRefsLinks(text, repository, "issue:", false) else text // convert task list to checkbox. val t2 = if(enableTaskList) convertCheckBox(t1, hasWritePermission) else t1 t2 } override def link(href: String, title: String, text: String): String = { super.link(fixUrl(href, false), title, text) } override def image(href: String, title: String, text: String): String = { super.image(fixUrl(href, true), title, text) } override def nolink(text: String): String = { if(enableWikiLink && text.startsWith("[[") && text.endsWith("]]")){ val link = text.replaceAll("(^\\\\[\\\\[|\\\\]\\\\]$)", "") val (label, page) = if(link.contains('|')){ val i = link.indexOf('|') (link.substring(0, i), link.substring(i + 1)) } else { (link, link) } val url = repository.httpUrl.replaceFirst("/git/", "/").stripSuffix(".git") + "/wiki/" + StringUtil.urlEncode(page) if(pages.contains(page)){ "<a href=\\"" + url + "\\">" + escape(label) + "</a>" } else { "<a href=\\"" + url + "\\" class=\\"absent\\">" + escape(label) + "</a>" } } else { escape(text) } } private def fixUrl(url: String, isImage: Boolean = false): String = { if(url.startsWith("http://") || url.startsWith("https://") || url.startsWith("/")){ url } else if(url.startsWith("#")){ ("#" + generateAnchorName(url.substring(1))) } else if(!enableWikiLink){ if(context.currentPath.contains("/blob/")){ url + (if(isImage) "?raw=true" else "") } else if(context.currentPath.contains("/tree/")){ val paths = context.currentPath.split("/") val branch = if(paths.length > 3) paths.drop(4).mkString("/") else repository.repository.defaultBranch repository.httpUrl.replaceFirst("/git/", "/").stripSuffix(".git") + "/blob/" + branch + "/" + url + (if(isImage) "?raw=true" else "") } else { val paths = context.currentPath.split("/") val branch = if(paths.length > 3) paths.last else repository.repository.defaultBranch repository.httpUrl.replaceFirst("/git/", "/").stripSuffix(".git") + "/blob/" + branch + "/" + url + (if(isImage) "?raw=true" else "") } } else { repository.httpUrl.replaceFirst("/git/", "/").stripSuffix(".git") + "/wiki/_blob/" + url } } } def escapeTaskList(text: String): String = { Pattern.compile("""^( *)- \\[([x| ])\\] """, Pattern.MULTILINE).matcher(text).replaceAll("$1* task:$2: ") } def generateAnchorName(text: String): String = { val normalized = Normalizer.normalize(text.replaceAll("<.*>", "").replaceAll("[\\\\s]", "-"), Normalizer.Form.NFD) val encoded = StringUtil.urlEncode(normalized) encoded.toLowerCase(Locale.ENGLISH) } def convertCheckBox(text: String, hasWritePermission: Boolean): String = { val disabled = if (hasWritePermission) "" else "disabled" text.replaceAll("task:x:", """<input type="checkbox" class="task-list-item-checkbox" checked="checked" """ + disabled + "/>") .replaceAll("task: :", """<input type="checkbox" class="task-list-item-checkbox" """ + disabled + "/>") } }
uli-heller/gitbucket
src/main/scala/gitbucket/core/view/Markdown.scala
Scala
apache-2.0
7,218
import scala.quoted.* object SourceFiles { type Macro[X] = (=> Quotes) ?=> Expr[X] implicit inline def getThisFile: String = ${getThisFileImpl} def getThisFileImpl: Macro[String] = val q = quotes // Quotes is ByName and hence not stable (q stabilizes it) Expr(q.reflect.SourceFile.current.name) }
dotty-staging/dotty
tests/run-macros/tasty-getfile-implicit-by-name-fun-context/Macro_1.scala
Scala
apache-2.0
320
package is.hail.expr.ir.analyses import is.hail.HailContext import is.hail.expr.ir._ object ComputeMethodSplits { def apply(ir: IR, controlFlowPreventsSplit: Memo[Unit]): Memo[Unit] = { val m = Memo.empty[Unit] val splitThreshold = HailContext.getFlag("method_split_ir_limit").toInt require(splitThreshold > 0, s"invalid method_split_ir_limit") def recurAndComputeSizeUnderneath(x: IR): Int = { val sizeUnderneath = x.children.iterator.map { case child: IR => recurAndComputeSizeUnderneath(child) }.sum val shouldSplit = !controlFlowPreventsSplit.contains(x) && (x match { case _: TailLoop => true // stream consumers case _: ToArray => true case _: ToSet => true case _: ToDict => true case _: StreamFold => true case _: StreamFold2 => true case _: StreamLen => true case _: StreamFor => true case _ => sizeUnderneath > splitThreshold }) if (shouldSplit) { m.bind(x, ()) 0 // method call is small } else { sizeUnderneath + (x match { case _: Ref => 0 case _: In => 0 case _ if IsConstant(x) => 0 case _ => 1 }) } } recurAndComputeSizeUnderneath(ir) m } }
hail-is/hail
hail/src/main/scala/is/hail/expr/ir/analyses/ComputeMethodSplits.scala
Scala
mit
1,283
package sample import language._ import scala.concurrent.duration._ import scala.collection.mutable.ListBuffer import akka.actor._ import akka.cluster._ import akka.cluster.ClusterEvent._ import akka.pattern._ import akka.util._ import akka.event._ import akka.event.Logging._ import akka.io._ import com.typesafe.config.ConfigFactory import scala.concurrent._ import spray.can._ import spray.can.server._ import spray.util._ import spray.http._ import HttpMethods._ import MediaTypes._ //#messages case class TransformationJob(text: String) case class TransformationResult(text: String) case class JobFailed(reason: String, job: TransformationJob) case object BackendRegistration //#messages object ConsoleSample { def main(args: Array[String]): Unit = { // Override the configuration of the port when specified as program argument val config = (if (args.nonEmpty) ConfigFactory.parseString(s"akka.remote.netty.tcp.port=${args(0)}") else ConfigFactory.empty).withFallback( ConfigFactory.parseString("akka.cluster.roles = [console]")). withFallback(ConfigFactory.load()) val system = ActorSystem("ClusterSystem", config) val console = system.actorOf(Props[Manager], name = "console") } } class Manager extends ClusterConsole object TransformationFrontend { def main(args: Array[String]): Unit = { // Override the configuration of the port when specified as program argument val config = (if (args.nonEmpty) ConfigFactory.parseString(s"akka.remote.netty.tcp.port=${args(0)}") else ConfigFactory.empty).withFallback( ConfigFactory.parseString("akka.cluster.roles = [frontend]")). withFallback(ConfigFactory.load()) val system = ActorSystem("ClusterSystem", config) val frontend = system.actorOf(Props[TransformationFrontend], name = "frontend") import system.dispatcher implicit val timeout = Timeout(5 seconds) for (n <- 1 to 120) { (frontend ? TransformationJob("hello-" + n)) onSuccess { case result => println(result) } // wait a while until next request, // to avoid flooding the console with output Thread.sleep(2000) } system.shutdown() } } //#frontend class TransformationFrontend extends Actor { var backends = IndexedSeq.empty[ActorRef] var jobCounter = 0 override def receive = { case job: TransformationJob if backends.isEmpty => sender ! JobFailed("Service unavailable, try again later", job) case job: TransformationJob => jobCounter += 1 backends(jobCounter % backends.size) forward job case BackendRegistration if !backends.contains(sender) => context watch sender backends = backends :+ sender case Terminated(a) => backends = backends.filterNot(_ == a) } } //#frontend object TransformationBackend { def main(args: Array[String]): Unit = { // Override the configuration of the port when specified as program argument val config = (if (args.nonEmpty) ConfigFactory.parseString(s"akka.remote.netty.tcp.port=${args(0)}") else ConfigFactory.empty).withFallback( ConfigFactory.parseString("akka.cluster.roles = [backend]")). withFallback(ConfigFactory.load()) val system = ActorSystem("ClusterSystem", config) system.actorOf(Props[TransformationBackend], name = "backend") } } //#backend class TransformationBackend extends Actor { val cluster = Cluster(context.system) // subscribe to cluster changes, MemberUp // re-subscribe when restart override def preStart(): Unit = cluster.subscribe(self, classOf[MemberUp]) override def postStop(): Unit = cluster.unsubscribe(self) def receive = { case TransformationJob(text) => sender ! TransformationResult(text.toUpperCase) case state: CurrentClusterState => state.members.filter(_.status == MemberStatus.Up) foreach register case MemberUp(m) => register(m) } def register(member: Member): Unit = if (member.hasRole("frontend")) context.actorSelection(RootActorPath(member.address) / "user" / "frontend") ! BackendRegistration } //#backend
ograycode/akka-console
src/main/scala/Sample.scala
Scala
apache-2.0
4,132
package reopp.common.guardedcommands.dataconnectors import reopp.common.{Predicate, Utils} import Utils._ import reopp.common.guardedcommands._ import reopp.common.IntPredicate /** * Creates a Filter: a lossy sync that loses data exactly when a predicate does not hold. * * Created by jose on 07/06/12. */ class GCFilter(a: String, b: String,p: Predicate, positive:Boolean = true) extends GCConnector(List(a,b)) { // /** // * Build guard (formula) from a Predicate // * @param a source end // * @param b sink end // * @param uid unique channel id // * @param p predicate // */ // def this(a: String, b:String, uid: Int, p: Predicate) { // this(a,b,uid,Pred(dataVar(a,uid),p)) // } // /** // * Build guard (formula) from a Predicate // * @param a source end // * @param b sink end // * @param uid unique channel id // * @param p predicate // * @param positive if false consider the negation of the predicate // */ // def this(a: String, b:String, uid: Int, p: Predicate, positive: Boolean) { // this(a, b, uid, if (positive) Pred(dataVar(a,uid),p) // else Neg(Pred(dataVar(a,uid),p))) //} protected def guard: Guard = if (positive) Pred(a.data,p) else Neg(Pred(a.data,p)) def getConstraints = Formula( b --> a, b --> (b := a), //VarAssgn(dataVar(b,uid),dataVar(a,uid)), // bv := av , b --> guard, (a /\\ guard) --> b ) if (!useData) throw new Exception("Filter requires 'useData' option") if (useCC3) throw new Exception("CC3 not implemented") } //object GCFilter { // //} class GCTFilter[A](a: String, b: String, filter: (A) => Boolean) extends GCFilter(a, b, Predicate()(filter)) class GCIFilter[A](a: String, b: String, p: IntPredicate, positive:Boolean = true) extends GCFilter(a, b, p, positive) { override def guard = if (positive) IntPred(a.data,p) else Neg(IntPred(a.data,p)) } class GCGenFilter(a: String, b:String, gfunc: Var => Guard) extends GCFilter(a,b,null) { override def guard: Guard = gfunc.apply( Var(Utils.mkDataVar(a)) ) }
joseproenca/ip-constraints
code/src/main/scala/reopp/common/guardedcommands/dataconnectors/GCFilter.scala
Scala
mit
2,137
package org.elasticsearch.spark.sql import scala.collection.Map import org.apache.commons.logging.Log import org.apache.commons.logging.LogFactory import org.apache.spark.Partition import org.apache.spark.SparkContext import org.apache.spark.TaskContext import org.apache.spark.sql.api.java.Row import org.elasticsearch.hadoop.cfg.Settings import org.elasticsearch.hadoop.rest.InitializationUtils import org.elasticsearch.hadoop.rest.RestService.PartitionDefinition import org.elasticsearch.spark.rdd.AbstractEsRDD import org.elasticsearch.spark.rdd.AbstractEsRDDIterator import org.elasticsearch.spark.rdd.EsPartition // see the comments in ScalaEsRowRDD private[spark] class JavaEsRowRDD( @transient sc: SparkContext, params: Map[String, String] = Map.empty, schema: MappingUtils.Schema) extends AbstractEsRDD[Row](sc, params) { override def compute(split: Partition, context: TaskContext): JavaEsRowRDDIterator = { new JavaEsRowRDDIterator(context, split.asInstanceOf[EsPartition].esPartition, schema) } } private[spark] class JavaEsRowRDDIterator( context: TaskContext, partition: PartitionDefinition, schema: MappingUtils.Schema) extends AbstractEsRDDIterator[Row](context, partition) { override def getLogger() = LogFactory.getLog(classOf[JavaEsRowRDD]) override def initReader(settings: Settings, log: Log) = { InitializationUtils.setValueReaderIfNotSet(settings, classOf[JavaEsRowValueReader], log) // parse the structure and save the order (requested by Spark) for each Row (root and nested) // since the data returned from Elastic is likely to not be in the same order MappingUtils.setRowOrder(settings, schema.struct) } override def createValue(value: Array[Object]): Row = { // drop the ID value(1).asInstanceOf[JavaEsRow] } }
huangll/elasticsearch-hadoop
spark/sql-12/src/main/scala/org/elasticsearch/spark/sql/JavaEsRowRDD.scala
Scala
apache-2.0
1,805
package com.tajpure.scheme.compiler.value import com.tajpure.scheme.compiler.ast.Node import com.tajpure.scheme.compiler.exception.RunTimeException class IntValue(val value: Long) extends Value { override def +(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new IntValue(value + that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new FloatValue(value + that.asInstanceOf[FloatValue].value) } else if (that.isInstanceOf[CharValue]) { new CharValue(value + that.asInstanceOf[CharValue].value) } else if (that.isInstanceOf[StringValue]) { new StringValue(value + that.asInstanceOf[StringValue].value) } else { throw new RunTimeException("type error") } } override def -(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new IntValue(value - that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new FloatValue(value - that.asInstanceOf[FloatValue].value) } else { throw new RunTimeException("type error") } } override def *(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new IntValue(value * that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new FloatValue(value * that.asInstanceOf[FloatValue].value) } else { throw new RunTimeException("type error") } } override def /(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new IntValue(value / that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new FloatValue(value / that.asInstanceOf[FloatValue].value) } else { throw new RunTimeException("type error") } } override def >(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new BoolValue(value > that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new BoolValue(value > that.asInstanceOf[FloatValue].value) } else if (that.isInstanceOf[CharValue]) { new BoolValue(value > that.asInstanceOf[CharValue].value.charAt(0)) } else { throw new RunTimeException("type error") } } override def <(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new BoolValue(value < that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new BoolValue(value < that.asInstanceOf[FloatValue].value) } else if (that.isInstanceOf[CharValue]) { new BoolValue(value < that.asInstanceOf[CharValue].value.charAt(0)) } else { throw new RunTimeException("type error") } } override def <=(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new BoolValue(value <= that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new BoolValue(value <= that.asInstanceOf[FloatValue].value) } else if (that.isInstanceOf[CharValue]) { new BoolValue(value <= that.asInstanceOf[CharValue].value.charAt(0)) } else { throw new RunTimeException("type error") } } override def >=(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new BoolValue(value >= that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new BoolValue(value >= that.asInstanceOf[FloatValue].value) } else if (that.isInstanceOf[CharValue]) { new BoolValue(value >= that.asInstanceOf[CharValue].value.charAt(0)) } else { throw new RunTimeException("type error") } } override def ==(that: Value): Value = { if (that.isInstanceOf[IntValue]) { new BoolValue(value == that.asInstanceOf[IntValue].value) } else if (that.isInstanceOf[FloatValue]) { new BoolValue(value == that.asInstanceOf[FloatValue].value) } else if (that.isInstanceOf[CharValue]) { new BoolValue(value == that.asInstanceOf[CharValue].value.charAt(0)) } else { throw new RunTimeException("type error") } } override def toString(): String = { value.toString() } } object IntValue { // val intVal = new IntValue(10) }
tajpure/SoScheme
src/main/scala/com/tajpure/scheme/compiler/value/IntValue.scala
Scala
gpl-3.0
4,244
/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.flink.table.utils import org.apache.flink.api.java.typeutils.RowTypeInfo import org.apache.flink.table.api.TableSchema import org.apache.flink.table.descriptors.ConnectorDescriptorValidator.{CONNECTOR_PROPERTY_VERSION, CONNECTOR_TYPE} import org.apache.flink.table.descriptors.DescriptorProperties._ import org.apache.flink.table.descriptors.Rowtime._ import org.apache.flink.table.descriptors.Schema._ import org.apache.flink.table.descriptors.{DescriptorProperties, SchemaValidator} import org.apache.flink.table.factories.{StreamTableSinkFactory, StreamTableSourceFactory, TableFactory} import org.apache.flink.table.sinks.StreamTableSink import org.apache.flink.table.sources.StreamTableSource import org.apache.flink.table.types.logical.LogicalTypeRoot import org.apache.flink.table.types.utils.TypeConversions.fromDataTypeToLegacyInfo import org.apache.flink.types.Row import java.sql.Timestamp import java.util /** * Factory for creating stream table sources and sinks. * * See [[MemoryTableSourceSinkUtil.UnsafeMemoryTableSource]] and * [[MemoryTableSourceSinkUtil.UnsafeMemoryAppendTableSink]]. * * @param terminationCount determines when to shutdown the streaming source function */ class InMemoryTableFactory(terminationCount: Int) extends TableFactory with StreamTableSourceFactory[Row] with StreamTableSinkFactory[Row] { override def createStreamTableSink( properties: util.Map[String, String]) : StreamTableSink[Row] = { val params: DescriptorProperties = new DescriptorProperties(true) params.putProperties(properties) // validate new SchemaValidator(true, true, true).validate(params) val tableSchema = SchemaValidator.deriveTableSinkSchema(params) val fieldTypes = tableSchema.getFieldDataTypes.map(t => { if (t.getLogicalType.getTypeRoot == LogicalTypeRoot.TIMESTAMP_WITHOUT_TIME_ZONE) { // force to use Timestamp because old planner only support Timestamp t.bridgedTo(classOf[Timestamp]) } else { t } }) new MemoryTableSourceSinkUtil.UnsafeMemoryAppendTableSink() .configure(tableSchema.getFieldNames, fromDataTypeToLegacyInfo(fieldTypes)) .asInstanceOf[StreamTableSink[Row]] } override def createStreamTableSource( properties: util.Map[String, String]) : StreamTableSource[Row] = { val params: DescriptorProperties = new DescriptorProperties(true) params.putProperties(properties) // validate new SchemaValidator(true, true, true).validate(params) val tableSchema = params.getTableSchema(SCHEMA) // proctime val proctimeAttributeOpt = SchemaValidator.deriveProctimeAttribute(params) val fieldTypes = tableSchema.getFieldDataTypes.map(t => { if (t.getLogicalType.getTypeRoot == LogicalTypeRoot.TIMESTAMP_WITHOUT_TIME_ZONE) { // force to use Timestamp because old planner only support Timestamp t.bridgedTo(classOf[Timestamp]) } else { t } }) val (names, types) = tableSchema.getFieldNames.zip(fromDataTypeToLegacyInfo(fieldTypes)) .filter(_._1 != proctimeAttributeOpt.get()).unzip // rowtime val rowtimeDescriptors = SchemaValidator.deriveRowtimeAttributes(params) new MemoryTableSourceSinkUtil.UnsafeMemoryTableSource( TableSchema.builder().fields(tableSchema.getFieldNames, fieldTypes).build(), new RowTypeInfo(types, names), rowtimeDescriptors, proctimeAttributeOpt.get(), terminationCount) } override def requiredContext(): util.Map[String, String] = { val context: util.Map[String, String] = new util.HashMap[String, String] context.put(CONNECTOR_TYPE, "memory") context.put(CONNECTOR_PROPERTY_VERSION, "1") // backwards compatibility context } override def supportedProperties(): util.List[String] = { val properties = new util.ArrayList[String]() // schema properties.add(SCHEMA + ".#." + SCHEMA_TYPE) properties.add(SCHEMA + ".#." + SCHEMA_DATA_TYPE) properties.add(SCHEMA + ".#." + SCHEMA_NAME) properties.add(SCHEMA + ".#." + SCHEMA_FROM) // time attributes properties.add(SCHEMA + ".#." + SCHEMA_PROCTIME) properties.add(SCHEMA + ".#." + ROWTIME_TIMESTAMPS_TYPE) properties.add(SCHEMA + ".#." + ROWTIME_TIMESTAMPS_FROM) properties.add(SCHEMA + ".#." + ROWTIME_TIMESTAMPS_CLASS) properties.add(SCHEMA + ".#." + ROWTIME_TIMESTAMPS_SERIALIZED) properties.add(SCHEMA + ".#." + ROWTIME_WATERMARKS_TYPE) properties.add(SCHEMA + ".#." + ROWTIME_WATERMARKS_CLASS) properties.add(SCHEMA + ".#." + ROWTIME_WATERMARKS_SERIALIZED) properties.add(SCHEMA + ".#." + ROWTIME_WATERMARKS_DELAY) // watermark properties.add(SCHEMA + "." + WATERMARK + ".#." + WATERMARK_ROWTIME); properties.add(SCHEMA + "." + WATERMARK + ".#." + WATERMARK_STRATEGY_EXPR); properties.add(SCHEMA + "." + WATERMARK + ".#." + WATERMARK_STRATEGY_DATA_TYPE); // computed column properties.add(SCHEMA + ".#." + TABLE_SCHEMA_EXPR) properties } }
GJL/flink
flink-table/flink-table-planner/src/test/scala/org/apache/flink/table/utils/InMemoryTableFactory.scala
Scala
apache-2.0
5,862
/* __ *\\ ** ________ ___ / / ___ Scala API ** ** / __/ __// _ | / / / _ | (c) 2003-2013, LAMP/EPFL ** ** __\\ \\/ /__/ __ |/ /__/ __ | http://scala-lang.org/ ** ** /____/\\___/_/ |_/____/_/ | | ** ** |/ ** \\* */ package scala package collection import generic._ import mutable.{ Builder } import scala.annotation.migration import scala.annotation.unchecked.{ uncheckedVariance => uV } import parallel.ParIterable import scala.language.higherKinds /** A template trait for traversable collections of type `Traversable[A]`. * * $traversableInfo * @define mutability * @define traversableInfo * This is a base trait of all kinds of $mutability Scala collections. It * implements the behavior common to all collections, in terms of a method * `foreach` with signature: * {{{ * def foreach[U](f: Elem => U): Unit * }}} * Collection classes mixing in this trait provide a concrete * `foreach` method which traverses all the * elements contained in the collection, applying a given function to each. * They also need to provide a method `newBuilder` * which creates a builder for collections of the same kind. * * A traversable class might or might not have two properties: strictness * and orderedness. Neither is represented as a type. * * The instances of a strict collection class have all their elements * computed before they can be used as values. By contrast, instances of * a non-strict collection class may defer computation of some of their * elements until after the instance is available as a value. * A typical example of a non-strict collection class is a * [[scala.collection.immutable.Stream]]. * A more general class of examples are `TraversableViews`. * * If a collection is an instance of an ordered collection class, traversing * its elements with `foreach` will always visit elements in the * same order, even for different runs of the program. If the class is not * ordered, `foreach` can visit elements in different orders for * different runs (but it will keep the same order in the same run).' * * A typical example of a collection class which is not ordered is a * `HashMap` of objects. The traversal order for hash maps will * depend on the hash codes of its elements, and these hash codes might * differ from one run to the next. By contrast, a `LinkedHashMap` * is ordered because its `foreach` method visits elements in the * order they were inserted into the `HashMap`. * * @author Martin Odersky * @version 2.8 * @since 2.8 * @tparam A the element type of the collection * @tparam Repr the type of the actual collection containing the elements. * * @define Coll Traversable * @define coll traversable collection */ trait TraversableLike[+A, +Repr] extends Any with HasNewBuilder[A, Repr] with FilterMonadic[A, Repr] with TraversableOnce[A] with GenTraversableLike[A, Repr] with Parallelizable[A, ParIterable[A]] { self => import Traversable.breaks._ /** The type implementing this traversable */ protected[this] type Self = Repr /** The collection of type $coll underlying this `TraversableLike` object. * By default this is implemented as the `TraversableLike` object itself, * but this can be overridden. */ def repr: Repr = this.asInstanceOf[Repr] final def isTraversableAgain: Boolean = true /** The underlying collection seen as an instance of `$Coll`. * By default this is implemented as the current collection object itself, * but this can be overridden. */ protected[this] def thisCollection: Traversable[A] = this.asInstanceOf[Traversable[A]] /** A conversion from collections of type `Repr` to `$Coll` objects. * By default this is implemented as just a cast, but this can be overridden. */ protected[this] def toCollection(repr: Repr): Traversable[A] = repr.asInstanceOf[Traversable[A]] /** Creates a new builder for this collection type. */ protected[this] def newBuilder: Builder[A, Repr] protected[this] def parCombiner = ParIterable.newCombiner[A] /** Applies a function `f` to all elements of this $coll. * * @param f the function that is applied for its side-effect to every element. * The result of function `f` is discarded. * * @tparam U the type parameter describing the result of function `f`. * This result will always be ignored. Typically `U` is `Unit`, * but this is not necessary. * * @usecase def foreach(f: A => Unit): Unit * @inheritdoc * * Note: this method underlies the implementation of most other bulk operations. * It's important to implement this method in an efficient way. * */ def foreach[U](f: A => U): Unit /** Tests whether this $coll is empty. * * @return `true` if the $coll contain no elements, `false` otherwise. */ def isEmpty: Boolean = { var result = true breakable { for (x <- this) { result = false break } } result } def hasDefiniteSize = true def ++[B >: A, That](that: GenTraversableOnce[B])(implicit bf: CanBuildFrom[Repr, B, That]): That = { val b = bf(repr) if (that.isInstanceOf[IndexedSeqLike[_, _]]) b.sizeHint(this, that.seq.size) b ++= thisCollection b ++= that.seq b.result } /** As with `++`, returns a new collection containing the elements from the left operand followed by the * elements from the right operand. * * It differs from `++` in that the right operand determines the type of * the resulting collection rather than the left one. * Mnemonic: the COLon is on the side of the new COLlection type. * * @param that the traversable to append. * @tparam B the element type of the returned collection. * @tparam That $thatinfo * @param bf $bfinfo * @return a new collection of type `That` which contains all elements * of this $coll followed by all elements of `that`. * * @usecase def ++:[B](that: TraversableOnce[B]): $Coll[B] * @inheritdoc * * Example: * {{{ * scala> val x = List(1) * x: List[Int] = List(1) * * scala> val y = LinkedList(2) * y: scala.collection.mutable.LinkedList[Int] = LinkedList(2) * * scala> val z = x ++: y * z: scala.collection.mutable.LinkedList[Int] = LinkedList(1, 2) * }}} * * @return a new $coll which contains all elements of this $coll * followed by all elements of `that`. */ def ++:[B >: A, That](that: TraversableOnce[B])(implicit bf: CanBuildFrom[Repr, B, That]): That = { val b = bf(repr) if (that.isInstanceOf[IndexedSeqLike[_, _]]) b.sizeHint(this, that.size) b ++= that b ++= thisCollection b.result } /** As with `++`, returns a new collection containing the elements from the * left operand followed by the elements from the right operand. * * It differs from `++` in that the right operand determines the type of * the resulting collection rather than the left one. * Mnemonic: the COLon is on the side of the new COLlection type. * * Example: * {{{ * scala> val x = List(1) * x: List[Int] = List(1) * * scala> val y = LinkedList(2) * y: scala.collection.mutable.LinkedList[Int] = LinkedList(2) * * scala> val z = x ++: y * z: scala.collection.mutable.LinkedList[Int] = LinkedList(1, 2) * }}} * * This overload exists because: for the implementation of `++:` we should * reuse that of `++` because many collections override it with more * efficient versions. * * Since `TraversableOnce` has no `++` method, we have to implement that * directly, but `Traversable` and down can use the overload. * * @param that the traversable to append. * @tparam B the element type of the returned collection. * @tparam That $thatinfo * @param bf $bfinfo * @return a new collection of type `That` which contains all elements * of this $coll followed by all elements of `that`. */ def ++:[B >: A, That](that: Traversable[B])(implicit bf: CanBuildFrom[Repr, B, That]): That = (that ++ seq)(breakOut) def map[B, That](f: A => B)(implicit bf: CanBuildFrom[Repr, B, That]): That = { def builder = { // extracted to keep method size under 35 bytes, so that it can be JIT-inlined val b = bf(repr) b.sizeHint(this) b } val b = builder for (x <- this) b += f(x) b.result } def flatMap[B, That](f: A => GenTraversableOnce[B])(implicit bf: CanBuildFrom[Repr, B, That]): That = { def builder = bf(repr) // extracted to keep method size under 35 bytes, so that it can be JIT-inlined val b = builder for (x <- this) b ++= f(x).seq b.result } private[scala] def filterImpl(p: A => Boolean, isFlipped: Boolean): Repr = { val b = newBuilder for (x <- this) if (p(x) != isFlipped) b += x b.result } /** Selects all elements of this $coll which satisfy a predicate. * * @param p the predicate used to test elements. * @return a new $coll consisting of all elements of this $coll that satisfy the given * predicate `p`. The order of the elements is preserved. */ def filter(p: A => Boolean): Repr = filterImpl(p, isFlipped = false) /** Selects all elements of this $coll which do not satisfy a predicate. * * @param p the predicate used to test elements. * @return a new $coll consisting of all elements of this $coll that do not satisfy the given * predicate `p`. The order of the elements is preserved. */ def filterNot(p: A => Boolean): Repr = filterImpl(p, isFlipped = true) def collect[B, That](pf: PartialFunction[A, B])(implicit bf: CanBuildFrom[Repr, B, That]): That = { val b = bf(repr) foreach(pf.runWith(b += _)) b.result } /** Builds a new collection by applying an option-valued function to all * elements of this $coll on which the function is defined. * * @param f the option-valued function which filters and maps the $coll. * @tparam B the element type of the returned collection. * @tparam That $thatinfo * @param bf $bfinfo * @return a new collection of type `That` resulting from applying the option-valued function * `f` to each element and collecting all defined results. * The order of the elements is preserved. * * @usecase def filterMap[B](f: A => Option[B]): $Coll[B] * @inheritdoc * * @param pf the partial function which filters and maps the $coll. * @return a new $coll resulting from applying the given option-valued function * `f` to each element and collecting all defined results. * The order of the elements is preserved. def filterMap[B, That](f: A => Option[B])(implicit bf: CanBuildFrom[Repr, B, That]): That = { val b = bf(repr) for (x <- this) f(x) match { case Some(y) => b += y case _ => } b.result } */ /** Partitions this $coll in two ${coll}s according to a predicate. * * @param p the predicate on which to partition. * @return a pair of ${coll}s: the first $coll consists of all elements that * satisfy the predicate `p` and the second $coll consists of all elements * that don't. The relative order of the elements in the resulting ${coll}s * is the same as in the original $coll. */ def partition(p: A => Boolean): (Repr, Repr) = { val l, r = newBuilder for (x <- this) (if (p(x)) l else r) += x (l.result, r.result) } def groupBy[K](f: A => K): immutable.Map[K, Repr] = { val m = mutable.Map.empty[K, Builder[A, Repr]] for (elem <- this) { val key = f(elem) val bldr = m.getOrElseUpdate(key, newBuilder) bldr += elem } val b = immutable.Map.newBuilder[K, Repr] for ((k, v) <- m) b += ((k, v.result)) b.result } def forall(p: A => Boolean): Boolean = { var result = true breakable { for (x <- this) if (!p(x)) { result = false; break } } result } /** Tests whether a predicate holds for at least one element of this $coll. * * $mayNotTerminateInf * * @param p the predicate used to test elements. * @return `false` if this $coll is empty, otherwise `true` if the given predicate `p` * holds for some of the elements of this $coll, otherwise `false` */ def exists(p: A => Boolean): Boolean = { var result = false breakable { for (x <- this) if (p(x)) { result = true; break } } result } def find(p: A => Boolean): Option[A] = { var result: Option[A] = None breakable { for (x <- this) if (p(x)) { result = Some(x); break } } result } def scan[B >: A, That](z: B)(op: (B, B) => B)(implicit cbf: CanBuildFrom[Repr, B, That]): That = scanLeft(z)(op) def scanLeft[B, That](z: B)(op: (B, A) => B)(implicit bf: CanBuildFrom[Repr, B, That]): That = { val b = bf(repr) b.sizeHint(this, 1) var acc = z b += acc for (x <- this) { acc = op(acc, x); b += acc } b.result } @migration("The behavior of `scanRight` has changed. The previous behavior can be reproduced with scanRight.reverse.", "2.9.0") def scanRight[B, That](z: B)(op: (A, B) => B)(implicit bf: CanBuildFrom[Repr, B, That]): That = { var scanned = List(z) var acc = z for (x <- reversed) { acc = op(x, acc) scanned ::= acc } val b = bf(repr) for (elem <- scanned) b += elem b.result } /** Selects the first element of this $coll. * $orderDependent * @return the first element of this $coll. * @throws NoSuchElementException if the $coll is empty. */ def head: A = { var result: () => A = () => throw new NoSuchElementException breakable { for (x <- this) { result = () => x break } } result() } /** Optionally selects the first element. * $orderDependent * @return the first element of this $coll if it is nonempty, * `None` if it is empty. */ def headOption: Option[A] = if (isEmpty) None else Some(head) /** Selects all elements except the first. * $orderDependent * @return a $coll consisting of all elements of this $coll * except the first one. * @throws `UnsupportedOperationException` if the $coll is empty. */ override def tail: Repr = { if (isEmpty) throw new UnsupportedOperationException("empty.tail") drop(1) } /** Selects the last element. * $orderDependent * @return The last element of this $coll. * @throws NoSuchElementException If the $coll is empty. */ def last: A = { var lst = head for (x <- this) lst = x lst } /** Optionally selects the last element. * $orderDependent * @return the last element of this $coll$ if it is nonempty, * `None` if it is empty. */ def lastOption: Option[A] = if (isEmpty) None else Some(last) /** Selects all elements except the last. * $orderDependent * @return a $coll consisting of all elements of this $coll * except the last one. * @throws UnsupportedOperationException if the $coll is empty. */ def init: Repr = { if (isEmpty) throw new UnsupportedOperationException("empty.init") var lst = head var follow = false val b = newBuilder b.sizeHint(this, -1) for (x <- this) { if (follow) b += lst else follow = true lst = x } b.result } def take(n: Int): Repr = slice(0, n) def drop(n: Int): Repr = if (n <= 0) { val b = newBuilder b.sizeHint(this) (b ++= thisCollection).result } else sliceWithKnownDelta(n, Int.MaxValue, -n) def slice(from: Int, until: Int): Repr = sliceWithKnownBound(scala.math.max(from, 0), until) // Precondition: from >= 0, until > 0, builder already configured for building. private[this] def sliceInternal(from: Int, until: Int, b: Builder[A, Repr]): Repr = { var i = 0 breakable { for (x <- this) { if (i >= from) b += x i += 1 if (i >= until) break } } b.result } // Precondition: from >= 0 private[scala] def sliceWithKnownDelta(from: Int, until: Int, delta: Int): Repr = { val b = newBuilder if (until <= from) b.result else { b.sizeHint(this, delta) sliceInternal(from, until, b) } } // Precondition: from >= 0 private[scala] def sliceWithKnownBound(from: Int, until: Int): Repr = { val b = newBuilder if (until <= from) b.result else { b.sizeHintBounded(until - from, this) sliceInternal(from, until, b) } } def takeWhile(p: A => Boolean): Repr = { val b = newBuilder breakable { for (x <- this) { if (!p(x)) break b += x } } b.result } def dropWhile(p: A => Boolean): Repr = { val b = newBuilder var go = false for (x <- this) { if (!go && !p(x)) go = true if (go) b += x } b.result } def span(p: A => Boolean): (Repr, Repr) = { val l, r = newBuilder var toLeft = true for (x <- this) { toLeft = toLeft && p(x) (if (toLeft) l else r) += x } (l.result, r.result) } def splitAt(n: Int): (Repr, Repr) = { val l, r = newBuilder l.sizeHintBounded(n, this) if (n >= 0) r.sizeHint(this, -n) var i = 0 for (x <- this) { (if (i < n) l else r) += x i += 1 } (l.result, r.result) } /** Iterates over the tails of this $coll. The first value will be this * $coll and the final one will be an empty $coll, with the intervening * values the results of successive applications of `tail`. * * @return an iterator over all the tails of this $coll * @example `List(1,2,3).tails = Iterator(List(1,2,3), List(2,3), List(3), Nil)` */ def tails: Iterator[Repr] = iterateUntilEmpty(_.tail) /** Iterates over the inits of this $coll. The first value will be this * $coll and the final one will be an empty $coll, with the intervening * values the results of successive applications of `init`. * * @return an iterator over all the inits of this $coll * @example `List(1,2,3).inits = Iterator(List(1,2,3), List(1,2), List(1), Nil)` */ def inits: Iterator[Repr] = iterateUntilEmpty(_.init) def copyToArray[B >: A](xs: Array[B], start: Int, len: Int) { var i = start val end = (start + len) min xs.length breakable { for (x <- this) { if (i >= end) break xs(i) = x i += 1 } } } @deprecatedOverriding("Enforce contract of toTraversable that if it is Traversable it returns itself.", "2.11.0") def toTraversable: Traversable[A] = thisCollection def toIterator: Iterator[A] = toStream.iterator def toStream: Stream[A] = toBuffer.toStream // Override to provide size hint. override def to[Col[_]](implicit cbf: CanBuildFrom[Nothing, A, Col[A @uV]]): Col[A @uV] = { val b = cbf() b.sizeHint(this) b ++= thisCollection b.result } /** Converts this $coll to a string. * * @return a string representation of this collection. By default this * string consists of the `stringPrefix` of this $coll, followed * by all elements separated by commas and enclosed in parentheses. */ override def toString = mkString(stringPrefix + "(", ", ", ")") /** Defines the prefix of this object's `toString` representation. * * @return a string representation which starts the result of `toString` * applied to this $coll. By default the string prefix is the * simple name of the collection class $coll. */ def stringPrefix: String = { /* This method is written in a style that avoids calling `String.split()` * as well as methods of java.lang.Character that require the Unicode * database information. This is mostly important for Scala.js, so that * using the collection library does automatically bring java.util.regex.* * and the Unicode database in the generated code. * * This algorithm has the additional benefit that it won't allocate * anything except the result String in the common case, where the class * is not an inner class (i.e., when the result contains no '.'). */ val fqn = repr.getClass.getName var pos: Int = fqn.length - 1 // Skip trailing $'s while (pos != -1 && fqn.charAt(pos) == '$') { pos -= 1 } if (pos == -1 || fqn.charAt(pos) == '.') { return "" } var result: String = "" while (true) { // Invariant: if we enter the loop, there is a non-empty part // Look for the beginning of the part, remembering where was the last non-digit val partEnd = pos + 1 while (pos != -1 && fqn.charAt(pos) <= '9' && fqn.charAt(pos) >= '0') { pos -= 1 } val lastNonDigit = pos while (pos != -1 && fqn.charAt(pos) != '$' && fqn.charAt(pos) != '.') { pos -= 1 } val partStart = pos + 1 // A non-last part which contains only digits marks a method-local part -> drop the prefix if (pos == lastNonDigit && partEnd != fqn.length) { return result } // Skip to the next part, and determine whether we are the end while (pos != -1 && fqn.charAt(pos) == '$') { pos -= 1 } val atEnd = pos == -1 || fqn.charAt(pos) == '.' // Handle the actual content of the part (we ignore parts that are likely synthetic) def isPartLikelySynthetic = { val firstChar = fqn.charAt(partStart) (firstChar > 'Z' && firstChar < 0x7f) || (firstChar < 'A') } if (atEnd || !isPartLikelySynthetic) { val part = fqn.substring(partStart, partEnd) result = if (result.isEmpty) part else part + '.' + result if (atEnd) return result } } // dead code result } /** Creates a non-strict view of this $coll. * * @return a non-strict view of this $coll. */ def view = new TraversableView[A, Repr] { protected lazy val underlying = self.repr override def foreach[U](f: A => U) = self foreach f } /** Creates a non-strict view of a slice of this $coll. * * Note: the difference between `view` and `slice` is that `view` produces * a view of the current $coll, whereas `slice` produces a new $coll. * * Note: `view(from, to)` is equivalent to `view.slice(from, to)` * $orderDependent * * @param from the index of the first element of the view * @param until the index of the element following the view * @return a non-strict view of a slice of this $coll, starting at index `from` * and extending up to (but not including) index `until`. */ def view(from: Int, until: Int): TraversableView[A, Repr] = view.slice(from, until) /** Creates a non-strict filter of this $coll. * * Note: the difference between `c filter p` and `c withFilter p` is that * the former creates a new collection, whereas the latter only * restricts the domain of subsequent `map`, `flatMap`, `foreach`, * and `withFilter` operations. * $orderDependent * * @param p the predicate used to test elements. * @return an object of class `WithFilter`, which supports * `map`, `flatMap`, `foreach`, and `withFilter` operations. * All these operations apply to those elements of this $coll * which satisfy the predicate `p`. */ def withFilter(p: A => Boolean): FilterMonadic[A, Repr] = new WithFilter(p) /** A class supporting filtered operations. Instances of this class are * returned by method `withFilter`. */ class WithFilter(p: A => Boolean) extends FilterMonadic[A, Repr] { /** Builds a new collection by applying a function to all elements of the * outer $coll containing this `WithFilter` instance that satisfy predicate `p`. * * @param f the function to apply to each element. * @tparam B the element type of the returned collection. * @tparam That $thatinfo * @param bf $bfinfo * @return a new collection of type `That` resulting from applying * the given function `f` to each element of the outer $coll * that satisfies predicate `p` and collecting the results. * * @usecase def map[B](f: A => B): $Coll[B] * @inheritdoc * * @return a new $coll resulting from applying the given function * `f` to each element of the outer $coll that satisfies * predicate `p` and collecting the results. */ def map[B, That](f: A => B)(implicit bf: CanBuildFrom[Repr, B, That]): That = { val b = bf(repr) for (x <- self) if (p(x)) b += f(x) b.result } /** Builds a new collection by applying a function to all elements of the * outer $coll containing this `WithFilter` instance that satisfy * predicate `p` and concatenating the results. * * @param f the function to apply to each element. * @tparam B the element type of the returned collection. * @tparam That $thatinfo * @param bf $bfinfo * @return a new collection of type `That` resulting from applying * the given collection-valued function `f` to each element * of the outer $coll that satisfies predicate `p` and * concatenating the results. * * @usecase def flatMap[B](f: A => TraversableOnce[B]): $Coll[B] * @inheritdoc * * The type of the resulting collection will be guided by the static type * of the outer $coll. * * @return a new $coll resulting from applying the given * collection-valued function `f` to each element of the * outer $coll that satisfies predicate `p` and concatenating * the results. */ def flatMap[B, That](f: A => GenTraversableOnce[B])(implicit bf: CanBuildFrom[Repr, B, That]): That = { val b = bf(repr) for (x <- self) if (p(x)) b ++= f(x).seq b.result } /** Applies a function `f` to all elements of the outer $coll containing * this `WithFilter` instance that satisfy predicate `p`. * * @param f the function that is applied for its side-effect to every element. * The result of function `f` is discarded. * * @tparam U the type parameter describing the result of function `f`. * This result will always be ignored. Typically `U` is `Unit`, * but this is not necessary. * * @usecase def foreach(f: A => Unit): Unit * @inheritdoc */ def foreach[U](f: A => U): Unit = for (x <- self) if (p(x)) f(x) /** Further refines the filter for this $coll. * * @param q the predicate used to test elements. * @return an object of class `WithFilter`, which supports * `map`, `flatMap`, `foreach`, and `withFilter` operations. * All these operations apply to those elements of this $coll which * satisfy the predicate `q` in addition to the predicate `p`. */ def withFilter(q: A => Boolean): WithFilter = new WithFilter(x => p(x) && q(x)) } // A helper for tails and inits. private def iterateUntilEmpty(f: Traversable[A @uV] => Traversable[A @uV]): Iterator[Repr] = { val it = Iterator.iterate(thisCollection)(f) takeWhile (x => !x.isEmpty) it ++ Iterator(Nil) map (x => (newBuilder ++= x).result) } }
felixmulder/scala
src/library/scala/collection/TraversableLike.scala
Scala
bsd-3-clause
28,643
package org.dsa.test /** * Created by xubo on 2016/11/18. */ object test1118 { def main(args: Array[String]) { println('a'.toInt) println('A'.toInt) println() } def compute(a: Int, b: Int) { // (a > b) ? a: b } }
xubo245/CloudSW
src/test/scala/org/dsa/test/test1118.scala
Scala
gpl-2.0
246
package org.aja.tej.examples.sparksql.sql import org.aja.tej.utils.TejUtils import org.apache.spark.sql._ import org.apache.spark.sql.expressions.{MutableAggregationBuffer, UserDefinedAggregateFunction} import org.apache.spark.sql.types._ import org.apache.spark.{SparkConf, SparkContext} /* An UDAF inherits the base class UserDefinedAggregateFunction and implements the following eight methods, which are defined as: */ /** * Created by mageswaran on 24/1/16. */ object UDAF { // // A UDAF that sums sales over $500 // private class ScalaAggregateFunction extends UserDefinedAggregateFunction { //inputSchema: inputSchema returns a StructType and every field of this StructType // represents an input argument of this UDAF. // an aggregation function can take multiple arguments in general. but // this one just takes one def inputSchema: StructType = new StructType().add("sales", DoubleType) //bufferSchema: bufferSchema returns a StructType and every field of this StructType // represents a field of this UDAF’s intermediate results. // the aggregation buffer can also have multiple values in general but // this one just has one: the partial sum def bufferSchema: StructType = new StructType().add("sumLargeSales", DoubleType) //dataType: dataType returns a DataType representing the data type of this UDAF’s returned value. // returns just a double: the sum def dataType: DataType = DoubleType //deterministic: deterministic returns a boolean indicating if this UDAF always generate the same // result for a given set of input values. // always gets the same result/ def deterministic: Boolean = true //initialize: initialize is used to initialize values of an aggregation buffer, represented by a MutableAggregationBuffer. // each partial sum is initialized to zero def initialize(buffer: MutableAggregationBuffer): Unit = { buffer.update(0, 0.0) } //update: update is used to update an aggregation buffer represented by a MutableAggregationBuffer for an input Row. // an individual sales value is incorporated by adding it if it exceeds 500.0 def update(buffer: MutableAggregationBuffer, input: Row): Unit = { val sum = buffer.getDouble(0) if (!input.isNullAt(0)) { val sales = input.getDouble(0) if (sales > 500.0) { buffer.update(0, sum + sales) } } } // merge: merge is used to merge two aggregation buffers and store the result to a MutableAggregationBuffer. // buffers are merged by adding the single values in them def merge(buffer1: MutableAggregationBuffer, buffer2: Row): Unit = { buffer1.update(0, buffer1.getDouble(0) + buffer2.getDouble(0)) } //evaluate: evaluate is used to generate the final result value of this UDAF based on values // stored in an aggregation buffer represented by a Row. // the aggregation buffer just has one value: so return it def evaluate(buffer: Row): Any = { buffer.getDouble(0) } } def main(args: Array[String]) { val sc = TejUtils.getSparkContext(this.getClass.getSimpleName) val sqlContext = new SQLContext(sc) import sqlContext.implicits._ val customers = Seq( (1, "Mageswaran", "TN", 15000.00, 150), (2, "Michael", "JR", 24000.00, 300), (3, "Antony Leo", "TN", 10000.00, 50), (4, "Arun", "TN", 18000.00, 90), (5, "Venkat", "ANDRA", 5000.00, 0), (6, "Sathis", "TN", 150000.00, 3000) ) val customerDF = sc.parallelize(customers, 4).toDF("id", "name", "state", "purchaseAmt", "discountAmt") val mysum = new ScalaAggregateFunction() customerDF.printSchema() // register as a temporary table customerDF.registerTempTable("customers") sqlContext.udf.register("mysum", mysum) // now use it in a query val sqlResult = sqlContext.sql( s""" | SELECT state, mysum(purchaseAmt) AS bigsales | FROM customers | GROUP BY state """.stripMargin) sqlResult. printSchema() println() sqlResult. show() } }
Mageswaran1989/aja
src/examples/scala/org/aja/tej/examples/sparksql/sql/UDAF.scala
Scala
apache-2.0
4,184
/* * This software is licensed under the GNU Affero General Public License, quoted below. * * This file is a part of PowerAPI. * * Copyright (C) 2011-2016 Inria, University of Lille 1. * * PowerAPI is free software: you can redistribute it and/or modify * it under the terms of the GNU Affero General Public License as * published by the Free Software Foundation, either version 3 of * the License, or (at your option) any later version. * * PowerAPI is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU Affero General Public License for more details. * * You should have received a copy of the GNU Affero General Public License * along with PowerAPI. * * If not, please consult http://www.gnu.org/licenses/agpl-3.0.html. */ package org.powerapi.core import Numeric._ import grizzled.math.stats._ package object power { type PowerUnit = org.powerapi.core.power.PowerConverter.PowerUnitVal final val MILLIWATTS = org.powerapi.core.power.PowerConverter.MILLIWATTS final val WATTS = org.powerapi.core.power.PowerConverter.WATTS final val KILOWATTS = org.powerapi.core.power.PowerConverter.KILOWATTS final val MEGAWATTS = org.powerapi.core.power.PowerConverter.MEGAWATTS def MAX(s: Seq[Power]): Power = s.map(_.toMilliWatts).max.mW def MIN(s: Seq[Power]): Power = s.map(_.toMilliWatts).min.mW def SUM(s : Seq[Power]): Power = s.map(_.toMilliWatts).sum.mW def MEAN(s: Seq[Power]): Power = mean(s.map(_.toMilliWatts): _*).mW def MEDIAN(s: Seq[Power]): Power = median(s.map(_.toMilliWatts): _*).mW implicit final class DoublePower(private val value: Double) extends AnyVal { def mW: Power = Power(value, MILLIWATTS) def W: Power = Power(value, WATTS) def kW: Power = Power(value, KILOWATTS) def MW: Power = Power(value, MEGAWATTS) } implicit final class LongPower(private val value: Long) extends AnyVal { def mW: Power = Power(value.toDouble, MILLIWATTS) def W: Power = Power(value.toDouble, WATTS) def kW: Power = Power(value.toDouble, KILOWATTS) def MW: Power = Power(value.toDouble, MEGAWATTS) } implicit final class IntPower(private val value: Int) extends AnyVal { def mW: Power = Power(value.toDouble, MILLIWATTS) def W: Power = Power(value.toDouble, WATTS) def kW: Power = Power(value.toDouble, KILOWATTS) def MW: Power = Power(value.toDouble, MEGAWATTS) } }
Spirals-Team/powerapi
powerapi-core/src/main/scala/org/powerapi/core/power/package.scala
Scala
agpl-3.0
2,514
package scawler import akka.actor.{ActorRef, ActorSystem} import akka.util.Timeout import scala.concurrent.Future import scala.io.Source /** A companion object to provide constants and/or factory methods for the DSL. */ private[scawler] object WebCrawlerDSL { val HttpPrefix = "http" } /** Provides an easy-to-use mini DSL for crawling and scraping web pages. */ private[scawler] trait WebCrawlerDSL { import WebCrawlerDSL._ import akka.pattern.ask import scala.concurrent.duration._ /** Defines a new crawler with its own `ActorSystem`. */ def newCrawler(systemName: String)(f: ActorRef => Unit): Unit = f(ActorSystem(systemName).actorOf(HtmlScrapeScatterer())) /** Dispatches the given `ScrapeRequest` to the recipient actor. */ def scrape[T <: ScrapeRequest](req: T)(implicit recipient: ActorRef, timeout: Timeout = Timeout(5.seconds)): Future[Any] = recipient ? req /** Synchronously fetches a collection of URLs to scrape data from. */ def forAllURLs(source: String)(f: String => Unit): Unit = Source.fromFile(source).getLines().collect({ case src if src.startsWith(HttpPrefix) => src case src => HttpPrefix + "://" + src }) foreach f }
scawler/scawler-core
src/main/scala/scawler/WebCrawlerDSL.scala
Scala
apache-2.0
1,198
package com.github.mdr.mash.integration import com.github.mdr.mash.os.MockFileObject._ import com.github.mdr.mash.os.MockFileSystem import com.github.mdr.mash.repl.LineBufferTestHelper._ import com.github.mdr.mash.repl.completions.IncrementalCompletionState import com.github.mdr.mash.utils.Region class IncrementalCompletionIntegrationTest extends AbstractIntegrationTest { "Incremental completion" should "stay incremental as you type characters" in { val repl = makeRepl() repl.input("whe") repl.complete().text should equal("where") val Some(completionState: IncrementalCompletionState) = repl.state.completionStateOpt completionState.replacementLocation should equal(Region(0, "where".length)) val completions = completionState.completions.map(_.displayText) completions should contain("where") completions should contain("whereNot") repl.input("N") val Some(completionState2: IncrementalCompletionState) = repl.state.completionStateOpt } it should "leave incremental completion mode if you type an exact match" in { val repl = makeRepl() repl.input("where").complete().input("Not") repl.state.completionStateOpt should equal(None) } it should "leave incremental completion mode if no longer have any matches" in { val repl = makeRepl() repl.input("where").complete().input("a") repl.state.completionStateOpt should equal(None) } it should "should remove added characters by pressing backspace" in { val repl = makeRepl() repl.input("where").complete().input("N").backspace() repl.text should equal("where") val completionState = repl.incrementalCompletionState val completions = completionState.completions.map(_.displayText) completions should contain("where") completions should contain("whereNot") } it should "should allow further tab completions" in { val repl = makeRepl() repl.input("where").complete().input("N").complete() repl.text should equal("whereNot") repl.state.completionStateOpt should equal(None) } it should "leave incremental completion mode if backspace past the first completion" in { val repl = makeRepl() repl.input("where").complete().input("N").backspace().backspace() repl.state.completionStateOpt should equal(None) } it should "partially complete a common prefix, handling any required escaping" in { val repl = makeRepl( new MockFileSystem(Directory( "foo$bar" -> File(), "foo$baz" -> File()))) repl.input("foo") repl.complete() repl.lineBuffer should equal(lineBuffer(""""foo`$ba"◀""")) val Some(completionState: IncrementalCompletionState) = repl.state.completionStateOpt val completions = completionState.completions.map(_.displayText) completions should equal(Seq("foo$bar", "foo$baz")) } it should "partially complete a common fragment" in { val repl = makeRepl( new MockFileSystem(Directory( "---foobar---" -> File(), "--goobab--" -> File()))) repl.input("ob") repl.complete() repl.lineBuffer should equal(lineBuffer(""""ooba"◀""")) val Some(completionState: IncrementalCompletionState) = repl.state.completionStateOpt val completions = completionState.completions.map(_.displayText) completions should equal(Seq("---foobar---", "--goobab--")) completionState.getCommonDisplayFragment.text should equal("ooba") } it should "handle escaped characters in a common fragment" in { val repl = makeRepl(new MockFileSystem(Directory( "---foob$ar---" -> File(), "--goob$ab--" -> File()))) repl.input("ob") repl.complete() repl.lineBuffer should equal(lineBuffer(""""oob`$a"◀""")) val Some(completionState: IncrementalCompletionState) = repl.state.completionStateOpt val completions = completionState.completions.map(_.displayText) completions should equal(Seq("---foob$ar---", "--goob$ab--")) completionState.getCommonDisplayFragment.text should equal("oob$a") } it should "not have a bug after completing a path" in { val repl = makeRepl(new MockFileSystem(Directory( "etc" -> Directory( "foo.conf" -> File(), "bar.conf" -> File())))) repl.input("/etc/").complete() repl.lineBuffer should equal(lineBuffer(""""/etc/▶"""")) } it should "substring complete with path prefixes" in { val repl = makeRepl(new MockFileSystem(Directory( "etc" -> Directory( "foobar" -> File(), "gooban" -> File())))) repl.input("/etc/ob").complete() repl.lineBuffer should equal(lineBuffer(""""/etc/ooba▶"""")) val Some(completionState: IncrementalCompletionState) = repl.state.completionStateOpt completionState.getCommonDisplayFragment.prefix should equal("/etc/") completionState.getCommonDisplayFragment.text should equal("ooba") val completions = completionState.completions.map(_.displayText) completions should equal(Seq("/etc/foobar", "/etc/gooban")) } }
mdr/mash
src/test/scala/com/github/mdr/mash/integration/IncrementalCompletionIntegrationTest.scala
Scala
mit
5,011
/** * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * */ package com.ksmpartners.ernie.engine.report import com.ksmpartners.ernie.model.{ ReportType, DefinitionEntity } import org.joda.time.DateTime /** * Immutable wrapper class for sharing DefinitionEntity data */ class Definition protected[report] (defEntity: DefinitionEntity) { private lazy val paramNames: Array[String] = { val jParamNames = defEntity.getParamNames if (jParamNames == null) new Array(0) else jParamNames.toArray.map({ _.toString }) } private lazy val unsupportedReportTypes: Array[ReportType] = { val jUnsupportedReportTypes: java.util.List[ReportType] = defEntity.getUnsupportedReportTypes if (jUnsupportedReportTypes == null) new Array(0) else jUnsupportedReportTypes.toArray.map(f => f.asInstanceOf[ReportType]) } def getCreatedDate: DateTime = defEntity.getCreatedDate def getDefId: String = defEntity.getDefId def getCreatedUser: String = defEntity.getCreatedUser def getParamNames: Array[String] = paramNames def getDefDescription: String = defEntity.getDefDescription def getUnsupportedReportTypes: Array[ReportType] = unsupportedReportTypes /** * Get a mutable DefinitionEntity, a representation of the definition that is serializable and used for persistence. */ def getEntity: DefinitionEntity = { val defEnt = new DefinitionEntity() defEnt.setCreatedDate(defEntity.getCreatedDate) defEnt.setCreatedUser(defEntity.getCreatedUser) defEnt.setDefDescription(defEntity.getDefDescription) defEnt.setDefId(defEntity.getDefId) defEnt.setParamNames(defEntity.getParamNames) defEnt.setParams(defEntity.getParams) defEnt.setUnsupportedReportTypes(defEntity.getUnsupportedReportTypes) defEnt } }
ksmpartners/ernie
ernie-engine/src/main/scala/com/ksmpartners/ernie/engine/report/Definition.scala
Scala
apache-2.0
2,275
package com.amazon.datagen.api.rof import com.amazon.mqa.datagen.supplier.{AlphanumericStringSupplier, MinMaxIntegerSupplier} /** * Created by chengpan on 4/20/15. */ object ObjectFactoryTest { def main(args: Array[String]) { val factory = ReflectionObjectFactory( ReflectionObjectFactory.fromSupplier(new MinMaxIntegerSupplier(1, 11)), ReflectionObjectFactory.fromSupplier(new AlphanumericStringSupplier) ) println(factory.create[String]) println(factory.create[Integer]) println(factory.create[Int]) val x = factory.create[TestClassA] println(x) println(factory.create[List[Int]]) } }
leakingtapan/rof-scala
src/test/scala/com/amazon/datagen/api/rof/ObjectFactoryTest.scala
Scala
apache-2.0
643
package com.eevolution.context.dictionary.infrastructure.service import java.util.UUID import akka.NotUsed import com.eevolution.context.dictionary.domain._ import com.eevolution.context.dictionary.domain.model.WorkflowNodeTrl import com.eevolution.utils.PaginatedSequence import com.lightbend.lagom.scaladsl.api.{Service, ServiceCall} /** * Copyright (C) 2003-2017, e-Evolution Consultants S.A. , http://www.e-evolution.com * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. * Email: eduardo.moreno@e-evolution.com, http://www.e-evolution.com , http://github.com/e-Evolution * Created by eduardo.moreno@e-evolution.com , www.e-evolution.com */ /** * Workflow Node Trl Service */ trait WorkflowNodeTrlService extends Service with api.service.WorkflowNodeTrlService { override def getAll() : ServiceCall[NotUsed, List[WorkflowNodeTrl]] override def getById(id: Int): ServiceCall[NotUsed, WorkflowNodeTrl] override def getByUUID(uuid :UUID): ServiceCall[NotUsed, WorkflowNodeTrl] override def getAllByPage(pageNo: Option[Int], pageSize: Option[Int]): ServiceCall[NotUsed, PaginatedSequence[WorkflowNodeTrl]] def descriptor = { import Service._ named("workflowNodeTrl").withCalls( pathCall("/api/v1_0_0/workflowNodeTrl/all", getAll _) , pathCall("/api/v1_0_0/workflowNodeTrl/:id", getById _), pathCall("/api/v1_0_0/workflowNodeTrl/:uuid", getByUUID _) , pathCall("/api/v1_0_0/workflowNodeTrl?pageNo&pageSize", getAllByPage _) ) } }
adempiere/ADReactiveSystem
dictionary-impl/src/main/scala/com/eevolution/context/dictionary/infrastructure/service/WorkflowNodeTrlService.scala
Scala
gpl-3.0
2,096
package nexus.diff.syntax import nexus.diff._ /** * @author Tongfei Chen */ trait TupleExprOpsMixin { implicit class Tuple2ExprOps[F[_], X1, X2](val p: (F[X1], F[X2]))(implicit F: Algebra[F]) { def |>[Y] (f: Func2[X1, X2, Y]): F[Y] = f(p._1, p._2) def |>[Y] (f: PolyFunc2) (implicit ff: f.P[X1, X2, Y]): F[Y] = f(p._1, p._2) } implicit class Tuple3ExprOps[F[_], X1, X2, X3](val t: (F[X1], F[X2], F[X3]))(implicit F: Algebra[F]) { def |>[Y] (f: Func3[X1, X2, X3, Y]): F[Y] = f(t._1, t._2, t._3) def |>[Y] (f: PolyFunc3) (implicit ff: f.P[X1, X2, X3, Y]): F[Y] = f(t._1, t._2, t._3) } }
ctongfei/nexus
diff/src/main/scala/nexus/diff/syntax/TupleExprOps.scala
Scala
mit
671
package org.scalarules.finance.nl import org.scalatest.{FlatSpec, Matchers} class PerTest extends FlatSpec with Matchers { it should "do arithmetic when Termijn is not specified" in { val a: Bedrag Per Termijn = 10.euro per Maand val b: Bedrag Per Termijn = 2.euro per Maand a + b should be(12.euro per Maand) } it should "do addition on a number-like value" in { val a = 1 per Jaar val b = 2 per Jaar a + b should be(3 per Jaar) } it should "throw an exception when Termijnen don't match on addition" in { val a: Bedrag Per Termijn = 10.euro per Maand val b: Bedrag Per Termijn = 2.euro per Jaar intercept[IllegalArgumentException] { a + b } } it should "do subtraction on a number-like value" in { val a = 3.euro per Maand val b = 2.euro per Maand a - b should be(Bedrag(1) per Maand) } it should "throw an exception when Termijnen don't match on subtraction" in { val a: Bedrag Per Termijn = 10.euro per Maand val b: Bedrag Per Termijn = 2.euro per Jaar intercept[IllegalArgumentException] { a - b } } it should "do multiplication on a number-like value" in { val a = 2 per Halfjaar val b = 3 a * b should be(6 per Halfjaar) } it should "do division on a number-like value" in { val a = 6.euro per Jaar val b = 3 a / b should be(2.euro per Jaar) } it should "not do arithmetic on a non-number" in { """("hello" per Maand) + ("world" per Maand)""" shouldNot typeCheck } it should "not mix Periodes" in { "val x: BigDecimal Per Jaar = 10 per Jaar" should compile "val x: BigDecimal Per Jaar = 10 per Maand" shouldNot typeCheck } it should "not mix specified and non-specified Periodes" in { "val x: BigDecimal Per Jaar = 10" shouldNot typeCheck "val x: BigDecimal = 10 per Jaar" shouldNot typeCheck } it should "be convertable from Per Maand to Per Maand" in { (1 per Maand).maandelijks should be(1 per Maand) (3 per Maand).maandelijks should be(3 per Maand) } it should "be convertable from Per Kwartaal to Per Maand" in { (3 per Kwartaal).maandelijks should be(1 per Maand) (7 per Kwartaal).maandelijks should be((BigDecimal(7) / BigDecimal(3)) per Maand) } it should "be convertable from Per Halfjaar to Per Maand" in { (12 per Halfjaar).maandelijks should be(2 per Maand) (9 per Halfjaar).maandelijks should be(BigDecimal("1.5") per Maand) } it should "be convertable from Per Jaar to Per Maand" in { (12 per Jaar).maandelijks should be(1 per Maand) (13 per Jaar).maandelijks should be((BigDecimal(13) / BigDecimal(12)) per Maand) } it should "be convertable from Per Maand to Per Jaar" in { (2 per Maand).jaarlijks should be(24 per Jaar) } it should "be convertable from Per Kwartaal to Per Jaar" in { (3 per Kwartaal).jaarlijks should be(12 per Jaar) } it should "be convertable from Per Halfjaar to Per Jaar" in { (11 per Halfjaar).jaarlijks should be(22 per Jaar) } it should "be convertable from Per Jaar to Per Jaar" in { (24 per Jaar).jaarlijks should be(24 per Jaar) } it should "map over its contents, retaining the same type" in { (1 per Jaar) map (_ + 2) should be(3 per Jaar) ("123.456".euro per Maand) map (_.afgekaptOpEuros) should be("123".euro per Maand) } it should "map over its contents, changing to a different type" in { (1 per Maand) map (_.toString()) should be("1" per Maand) (10.procent per Jaar) map (_ * 10.euro) should be(1.euro per Jaar) } it should "flatMap over its contents, retaining the same type" in { (1 per Jaar) flatMap (_ + 2 per Jaar) should be(3 per Jaar) ("123.456".euro per Maand) flatMap (_.afgekaptOpEuros per Maand) should be("123".euro per Maand) } it should "flatMap over its contents, changing to a different type" in { (1 per Maand) flatMap (_.toString per Maand) should be("1" per Maand) (10.procent per Jaar) flatMap (_ * 10.euro per Jaar) should be(1.euro per Jaar) } it should "be possible to create a for comprehension using Pers" in { val xpm = 10 per Maand val ypm = 12 per Maand val result = for { x <- xpm y <- ypm } yield x + y result should be(22 per Maand) } it should "toString" in { (1 per Maand).toString should be(s"1 per ${Maand.toString}") } } class PerImplicitsTest extends FlatSpec with Matchers { it should "work with boolean operators from Ordered trait" in { val a = Bedrag(10) per Kwartaal val b = Bedrag(2) per Kwartaal a > b should be(true) a < b should be(false) } it should "work with boolean operators from Ordered trait on types that don't directly extend Ordering" in { val a = 10 per Jaar val b = 2 per Jaar a > b should be(true) a < b should be(false) } it should "be Orderable for BigDecimal" in { val list = List(3 per Kwartaal, 2 per Kwartaal, 4 per Kwartaal) list.sorted should be(List(2 per Kwartaal, 3 per Kwartaal, 4 per Kwartaal)) } it should "be Numeric for BigDecimal" in { val list = List(3 per Kwartaal, 2 per Kwartaal, 4 per Kwartaal) list.sum should be(9 per Kwartaal) } it should "be Orderable for Bedrag" in { val list = List(3.euro per Maand, 2.euro per Maand, 4.euro per Maand) list.sorted should be(List(2.euro per Maand, 3.euro per Maand, 4.euro per Maand)) } it should "be Numeric for Bedrag" in { val list = List(3.euro per Maand, 2.euro per Maand, 4.euro per Maand) list.sum should be(9.euro per Maand) } it should "work with boolean operators from Ordered trait when Termijn is not specified" in { val a: Bedrag Per Termijn = 10.euro per Maand val b: Bedrag Per Termijn = 2.euro per Maand a > b should be(true) } it should "throw an exception when Termijnen don't match on boolean operations" in { val a: Bedrag Per Termijn = 10.euro per Maand val b: Bedrag Per Termijn = 2.euro per Jaar intercept[IllegalArgumentException] { a > b } } } class NumericPerPeriodeTest extends FlatSpec with Matchers { val evPeriode = implicitly[Numeric[BigDecimal Per Halfjaar]] val xp = 8 per Halfjaar val yp = 3 per Halfjaar it should "add" in { evPeriode.plus(xp, yp) should be(11 per Halfjaar) } it should "subtract" in { evPeriode.minus(xp, yp) should be(5 per Halfjaar) } it should "refuse to multiply because of the resulting unit" in { intercept[IllegalStateException] { evPeriode.times(xp, yp) } } it should "negate" in { evPeriode.negate(xp) should be(-8 per Halfjaar) } it should "convert from Int" in { evPeriode.fromInt(5) should be(5 per Halfjaar) } it should "convert to Int" in { evPeriode.toInt(xp) should be(8) } it should "convert to Long" in { evPeriode.toLong(xp) should be(8L) } it should "convert to Float" in { evPeriode.toFloat(xp) should be(8.0F) } it should "convert to Double" in { evPeriode.toDouble(xp) should be(8.0D) } it should "compare" in { evPeriode.compare(xp, yp) should be > 0 } } class NumericPerTermijnTest extends FlatSpec with Matchers { val evTermijn = implicitly[Numeric[BigDecimal Per Termijn]] val xt: BigDecimal Per Termijn = 8 per Halfjaar val yt: BigDecimal Per Termijn = 3 per Halfjaar it should "add" in { evTermijn.plus(xt, yt) should be (11 per Halfjaar) } it should "subtract" in { evTermijn.minus(xt, yt) should be (5 per Halfjaar) } it should "refuse to multiply because of the resulting unit" in { intercept[IllegalStateException] { evTermijn.times(xt, yt) } } it should "negate" in { evTermijn.negate(xt) should be (-8 per Halfjaar) } it should "refuse to convert from Int because we don't know the Termijn" in { intercept[IllegalStateException] { evTermijn.fromInt(5) } } it should "convert to Int" in { evTermijn.toInt(xt) should be (8) } it should "convert to Long" in { evTermijn.toLong(xt) should be (8L) } it should "convert to Float" in { evTermijn.toFloat(xt) should be (8.0F) } it should "convert to Double" in { evTermijn.toDouble(xt) should be (8.0D) } it should "compare" in { evTermijn.compare(xt, yt) should be > 0 } }
scala-rules/finance-dsl
src/test/scala/org/scalarules/finance/nl/PerTests.scala
Scala
mit
8,284
/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.spark.metrics import java.io.{File, FileWriter, PrintWriter} import scala.collection.mutable.ArrayBuffer import org.apache.commons.lang3.RandomUtils import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.hadoop.io.{LongWritable, Text} import org.apache.hadoop.mapred.{FileSplit => OldFileSplit, InputSplit => OldInputSplit, JobConf, LineRecordReader => OldLineRecordReader, RecordReader => OldRecordReader, Reporter, TextInputFormat => OldTextInputFormat} import org.apache.hadoop.mapred.lib.{CombineFileInputFormat => OldCombineFileInputFormat, CombineFileRecordReader => OldCombineFileRecordReader, CombineFileSplit => OldCombineFileSplit} import org.apache.hadoop.mapreduce.{InputSplit => NewInputSplit, RecordReader => NewRecordReader, TaskAttemptContext} import org.apache.hadoop.mapreduce.lib.input.{CombineFileInputFormat => NewCombineFileInputFormat, CombineFileRecordReader => NewCombineFileRecordReader, CombineFileSplit => NewCombineFileSplit, FileSplit => NewFileSplit, TextInputFormat => NewTextInputFormat} import org.apache.hadoop.mapreduce.lib.output.{TextOutputFormat => NewTextOutputFormat} import org.scalatest.BeforeAndAfter import org.apache.spark.{SharedSparkContext, SparkFunSuite} import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.scheduler.{SparkListener, SparkListenerTaskEnd} import org.apache.spark.util.Utils class InputOutputMetricsSuite extends SparkFunSuite with SharedSparkContext with BeforeAndAfter { @transient var tmpDir: File = _ @transient var tmpFile: File = _ @transient var tmpFilePath: String = _ @transient val numRecords: Int = 100000 @transient val numBuckets: Int = 10 before { tmpDir = Utils.createTempDir() val testTempDir = new File(tmpDir, "test") testTempDir.mkdir() tmpFile = new File(testTempDir, getClass.getSimpleName + ".txt") val pw = new PrintWriter(new FileWriter(tmpFile)) for (x <- 1 to numRecords) { // scalastyle:off println pw.println(RandomUtils.nextInt(0, numBuckets)) // scalastyle:on println } pw.close() // Path to tmpFile tmpFilePath = "file://" + tmpFile.getAbsolutePath } after { Utils.deleteRecursively(tmpDir) } test("input metrics for old hadoop with coalesce") { val bytesRead = runAndReturnBytesRead { sc.textFile(tmpFilePath, 4).count() } val bytesRead2 = runAndReturnBytesRead { sc.textFile(tmpFilePath, 4).coalesce(2).count() } assert(bytesRead != 0) assert(bytesRead == bytesRead2) assert(bytesRead2 >= tmpFile.length()) } test("input metrics with cache and coalesce") { // prime the cache manager val rdd = sc.textFile(tmpFilePath, 4).cache() rdd.collect() val bytesRead = runAndReturnBytesRead { rdd.count() } val bytesRead2 = runAndReturnBytesRead { rdd.coalesce(4).count() } // for count and coalesce, the same bytes should be read. assert(bytesRead != 0) assert(bytesRead2 == bytesRead) } test("input metrics for new Hadoop API with coalesce") { val bytesRead = runAndReturnBytesRead { sc.newAPIHadoopFile(tmpFilePath, classOf[NewTextInputFormat], classOf[LongWritable], classOf[Text]).count() } val bytesRead2 = runAndReturnBytesRead { sc.newAPIHadoopFile(tmpFilePath, classOf[NewTextInputFormat], classOf[LongWritable], classOf[Text]).coalesce(5).count() } assert(bytesRead != 0) assert(bytesRead2 == bytesRead) assert(bytesRead >= tmpFile.length()) } test("input metrics when reading text file") { val bytesRead = runAndReturnBytesRead { sc.textFile(tmpFilePath, 2).count() } assert(bytesRead >= tmpFile.length()) } test("input metrics on records read - simple") { val records = runAndReturnRecordsRead { sc.textFile(tmpFilePath, 4).count() } assert(records == numRecords) } test("input metrics on records read - more stages") { val records = runAndReturnRecordsRead { sc.textFile(tmpFilePath, 4) .map(key => (key.length, 1)) .reduceByKey(_ + _) .count() } assert(records == numRecords) } test("input metrics on records - New Hadoop API") { val records = runAndReturnRecordsRead { sc.newAPIHadoopFile(tmpFilePath, classOf[NewTextInputFormat], classOf[LongWritable], classOf[Text]).count() } assert(records == numRecords) } test("input metrics on records read with cache") { // prime the cache manager val rdd = sc.textFile(tmpFilePath, 4).cache() rdd.collect() val records = runAndReturnRecordsRead { rdd.count() } assert(records == numRecords) } /** * Tests the metrics from end to end. * 1) reading a hadoop file * 2) shuffle and writing to a hadoop file. * 3) writing to hadoop file. */ test("input read/write and shuffle read/write metrics all line up") { var inputRead = 0L var outputWritten = 0L var shuffleRead = 0L var shuffleWritten = 0L sc.addSparkListener(new SparkListener() { override def onTaskEnd(taskEnd: SparkListenerTaskEnd) { val metrics = taskEnd.taskMetrics inputRead += metrics.inputMetrics.recordsRead outputWritten += metrics.outputMetrics.recordsWritten shuffleRead += metrics.shuffleReadMetrics.recordsRead shuffleWritten += metrics.shuffleWriteMetrics.recordsWritten } }) val tmpFile = new File(tmpDir, getClass.getSimpleName) sc.textFile(tmpFilePath, 4) .map(key => (key, 1)) .reduceByKey(_ + _) .saveAsTextFile("file://" + tmpFile.getAbsolutePath) sc.listenerBus.waitUntilEmpty(500) assert(inputRead == numRecords) // Only supported on newer Hadoop if (SparkHadoopUtil.get.getFSBytesWrittenOnThreadCallback().isDefined) { assert(outputWritten == numBuckets) } assert(shuffleRead == shuffleWritten) } test("input metrics with interleaved reads") { val numPartitions = 2 val cartVector = 0 to 9 val cartFile = new File(tmpDir, getClass.getSimpleName + "_cart.txt") val cartFilePath = "file://" + cartFile.getAbsolutePath // write files to disk so we can read them later. sc.parallelize(cartVector).saveAsTextFile(cartFilePath) val aRdd = sc.textFile(cartFilePath, numPartitions) val tmpRdd = sc.textFile(tmpFilePath, numPartitions) val firstSize = runAndReturnBytesRead { aRdd.count() } val secondSize = runAndReturnBytesRead { tmpRdd.count() } val cartesianBytes = runAndReturnBytesRead { aRdd.cartesian(tmpRdd).count() } // Computing the amount of bytes read for a cartesian operation is a little involved. // Cartesian interleaves reads between two partitions eg. p1 and p2. // Here are the steps: // 1) First it creates an iterator for p1 // 2) Creates an iterator for p2 // 3) Reads the first element of p1 and then all the elements of p2 // 4) proceeds to the next element of p1 // 5) Creates a new iterator for p2 // 6) rinse and repeat. // As a result we read from the second partition n times where n is the number of keys in // p1. Thus the math below for the test. assert(cartesianBytes != 0) assert(cartesianBytes == firstSize * numPartitions + (cartVector.length * secondSize)) } private def runAndReturnBytesRead(job: => Unit): Long = { runAndReturnMetrics(job, _.taskMetrics.inputMetrics.bytesRead) } private def runAndReturnRecordsRead(job: => Unit): Long = { runAndReturnMetrics(job, _.taskMetrics.inputMetrics.recordsRead) } private def runAndReturnRecordsWritten(job: => Unit): Long = { runAndReturnMetrics(job, _.taskMetrics.outputMetrics.recordsWritten) } private def runAndReturnMetrics(job: => Unit, collector: (SparkListenerTaskEnd) => Long): Long = { val taskMetrics = new ArrayBuffer[Long]() // Avoid receiving earlier taskEnd events sc.listenerBus.waitUntilEmpty(500) sc.addSparkListener(new SparkListener() { override def onTaskEnd(taskEnd: SparkListenerTaskEnd) { taskMetrics += collector(taskEnd) } }) job sc.listenerBus.waitUntilEmpty(500) taskMetrics.sum } test("output metrics on records written") { // Only supported on newer Hadoop if (SparkHadoopUtil.get.getFSBytesWrittenOnThreadCallback().isDefined) { val file = new File(tmpDir, getClass.getSimpleName) val filePath = "file://" + file.getAbsolutePath val records = runAndReturnRecordsWritten { sc.parallelize(1 to numRecords).saveAsTextFile(filePath) } assert(records == numRecords) } } test("output metrics on records written - new Hadoop API") { // Only supported on newer Hadoop if (SparkHadoopUtil.get.getFSBytesWrittenOnThreadCallback().isDefined) { val file = new File(tmpDir, getClass.getSimpleName) val filePath = "file://" + file.getAbsolutePath val records = runAndReturnRecordsWritten { sc.parallelize(1 to numRecords).map(key => (key.toString, key.toString)) .saveAsNewAPIHadoopFile[NewTextOutputFormat[String, String]](filePath) } assert(records == numRecords) } } test("output metrics when writing text file") { val fs = FileSystem.getLocal(new Configuration()) val outPath = new Path(fs.getWorkingDirectory, "outdir") if (SparkHadoopUtil.get.getFSBytesWrittenOnThreadCallback().isDefined) { val taskBytesWritten = new ArrayBuffer[Long]() sc.addSparkListener(new SparkListener() { override def onTaskEnd(taskEnd: SparkListenerTaskEnd) { taskBytesWritten += taskEnd.taskMetrics.outputMetrics.bytesWritten } }) val rdd = sc.parallelize(Array("a", "b", "c", "d"), 2) try { rdd.saveAsTextFile(outPath.toString) sc.listenerBus.waitUntilEmpty(500) assert(taskBytesWritten.length == 2) val outFiles = fs.listStatus(outPath).filter(_.getPath.getName != "_SUCCESS") taskBytesWritten.zip(outFiles).foreach { case (bytes, fileStatus) => assert(bytes >= fileStatus.getLen) } } finally { fs.delete(outPath, true) } } } test("input metrics with old CombineFileInputFormat") { val bytesRead = runAndReturnBytesRead { sc.hadoopFile(tmpFilePath, classOf[OldCombineTextInputFormat], classOf[LongWritable], classOf[Text], 2).count() } assert(bytesRead >= tmpFile.length()) } test("input metrics with new CombineFileInputFormat") { val bytesRead = runAndReturnBytesRead { sc.newAPIHadoopFile(tmpFilePath, classOf[NewCombineTextInputFormat], classOf[LongWritable], classOf[Text], new Configuration()).count() } assert(bytesRead >= tmpFile.length()) } } /** * Hadoop 2 has a version of this, but we can't use it for backwards compatibility */ class OldCombineTextInputFormat extends OldCombineFileInputFormat[LongWritable, Text] { override def getRecordReader(split: OldInputSplit, conf: JobConf, reporter: Reporter) : OldRecordReader[LongWritable, Text] = { new OldCombineFileRecordReader[LongWritable, Text](conf, split.asInstanceOf[OldCombineFileSplit], reporter, classOf[OldCombineTextRecordReaderWrapper] .asInstanceOf[Class[OldRecordReader[LongWritable, Text]]]) } } class OldCombineTextRecordReaderWrapper( split: OldCombineFileSplit, conf: Configuration, reporter: Reporter, idx: Integer) extends OldRecordReader[LongWritable, Text] { val fileSplit = new OldFileSplit(split.getPath(idx), split.getOffset(idx), split.getLength(idx), split.getLocations()) val delegate: OldLineRecordReader = new OldTextInputFormat().getRecordReader(fileSplit, conf.asInstanceOf[JobConf], reporter).asInstanceOf[OldLineRecordReader] override def next(key: LongWritable, value: Text): Boolean = delegate.next(key, value) override def createKey(): LongWritable = delegate.createKey() override def createValue(): Text = delegate.createValue() override def getPos(): Long = delegate.getPos override def close(): Unit = delegate.close() override def getProgress(): Float = delegate.getProgress } /** * Hadoop 2 has a version of this, but we can't use it for backwards compatibility */ class NewCombineTextInputFormat extends NewCombineFileInputFormat[LongWritable, Text] { def createRecordReader(split: NewInputSplit, context: TaskAttemptContext) : NewRecordReader[LongWritable, Text] = { new NewCombineFileRecordReader[LongWritable, Text](split.asInstanceOf[NewCombineFileSplit], context, classOf[NewCombineTextRecordReaderWrapper]) } } class NewCombineTextRecordReaderWrapper( split: NewCombineFileSplit, context: TaskAttemptContext, idx: Integer) extends NewRecordReader[LongWritable, Text] { val fileSplit = new NewFileSplit(split.getPath(idx), split.getOffset(idx), split.getLength(idx), split.getLocations()) val delegate = new NewTextInputFormat().createRecordReader(fileSplit, context) override def initialize(split: NewInputSplit, context: TaskAttemptContext): Unit = { delegate.initialize(fileSplit, context) } override def nextKeyValue(): Boolean = delegate.nextKeyValue() override def getCurrentKey(): LongWritable = delegate.getCurrentKey override def getCurrentValue(): Text = delegate.getCurrentValue override def getProgress(): Float = delegate.getProgress override def close(): Unit = delegate.close() }
Panos-Bletsos/spark-cost-model-optimizer
core/src/test/scala/org/apache/spark/metrics/InputOutputMetricsSuite.scala
Scala
apache-2.0
14,397
/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.spark.sql.catalyst.csv import java.util.Locale import scala.util.control.Exception.allCatch import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.analysis.TypeCoercion import org.apache.spark.sql.catalyst.expressions.ExprUtils import org.apache.spark.sql.catalyst.util.TimestampFormatter import org.apache.spark.sql.types._ class CSVInferSchema(val options: CSVOptions) extends Serializable { private val timestampParser = TimestampFormatter( options.timestampFormat, options.zoneId, options.locale) private val decimalParser = if (options.locale == Locale.US) { // Special handling the default locale for backward compatibility s: String => new java.math.BigDecimal(s) } else { ExprUtils.getDecimalParser(options.locale) } /** * Similar to the JSON schema inference * 1. Infer type of each row * 2. Merge row types to find common type * 3. Replace any null types with string type */ def infer( tokenRDD: RDD[Array[String]], header: Array[String]): StructType = { val fields = if (options.inferSchemaFlag) { val startType: Array[DataType] = Array.fill[DataType](header.length)(NullType) val rootTypes: Array[DataType] = tokenRDD.aggregate(startType)(inferRowType, mergeRowTypes) toStructFields(rootTypes, header) } else { // By default fields are assumed to be StringType header.map(fieldName => StructField(fieldName, StringType, nullable = true)) } StructType(fields) } def toStructFields( fieldTypes: Array[DataType], header: Array[String]): Array[StructField] = { header.zip(fieldTypes).map { case (thisHeader, rootType) => val dType = rootType match { case _: NullType => StringType case other => other } StructField(thisHeader, dType, nullable = true) } } def inferRowType(rowSoFar: Array[DataType], next: Array[String]): Array[DataType] = { var i = 0 while (i < math.min(rowSoFar.length, next.length)) { // May have columns on right missing. rowSoFar(i) = inferField(rowSoFar(i), next(i)) i+=1 } rowSoFar } def mergeRowTypes(first: Array[DataType], second: Array[DataType]): Array[DataType] = { first.zipAll(second, NullType, NullType).map { case (a, b) => compatibleType(a, b).getOrElse(NullType) } } /** * Infer type of string field. Given known type Double, and a string "1", there is no * point checking if it is an Int, as the final type must be Double or higher. */ def inferField(typeSoFar: DataType, field: String): DataType = { if (field == null || field.isEmpty || field == options.nullValue) { typeSoFar } else { typeSoFar match { case NullType => tryParseInteger(field) case IntegerType => tryParseInteger(field) case LongType => tryParseLong(field) case _: DecimalType => // DecimalTypes have different precisions and scales, so we try to find the common type. compatibleType(typeSoFar, tryParseDecimal(field)).getOrElse(StringType) case DoubleType => tryParseDouble(field) case TimestampType => tryParseTimestamp(field) case BooleanType => tryParseBoolean(field) case StringType => StringType case other: DataType => throw new UnsupportedOperationException(s"Unexpected data type $other") } } } private def isInfOrNan(field: String): Boolean = { field == options.nanValue || field == options.negativeInf || field == options.positiveInf } private def tryParseInteger(field: String): DataType = { if ((allCatch opt field.toInt).isDefined) { IntegerType } else { tryParseLong(field) } } private def tryParseLong(field: String): DataType = { if ((allCatch opt field.toLong).isDefined) { LongType } else { tryParseDecimal(field) } } private def tryParseDecimal(field: String): DataType = { val decimalTry = allCatch opt { // The conversion can fail when the `field` is not a form of number. val bigDecimal = decimalParser(field) // Because many other formats do not support decimal, it reduces the cases for // decimals by disallowing values having scale (eg. `1.1`). if (bigDecimal.scale <= 0) { // `DecimalType` conversion can fail when // 1. The precision is bigger than 38. // 2. scale is bigger than precision. DecimalType(bigDecimal.precision, bigDecimal.scale) } else { tryParseDouble(field) } } decimalTry.getOrElse(tryParseDouble(field)) } private def tryParseDouble(field: String): DataType = { if ((allCatch opt field.toDouble).isDefined || isInfOrNan(field)) { DoubleType } else { tryParseTimestamp(field) } } private def tryParseTimestamp(field: String): DataType = { // This case infers a custom `dataFormat` is set. if ((allCatch opt timestampParser.parse(field)).isDefined) { TimestampType } else { tryParseBoolean(field) } } private def tryParseBoolean(field: String): DataType = { if ((allCatch opt field.toBoolean).isDefined) { BooleanType } else { stringType() } } // Defining a function to return the StringType constant is necessary in order to work around // a Scala compiler issue which leads to runtime incompatibilities with certain Spark versions; // see issue #128 for more details. private def stringType(): DataType = { StringType } /** * Returns the common data type given two input data types so that the return type * is compatible with both input data types. */ private def compatibleType(t1: DataType, t2: DataType): Option[DataType] = { TypeCoercion.findTightestCommonType(t1, t2).orElse(findCompatibleTypeForCSV(t1, t2)) } /** * The following pattern matching represents additional type promotion rules that * are CSV specific. */ private val findCompatibleTypeForCSV: (DataType, DataType) => Option[DataType] = { case (StringType, t2) => Some(StringType) case (t1, StringType) => Some(StringType) // These two cases below deal with when `IntegralType` is larger than `DecimalType`. case (t1: IntegralType, t2: DecimalType) => compatibleType(DecimalType.forType(t1), t2) case (t1: DecimalType, t2: IntegralType) => compatibleType(t1, DecimalType.forType(t2)) // Double support larger range than fixed decimal, DecimalType.Maximum should be enough // in most case, also have better precision. case (DoubleType, _: DecimalType) | (_: DecimalType, DoubleType) => Some(DoubleType) case (t1: DecimalType, t2: DecimalType) => val scale = math.max(t1.scale, t2.scale) val range = math.max(t1.precision - t1.scale, t2.precision - t2.scale) if (range + scale > 38) { // DecimalType can't support precision > 38 Some(DoubleType) } else { Some(DecimalType(range + scale, scale)) } case _ => None } }
pgandhi999/spark
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVInferSchema.scala
Scala
apache-2.0
7,905
package util import org.scalajs.dom import util.logger.log import scala.concurrent.{ExecutionContext, Future, Promise} import scala.util.control.NonFatal object FutureUtils { type LazyFuture[T] = () => Future[T] // Execute a list of LazyFutures, continuing and ignoring if there is any error. def sequenceWithDelay[T](tasks: List[LazyFuture[T]], ms: Int, ignoreErrors: Boolean)(implicit executionContext: ExecutionContext): Future[List[T]] = { val p = Promise[List[T]]() def exec(acc: List[T], remaining: List[LazyFuture[T]]): Unit = { remaining match { case head :: tail => delay(ms) { () => head().map { result => exec(acc :+ result, tail) }.recover { case NonFatal(ex) if ignoreErrors => log.info(s"Unable to process, Future Skipped - ${ex.getMessage}") exec(acc, tail) case NonFatal(ex) => log.info(s"Unable to process, Stopping - ${ex.getMessage}") p.failure(ex) } } case Nil => p.success(acc) } } exec(List.empty, tasks) p.future } // task like Image GC, need some delay to keep responsive the ui val LongDelay = 200 val SmallDelay = 20 def delay[T](ms: Int)(task: () => Unit) = dom.setTimeout(task, ms) }
felixgborrego/simple-docker-ui
src/main/scala/util/FutureUtils.scala
Scala
mit
1,351
/** * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * <p/> * http://www.apache.org/licenses/LICENSE-2.0 * <p/> * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package kafka.security.auth import kafka.common.{BaseEnum, KafkaException} import org.apache.kafka.common.acl.AclPermissionType sealed trait PermissionType extends BaseEnum { val toJava: AclPermissionType } case object Allow extends PermissionType { val name = "Allow" val toJava = AclPermissionType.ALLOW } case object Deny extends PermissionType { val name = "Deny" val toJava = AclPermissionType.DENY } object PermissionType { def fromString(permissionType: String): PermissionType = { val pType = values.find(pType => pType.name.equalsIgnoreCase(permissionType)) pType.getOrElse(throw new KafkaException(permissionType + " not a valid permissionType name. The valid names are " + values.mkString(","))) } def fromJava(permissionType: AclPermissionType): PermissionType = fromString(permissionType.toString) def values: Seq[PermissionType] = List(Allow, Deny) }
ollie314/kafka
core/src/main/scala/kafka/security/auth/PermissionType.scala
Scala
apache-2.0
1,708
/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.flink.table.planner.plan.nodes.physical.batch import org.apache.flink.table.planner.calcite.FlinkTypeFactory import org.apache.flink.table.planner.plan.nodes.exec.batch.BatchExecOverAggregate import org.apache.flink.table.planner.plan.nodes.exec.spec.{OverSpec, PartitionSpec} import org.apache.flink.table.planner.plan.nodes.exec.{ExecNode, InputProperty} import org.apache.flink.table.planner.plan.utils.OverAggregateUtil import org.apache.calcite.plan._ import org.apache.calcite.rel._ import org.apache.calcite.rel.`type`.RelDataType import org.apache.calcite.rel.core.Window import scala.collection.JavaConversions._ /** * Batch physical RelNode for sort-based over [[Window]] aggregate. */ class BatchPhysicalOverAggregate( cluster: RelOptCluster, traitSet: RelTraitSet, inputRel: RelNode, outputRowType: RelDataType, inputRowType: RelDataType, windowGroups: Seq[Window.Group], logicWindow: Window) extends BatchPhysicalOverAggregateBase( cluster, traitSet, inputRel, outputRowType, inputRowType, windowGroups, logicWindow) { override def deriveRowType: RelDataType = outputRowType override def copy(traitSet: RelTraitSet, inputs: java.util.List[RelNode]): RelNode = { new BatchPhysicalOverAggregate( cluster, traitSet, inputs.get(0), outputRowType, inputRowType, windowGroups, logicWindow) } override def translateToExecNode(): ExecNode[_] = { new BatchExecOverAggregate( new OverSpec( new PartitionSpec(partitionKeyIndices), offsetAndInsensitiveSensitiveGroups.map(OverAggregateUtil.createGroupSpec(_, logicWindow)), logicWindow.constants, OverAggregateUtil.calcOriginalInputFields(logicWindow)), InputProperty.DEFAULT, FlinkTypeFactory.toLogicalRowType(getRowType), getRelDetailedDescription ) } }
StephanEwen/incubator-flink
flink-table/flink-table-planner/src/main/scala/org/apache/flink/table/planner/plan/nodes/physical/batch/BatchPhysicalOverAggregate.scala
Scala
apache-2.0
2,720
/* * Copyright (c) 2012-2019 Snowplow Analytics Ltd. All rights reserved. * * This program is licensed to you under the Apache License Version 2.0, * and you may not use this file except in compliance with the Apache License Version 2.0. * You may obtain a copy of the Apache License Version 2.0 at http://www.apache.org/licenses/LICENSE-2.0. * * Unless required by applicable law or agreed to in writing, * software distributed under the Apache License Version 2.0 is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the Apache License Version 2.0 for the specific language governing permissions and limitations there under. */ package com.snowplowanalytics.snowplow.enrich.common package enrichments package registry // Specs2 import org.specs2.Specification import org.specs2.scalaz.ValidationMatchers // Scalaz import scalaz._ import Scalaz._ /** * Tests CampaignAttributionEnrichment */ class CampaignAttributionEnrichmentSpec extends Specification with ValidationMatchers { def is = s2""" This is a specification to test the CampaignAttributionEnrichment extractMarketingFields should create an empty MarketingCampaign if no campaign fields are specified $e1 extractMarketingFields should create a MarketingCampaign using the standard Google-style settings $e2 extractMarketingFields should create a MarketingCampaign using the standard Omniture settings $e3 extractMarketingFields should create a MarketingCampaign using the correct order of precedence $e4 extractMarketingFields should create a MarketingCampaign with clickId and network fields $e5 """ val google_uri = Map( "utm_source" -> "GoogleSearch", "utm_medium" -> "cpc", "utm_term" -> "native american tarot deck", "utm_content" -> "39254295088", "utm_campaign" -> "uk-tarot--native-american" ) val omniture_uri = Map("cid" -> "uk-tarot--native-american") val heterogeneous_uri = Map( "utm_source" -> "GoogleSearch", "source" -> "bad_source", "utm_medium" -> "cpc", "legacy_term" -> "bad_term", "utm_term" -> "native american tarot deck", "legacy_campaign" -> "bad_campaign", "cid" -> "uk-tarot--native-american" ) val clickid_uri = Map( "utm_source" -> "GoogleSearch", "source" -> "bad_source", "utm_medium" -> "cpc", "legacy_term" -> "bad_term", "utm_term" -> "native american tarot deck", "legacy_campaign" -> "bad_campaign", "cid" -> "uk-tarot--native-american", "msclkid" -> "500" ) def e1 = { val config = CampaignAttributionEnrichment( List(), List(), List(), List(), List(), List() ) config.extractMarketingFields(google_uri) must beSuccessful( MarketingCampaign(None, None, None, None, None, None, None)) } def e2 = { val config = CampaignAttributionEnrichment( List("utm_medium"), List("utm_source"), List("utm_term"), List("utm_content"), List("utm_campaign"), List() ) config.extractMarketingFields(google_uri) must beSuccessful( MarketingCampaign(Some("cpc"), Some("GoogleSearch"), Some("native american tarot deck"), Some("39254295088"), Some("uk-tarot--native-american"), None, None)) } def e3 = { val config = CampaignAttributionEnrichment( List(), List(), List(), List(), List("cid"), List() ) config.extractMarketingFields(omniture_uri) must beSuccessful( MarketingCampaign(None, None, None, None, Some("uk-tarot--native-american"), None, None)) } def e4 = { val config = CampaignAttributionEnrichment( List("utm_medium", "medium"), List("utm_source", "source"), List("utm_term", "legacy_term"), List("utm_content"), List("utm_campaign", "cid", "legacy_campaign"), List() ) config.extractMarketingFields(heterogeneous_uri) must beSuccessful( MarketingCampaign(Some("cpc"), Some("GoogleSearch"), Some("native american tarot deck"), None, Some("uk-tarot--native-american"), None, None)) } def e5 = { val config = CampaignAttributionEnrichment( List("utm_medium", "medium"), List("utm_source", "source"), List("utm_term", "legacy_term"), List("utm_content"), List("utm_campaign", "cid", "legacy_campaign"), List( "gclid" -> "Google", "msclkid" -> "Microsoft", "dclid" -> "DoubleClick" ) ) config.extractMarketingFields(clickid_uri) must beSuccessful( MarketingCampaign(Some("cpc"), Some("GoogleSearch"), Some("native american tarot deck"), None, Some("uk-tarot--native-american"), Some("500"), Some("Microsoft"))) } }
RetentionGrid/snowplow
3-enrich/scala-common-enrich/src/test/scala/com.snowplowanalytics.snowplow.enrich.common/enrichments/registry/CampaignAttributionEnrichmentSpec.scala
Scala
apache-2.0
5,287
/* * Copyright 2013 Maurício Linhares * * Maurício Linhares licenses this file to you under the Apache License, * version 2.0 (the "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at: * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the * License for the specific language governing permissions and limitations * under the License. */ package com.github.mauricio.async.db.mysql.encoder.auth import java.nio.charset.Charset object AuthenticationMethod { final val Native = "mysql_native_password" final val Old = "mysql_old_password" final val Availables = Map( Native -> MySQLNativePasswordAuthentication, Old -> OldPasswordAuthentication ) } trait AuthenticationMethod { def generateAuthentication( charset : Charset, password : Option[String], seed : Array[Byte] ) : Array[Byte] }
outbrain/postgresql-async
mysql-async/src/main/scala/com/github/mauricio/async/db/mysql/encoder/auth/AuthenticationMethod.scala
Scala
apache-2.0
1,111
package org.jetbrains.sbt package project.structure import com.intellij.execution.process.{ProcessAdapter, ProcessEvent, ProcessOutputTypes} import com.intellij.openapi.util.Key /** * @author Pavel Fatin */ class ListenerAdapter(listener: (OutputType, String) => Unit) extends ProcessAdapter { override def onTextAvailable(event: ProcessEvent, outputType: Key[_]): Unit = { val textType = outputType match { case ProcessOutputTypes.STDOUT => Some(OutputType.StdOut) case ProcessOutputTypes.STDERR => Some(OutputType.StdErr) case ProcessOutputTypes.SYSTEM => Some(OutputType.MySystem) case other => Some(OutputType.Other(other)) } textType.foreach(t => listener(t, event.getText)) } }
JetBrains/intellij-scala
scala/scala-impl/src/org/jetbrains/sbt/project/structure/ListenerAdapter.scala
Scala
apache-2.0
748
package debop4s.data.orm.jpa.spring import java.util.Properties import javax.sql.DataSource import debop4s.data.orm.DataConst._ import org.hibernate.cfg.AvailableSettings /** * JPA 에서 PostgreSql 을 사용하기 위한 환경설정 * Created by debop on 2014. 1. 29.. */ abstract class AbstractJpaPostgreSqlConfiguration extends AbstractJpaConfiguration { override def dataSource: DataSource = { buildDataSource(DRIVER_CLASS_POSTGRESQL, s"jdbc:postgresql://localhost:5432/$getDatabaseName?charSet=UTF8", "root", "root") } override def jpaProperties: Properties = { val props = super.jpaProperties props.put(AvailableSettings.DIALECT, DIALECT_POSTGRESQL) props } }
debop/debop4s
debop4s-data-orm/src/main/scala/debop4s/data/orm/jpa/spring/AbstractJpaPostgreSqlConfiguration.scala
Scala
apache-2.0
718
package cz.kamenitxan.jakon.core.deploy.entity import java.time.LocalDateTime class Server( val id: Int, val url: String, val path: String, var lastDeployed: LocalDateTime ) { override def toString = s"Server(id=$id, url=$url, path=$path, lastDeployed=$lastDeployed)" }
kamenitxan/Jakon
modules/backend/src/main/scala/cz/kamenitxan/jakon/core/deploy/entity/Server.scala
Scala
bsd-3-clause
336
package uk.gov.digital.ho.proving.financialstatus.domain import java.time.{Clock, LocalDate, Period} object LeaveToRemainCalculator { private val ONE_YEAR = 1 private val SIX_MONTHS = 6 private def calcWrapUpPeriod(coursePeriod: Period, preSessional: Boolean) = { if (coursePeriod.getYears >= ONE_YEAR) Period.ofMonths(4) else if (coursePeriod.getMonths >= SIX_MONTHS) Period.ofMonths(2) else if (preSessional) Period.ofMonths(1) else Period.ofDays(7) } private def calculatePeriod(start: LocalDate, end: LocalDate, inclusive: Boolean = true) = { Period.between(start, end.plusDays(if (inclusive) 1 else 0)) } private def calculatePeriodInclusive(start: LocalDate, end: LocalDate) = calculatePeriod(start, end) private def calculatePeriodExclusive(start: LocalDate, end: LocalDate) = calculatePeriod(start, end, inclusive = false) def calculateLeaveToRemain(clock: Clock, courseStartDate: Option[LocalDate], courseEndDate: Option[LocalDate], originalCourseStartDate: Option[LocalDate], preSessional: Boolean): Option[LocalDate] = { for { start <- courseStartDate end <- courseEndDate } yield { val startDate = originalCourseStartDate match { case Some(originalStart) => originalStart case None => start } val considerationDate = LocalDate.now(clock) val endDate = if (end.isBefore(considerationDate)) { considerationDate } else { end } val coursePeriod = calculatePeriodInclusive(startDate, end) println(s"coursePeriod: $coursePeriod") val wrapUpPeriod = calcWrapUpPeriod(coursePeriod, preSessional) println(s"wrapUpPeriod: $wrapUpPeriod") endDate.plus(wrapUpPeriod) } } def calculateLeaveToRemain(clock: Clock, courseStartDate: LocalDate, courseEndDate: LocalDate, originalCourseStartDate: Option[LocalDate], preSessional: Boolean): LocalDate = { val startDate = originalCourseStartDate match { case Some(originalStart) => originalStart case None => courseStartDate } val considerationDate = LocalDate.now(clock) val endDate = if (courseEndDate.isBefore(considerationDate)) { considerationDate } else { courseEndDate } val coursePeriod = calculatePeriodInclusive(startDate, courseEndDate) val wrapUpPeriod = calcWrapUpPeriod(coursePeriod, preSessional) endDate.plus(wrapUpPeriod) } def calculateFixedLeaveToRemain(courseEndDate: LocalDate, period: Period): LocalDate = { courseEndDate.plus(period) } }
UKHomeOffice/pttg-fs-api
src/main/scala/uk/gov/digital/ho/proving/financialstatus/domain/LeaveToRemainCalculator.scala
Scala
mit
2,908
package colossus.protocols.memcache import org.scalatest._ import akka.util.ByteString import colossus.protocols.memcache.MemcacheCommand._ class MemcacheCommandSuite extends FlatSpec with Matchers { "MemcacheCommand" should "format a GET correctly" in { val experimental = Get(ByteString("test")) experimental.toString() should equal("get test\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("get test\\r\\n")) } it should "format a GETS correctly" in { val experimental = Gets(ByteString("test")) experimental.toString() should equal("gets test\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("gets test\\r\\n")) } it should "format a SET correctly" in { val experimental = Set(ByteString("key"), ByteString("value"), 30) // key, value, ttl experimental.toString() should equal("set key 0 30 5\\r\\nvalue\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("set key 0 30 5\\r\\nvalue\\r\\n")) } it should "format a CAS correctly" in { val experimental = Cas(ByteString("key"), ByteString("value"), 30, casUniqueMaybe = Some(1337)) // key, value, ttl, cas experimental.toString() should equal("cas key 0 30 5 1337\\r\\nvalue\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("cas key 0 30 5 1337\\r\\nvalue\\r\\n")) } it should "format an ADD correctly" in { val experimental = Add(ByteString("key"), ByteString("magic"), 30) experimental.toString() should equal("add key 0 30 5\\r\\nmagic\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("add key 0 30 5\\r\\nmagic\\r\\n")) } it should "format a REPLACE correctly" in { val experimental = Replace(ByteString("key"), ByteString("magic"), 30) experimental.toString() should equal("replace key 0 30 5\\r\\nmagic\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("replace key 0 30 5\\r\\nmagic\\r\\n")) } it should "format an APPEND correctly" in { val experimental = Append(ByteString("key"), ByteString("magic")) experimental.toString() should equal("append key 0 0 5\\r\\nmagic\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("append key 0 0 5\\r\\nmagic\\r\\n")) } it should "format a PREPEND correctly" in { val experimental = Prepend(ByteString("key"), ByteString("magic")) experimental.toString() should equal("prepend key 0 0 5\\r\\nmagic\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("prepend key 0 0 5\\r\\nmagic\\r\\n")) } it should "format DELETE correctly" in { val experimental = Delete(ByteString("key")) experimental.toString() should equal("delete key\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("delete key\\r\\n")) } it should "format INCR correctly" in { val experimental = Incr(ByteString("key"), 1L) experimental.toString() should equal("incr key 1\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("incr key 1\\r\\n")) } it should "format DECR correctly" in { val experimental = Decr(ByteString("key"), 1L) experimental.toString() should equal("decr key 1\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("decr key 1\\r\\n")) } it should "format TOUCH correctly" in { val experimental = Touch(ByteString("key"), 30) experimental.toString() should equal("touch key 30\\r\\n") experimental.memcacheCommandMsg() should equal(ByteString("touch key 30\\r\\n")) } }
tumblr/colossus
colossus-tests/src/test/scala/colossus/protocols/memcache/MemcacheCommandSpec.scala
Scala
apache-2.0
3,457
package sativum import org.joda.time.LocalDate import peapod.Task /* * This is a Task that is run on a daily basis or which can be tied to a date */ trait DatedTask extends Task[Any] { val partition: LocalDate override lazy val name: String = baseName+ "/" + partition.toString() override lazy val versionName = baseName override lazy val dir = p.path + "/" + baseName + "/" + storageRecursiveVersion() + "/" + partition.toString("yyyy/MM/dd") + "/" }
mindfulmachines/sativum
src/main/scala/sativum/DatedTask.scala
Scala
mit
476
package controllers import play.api.mvc._ import java.util.Date import model.EstateProvider import org.joda.time.DateTime class Management( estateProvider: EstateProvider, controllerComponents: ControllerComponents ) extends AbstractController(controllerComponents) { def healthcheck = Action { estateProvider().lastUpdated match { case Some(dt) if dt.isBefore(DateTime.now().minusMinutes(5)) => InternalServerError("Out of date data") case _ => Ok("") } } def manifest() = Action { val data = Map( "Build" -> BuildInfo.buildNumber, "Commit" -> BuildInfo.gitCommitId, "Date" -> new Date(BuildInfo.buildTime).toString, "Dependencies" -> BuildInfo.libraryDependencies.mkString(", ") ) Ok(data map { case (k, v) => s"$k: $v"} mkString "\\n") } }
guardian/status-app
app/controllers/Management.scala
Scala
apache-2.0
815
package main.scala.overlapping.timeSeriesOld.secondOrder.univariate.Procedures import breeze.linalg._ import main.scala.overlapping.timeSeries._ import main.scala.overlapping.timeSeriesOld.SecondOrderSignature /** * Created by Francois Belletti on 7/14/15. */ /* This calibrate one univariate AR model per columns. Returns an array of calibrated parameters (Coeffs, variance of noise). Check out Brockwell, Davis, Time Series: Theory and Methods, 1987 (p 234) TODO: shield procedure against the following edge cases, autoCov.size < 1, autoCov(0) = 0.0 */ object DurbinLevinson extends Serializable{ def apply(h: Int, autoCov: DenseVector[Double]): SecondOrderSignature ={ var prevPhiEst = DenseVector.zeros[Double](1) prevPhiEst(0) = autoCov(1) / autoCov(0) var prevVarEst: Double = autoCov(0) * (1.0 - prevPhiEst(0) * prevPhiEst(0)) var newVarEst: Double = 0.0 for(m <- 2 to h){ val newPhiEst = DenseVector.zeros[Double](m) val temp = reverse(autoCov(1 until m)) newPhiEst(m - 1) = (autoCov(m) - sum(prevPhiEst :* temp)) / prevVarEst newPhiEst(0 to (m - 2)) := prevPhiEst - (reverse(prevPhiEst) :* newPhiEst(m - 1)) newVarEst = prevVarEst * (1.0 - newPhiEst(m - 1) * newPhiEst(m - 1)) prevPhiEst = newPhiEst prevVarEst = newVarEst } SecondOrderSignature(prevPhiEst, prevVarEst) } }
bellettif/sparkGeoTS
sparkTS/src/main/scala/overlapping/timeSeriesOld/secondOrder/univariate/Procedures/DurbinLevinson.scala
Scala
bsd-3-clause
1,471
package org.jetbrains.plugins.scala.lang.completion import com.intellij.codeInsight.completion.{CompletionResultSet, InsertHandler} import com.intellij.codeInsight.lookup.{AutoCompletionPolicy, LookupElement, LookupElementPresentation, LookupElementRenderer} import com.intellij.openapi.application.ApplicationManager import com.intellij.psi.search.searches.ClassInheritorsSearch import com.intellij.psi.search.{GlobalSearchScope, LocalSearchScope} import com.intellij.psi.{PsiClass, PsiDocCommentOwner, PsiElement, PsiNamedElement} import com.intellij.util.Processor import org.jetbrains.plugins.scala.extensions.{toPsiClassExt, toPsiMemberExt, toPsiModifierListOwnerExt, toPsiNamedElementExt} import org.jetbrains.plugins.scala.lang.completion.handlers.ScalaConstructorInsertHandler import org.jetbrains.plugins.scala.lang.completion.lookups.ScalaLookupItem import org.jetbrains.plugins.scala.lang.formatting.settings.ScalaCodeStyleSettings import org.jetbrains.plugins.scala.lang.psi.api.base.types.ScSimpleTypeElement import org.jetbrains.plugins.scala.lang.psi.api.base.{ScConstructor, ScStableCodeReferenceElement} import org.jetbrains.plugins.scala.lang.psi.api.expr.ScNewTemplateDefinition import org.jetbrains.plugins.scala.lang.psi.api.toplevel.templates.{ScClassParents, ScExtendsBlock} import org.jetbrains.plugins.scala.lang.psi.api.toplevel.typedef.{ScObject, ScTrait} import org.jetbrains.plugins.scala.lang.psi.types._ import org.jetbrains.plugins.scala.lang.resolve.ResolveUtils import scala.collection.mutable import com.intellij.ide.IconDescriptorUpdaters /** * @author Alefas * @since 27.03.12 */ object ScalaAfterNewCompletionUtil { lazy val afterNewPattern = ScalaSmartCompletionContributor.superParentsPattern(classOf[ScStableCodeReferenceElement], classOf[ScSimpleTypeElement], classOf[ScConstructor], classOf[ScClassParents], classOf[ScExtendsBlock], classOf[ScNewTemplateDefinition]) def getLookupElementFromClass(expectedTypes: Array[ScType], clazz: PsiClass, renamesMap: mutable.HashMap[String, (String, PsiNamedElement)]): LookupElement = { val undefines: Seq[ScUndefinedType] = clazz.getTypeParameters.map(ptp => new ScUndefinedType(new ScTypeParameterType(ptp, ScSubstitutor.empty)) ) val predefinedType = if (clazz.getTypeParameters.length == 1) { ScParameterizedType(ScDesignatorType(clazz), undefines) } else ScDesignatorType(clazz) val noUndefType = if (clazz.getTypeParameters.length == 1) { ScParameterizedType(ScDesignatorType(clazz), clazz.getTypeParameters.map(ptp => new ScTypeParameterType(ptp, ScSubstitutor.empty) )) } else ScDesignatorType(clazz) val iterator = expectedTypes.iterator while (iterator.hasNext) { val typez = iterator.next() if (predefinedType.conforms(typez)) { val undef = Conformance.undefinedSubst(typez, predefinedType) undef.getSubstitutor match { case Some(subst) => val lookupElement = getLookupElementFromTypeAndClass(subst.subst(noUndefType), clazz, ScSubstitutor.empty, new AfterNewLookupElementRenderer(_, _, _), new ScalaConstructorInsertHandler, renamesMap) for (undefine <- undefines) { subst.subst(undefine) match { case ScUndefinedType(_) => lookupElement.typeParametersProblem = true case _ => } } return lookupElement case _ => } } } val lookupElement = getLookupElementFromTypeAndClass(noUndefType, clazz, ScSubstitutor.empty, new AfterNewLookupElementRenderer(_, _, _), new ScalaConstructorInsertHandler, renamesMap) if (undefines.length > 0) { lookupElement.typeParametersProblem = true } lookupElement } class AfterNewLookupElementRenderer(tp: ScType, psiClass: PsiClass, subst: ScSubstitutor) extends LookupElementRenderer[LookupElement] { def renderElement(ignore: LookupElement, presentation: LookupElementPresentation) { var isDeprecated = false psiClass match { case doc: PsiDocCommentOwner if doc.isDeprecated => isDeprecated = true case _ => } var tailText: String = "" val itemText: String = psiClass.name + (tp match { case ScParameterizedType(_, tps) => tps.map(tp => ScType.presentableText(subst.subst(tp))).mkString("[", ", ", "]") case _ => "" }) psiClass match { case clazz: PsiClass => { if (psiClass.isInterface || psiClass.isInstanceOf[ScTrait] || psiClass.hasModifierPropertyScala("abstract")) { tailText += " {...}" } val location: String = clazz.getPresentation.getLocationString presentation.setTailText(tailText + " " + location, true) } case _ => } presentation.setIcon(IconDescriptorUpdaters.getIcon(psiClass, 0)) presentation.setStrikeout(isDeprecated) presentation.setItemText(itemText) } } private def getLookupElementFromTypeAndClass(tp: ScType, psiClass: PsiClass, subst: ScSubstitutor, renderer: (ScType, PsiClass, ScSubstitutor) => LookupElementRenderer[LookupElement], insertHandler: InsertHandler[LookupElement], renamesMap: mutable.HashMap[String, (String, PsiNamedElement)]): ScalaLookupItem = { val name: String = psiClass.name val isRenamed = renamesMap.filter { case (aName, (renamed, aClazz)) => aName == name && aClazz == psiClass }.map(_._2._1).headOption val lookupElement: ScalaLookupItem = new ScalaLookupItem(psiClass, isRenamed.getOrElse(name)) { override def renderElement(presentation: LookupElementPresentation) { renderer(tp, psiClass, subst).renderElement(this, presentation) isRenamed match { case Some(name) => presentation.setItemText(name + " <= " + presentation.getItemText) case _ => } } } lookupElement.isRenamed = isRenamed if (ApplicationManager.getApplication.isUnitTestMode || psiClass.isInterface || psiClass.isInstanceOf[ScTrait] || psiClass.hasModifierPropertyScala("abstract")) lookupElement.setAutoCompletionPolicy(if (ApplicationManager.getApplication.isUnitTestMode) AutoCompletionPolicy.ALWAYS_AUTOCOMPLETE else AutoCompletionPolicy.NEVER_AUTOCOMPLETE) val qualName = psiClass.qualifiedName if (ScalaCodeStyleSettings.getInstance(psiClass.getProject).hasImportWithPrefix(qualName)) { lookupElement.prefixCompletion = true } lookupElement.setInsertHandler(new ScalaConstructorInsertHandler) tp match { case ScParameterizedType(_, tps) => lookupElement.typeParameters = tps case _ => } lookupElement } def convertTypeToLookupElement(tp: ScType, place: PsiElement, addedClasses: mutable.HashSet[String], renderer: (ScType, PsiClass, ScSubstitutor) => LookupElementRenderer[LookupElement], insertHandler: InsertHandler[LookupElement], renamesMap: mutable.HashMap[String, (String, PsiNamedElement)]): ScalaLookupItem = { ScType.extractClassType(tp, Some(place.getProject)) match { case Some((clazz: PsiClass, subst: ScSubstitutor)) => //filter base types (it's important for scala 2.9) clazz.qualifiedName match { case "scala.Boolean" | "scala.Int" | "scala.Long" | "scala.Byte" | "scala.Short" | "scala.AnyVal" | "scala.Char" | "scala.Unit" | "scala.Float" | "scala.Double" | "scala.Any" => return null case _ => } //todo: filter inner classes smarter (how? don't forget deep inner classes) if (clazz.containingClass != null && (!clazz.containingClass.isInstanceOf[ScObject] || clazz.hasModifierPropertyScala("static"))) return null if (!ResolveUtils.isAccessible(clazz, place, forCompletion = true)) return null if (addedClasses.contains(clazz.qualifiedName)) return null addedClasses += clazz.qualifiedName getLookupElementFromTypeAndClass(tp, clazz, subst, renderer, insertHandler, renamesMap) case _ => null } } def collectInheritorsForType(typez: ScType, place: PsiElement, addedClasses: mutable.HashSet[String], result: CompletionResultSet, renderer: (ScType, PsiClass, ScSubstitutor) => LookupElementRenderer[LookupElement], insertHandler: InsertHandler[LookupElement], renamesMap: mutable.HashMap[String, (String, PsiNamedElement)]) { ScType.extractClassType(typez, Some(place.getProject)) match { case Some((clazz, subst)) => //this change is important for Scala Worksheet/Script classes. Will not find inheritors, due to file copy. val searchScope = if (clazz.getUseScope.isInstanceOf[LocalSearchScope]) GlobalSearchScope.allScope(place.getProject) else clazz.getUseScope ClassInheritorsSearch.search(clazz, searchScope, true).forEach(new Processor[PsiClass] { def process(clazz: PsiClass): Boolean = { if (clazz.name == null || clazz.name == "") return true val undefines: Seq[ScUndefinedType] = clazz.getTypeParameters.map(ptp => new ScUndefinedType(new ScTypeParameterType(ptp, ScSubstitutor.empty)) ) val predefinedType = if (clazz.getTypeParameters.length >= 1) { ScParameterizedType(ScDesignatorType(clazz), undefines) } else ScDesignatorType(clazz) val noUndefType = if (clazz.getTypeParameters.length >= 1) { ScParameterizedType(ScDesignatorType(clazz), clazz.getTypeParameters.map(ptp => new ScTypeParameterType(ptp, ScSubstitutor.empty) )) } else ScDesignatorType(clazz) if (!predefinedType.conforms(typez)) return true val undef = Conformance.undefinedSubst(typez, predefinedType) undef.getSubstitutor match { case Some(undefSubst) => val lookupElement = convertTypeToLookupElement(undefSubst.subst(noUndefType), place, addedClasses, renderer, insertHandler, renamesMap) if (lookupElement != null) { for (undefine <- undefines) { undefSubst.subst(undefine) match { case ScUndefinedType(_) => lookupElement.typeParametersProblem = true case _ => } } result.addElement(lookupElement) } case _ => } true } }) case _ => } } }
consulo/consulo-scala
src/org/jetbrains/plugins/scala/lang/completion/ScalaAfterNewCompletionUtil.scala
Scala
apache-2.0
11,119
package com.sksamuel.elastic4s.akka import java.util.concurrent.TimeUnit import akka.http.scaladsl.model.HttpRequest import akka.http.scaladsl.settings.ConnectionPoolSettings import com.typesafe.config.{Config, ConfigFactory} import scala.collection.JavaConverters._ import scala.concurrent.duration._ import scala.util.Try object AkkaHttpClientSettings { private def defaultConfig: Config = ConfigFactory.load().getConfig("com.sksamuel.elastic4s.akka") lazy val default: AkkaHttpClientSettings = apply(defaultConfig) def apply(config: Config): AkkaHttpClientSettings = { val cfg = config.withFallback(defaultConfig) val hosts = cfg.getStringList("hosts").asScala.toVector val username = Try(cfg.getString("username")).map(Some(_)).getOrElse(None) val password = Try(cfg.getString("password")).map(Some(_)).getOrElse(None) val queueSize = cfg.getInt("queue-size") val https = cfg.getBoolean("https") val verifySslCertificate = Try(cfg.getBoolean("verify-ssl-certificate")).toOption.getOrElse(true) val blacklistMinDuration = Duration( cfg.getDuration("blacklist.min-duration", TimeUnit.MILLISECONDS), TimeUnit.MILLISECONDS ) val blacklistMaxDuration = Duration( cfg.getDuration("blacklist.max-duration", TimeUnit.MILLISECONDS), TimeUnit.MILLISECONDS ) val maxRetryTimeout = Duration( cfg.getDuration("max-retry-timeout", TimeUnit.MILLISECONDS), TimeUnit.MILLISECONDS ) val poolSettings = ConnectionPoolSettings( cfg.withFallback(ConfigFactory.load()) ) AkkaHttpClientSettings( https, hosts, username, password, queueSize, poolSettings, verifySslCertificate, blacklistMinDuration, blacklistMaxDuration, maxRetryTimeout ) } def apply(): AkkaHttpClientSettings = { default } def apply(hosts: Seq[String]): AkkaHttpClientSettings = { apply().copy(hosts = hosts.toVector) } } case class AkkaHttpClientSettings( https: Boolean, hosts: Vector[String], username: Option[String], password: Option[String], queueSize: Int, poolSettings: ConnectionPoolSettings, verifySSLCertificate : Boolean, blacklistMinDuration: FiniteDuration = AkkaHttpClientSettings.default.blacklistMinDuration, blacklistMaxDuration: FiniteDuration = AkkaHttpClientSettings.default.blacklistMaxDuration, maxRetryTimeout: FiniteDuration = AkkaHttpClientSettings.default.maxRetryTimeout, requestCallback: HttpRequest => HttpRequest = identity ) { def hasCredentialsDefined: Boolean = username.isDefined && password.isDefined }
sksamuel/elastic4s
elastic4s-client-akka/src/main/scala/com/sksamuel/elastic4s/akka/AkkaHttpClientSettings.scala
Scala
apache-2.0
2,632
import scala.reflect.runtime.universe._ import scala.tools.reflect.ToolBox object Test extends dotty.runtime.LegacyApp { val tb = runtimeMirror(getClass.getClassLoader).mkToolBox() val tree1 = reify(new collection.immutable.HashMap[String, String]) val tree2 = reify(new collection.mutable.HashMap[String, String]) println(showRaw(tb.typecheck(tree1.tree), printTypes = true)) println(showRaw(tb.typecheck(tree2.tree), printTypes = true)) }
yusuke2255/dotty
tests/disabled/macro/run/showraw_tree_types_typed.scala
Scala
bsd-3-clause
452
package com.github.vitalsoftware.scalaredox.receiver import com.github.vitalsoftware.scalaredox.receiver.ReceiveController._ import com.github.vitalsoftware.util.JsonNaming.KebabCase import play.api.libs.json._ import play.api.mvc._ import play.api.Logger import play.api.libs.json.JsonConfiguration.Aux import scala.concurrent.Future trait ReceiveController extends BaseController { protected def verificationToken: String val logger: Logger /** * Validate an initial challenge from Redox to authenticate our server as a * destination, or validate a normal Redox event request and delegate to the * verifiedAction * * Redox documentation says: * > Verification POSTs will include a challenge value and your destination’s * > verification token (that you specified when you set up the destination * > record) in the body of the POST. Non-verification POSTs from Redox will * > always include the verification token in the header of the message. * * @see http://developer.redoxengine.com/getting-started/create-a-destination/ */ protected def validatedAction(verifiedAction: RedoxRequest => Future[Result]): Action[JsValue] = Action(parse.json).async({ request: Request[JsValue] => RedoxRequest(request).token match { case Some(token) if token == verificationToken => verifiedAction(RedoxRequest(request)) case Some(token) => // The verification token is incorrect logger.error(s"Redox webhook had an incorrect token from ${RedoxRequest(request)}") Future.successful(Forbidden(s"Validation failed.")) case None => challengeResponse(RedoxRequest(request)) } }) private def challengeResponse(request: RedoxRequest): Future[Result] = request.underlying.body .validate[Challenge] .fold( (errors: Seq[(JsPath, Seq[JsonValidationError])]) => { // The challenge has an invalid format logger.error(s"Redox webhook challenge had errors (${JsError.toJson(errors)}) from $request") logger.debug(s"Failed challenge body was: ${request.underlying.body.toString()}") Future.successful(Forbidden(s"Challenge failed.")) }, (challenge: Challenge) => { if (challenge.verificationToken == verificationToken) { // The challenge is successful: we must respond with the challenge token (only) logger.info(s"Redox endpoint initialized via challenge from $request") Future.successful(Ok(challenge.challenge)) } else { // The challenge has an invalid validation token logger.error(s"Redox challenge had invalid token from $request") Future.successful(Forbidden(s"Challenge failed.")) } } ) } object ReceiveController { case class Challenge(verificationToken: String, challenge: String) implicit val config: Aux[Json.MacroOptions] = JsonConfiguration(KebabCase) implicit val challengeFormat: Format[Challenge] = Json.format[Challenge] }
vital-software/scala-redox
src/main/scala/com/github/vitalsoftware/scalaredox/receiver/ReceiveController.scala
Scala
mit
3,061
package models case class Configuration( version: String, styleName: String, scriptName: String) { } object Configuration { def apply(conf: play.api.Configuration) = { new Configuration( version = conf.getString("application.version").getOrElse(""), styleName = conf.getString("application.files.style").getOrElse(""), scriptName = conf.getString("application.files.script").getOrElse("") ) } }
bobeal/geebooks
app/models/Configuration.scala
Scala
agpl-3.0
440
package utils object StringOpz { implicit final class StrOpz(private val s: String) extends AnyVal { def inlined = s.stripMargin.replace("\\n", "") } }
falconepl/daarvin-protos
daarvin-proto/src/main/scala/utils/StringOpz.scala
Scala
gpl-2.0
162
// Sample adapters: class logged extends EntryPoint.Adapter: def wrapper(wrapped: EntryPoint.Wrapper): LoggedWrapper = LoggedWrapper(wrapped) class LoggedWrapper(val wrapped: EntryPoint.Wrapper) extends Wrapper: def adapt[A, R](op: A => R)(args: A): R = val argsString: String = args match case args: Array[_] => args.mkString(", ") case args: Seq[_] => args.mkString(", ") case args: Unit => "()" case args => args.toString val result = op(args) println(s"[log] ${finalWrapped.entryPointName}($argsString) -> $result") result end LoggedWrapper end logged class split extends EntryPoint.Adapter: def wrapper(wrapped: EntryPoint.Wrapper): SplitWrapper = SplitWrapper(wrapped) class SplitWrapper(val wrapped: EntryPoint.Wrapper) extends Wrapper: def adapt[R](op: Array[String] => R)(args: String): R = op(args.split(" ")) end split class join extends EntryPoint.Adapter: def wrapper(wrapped: EntryPoint.Wrapper): JoinWrapper = JoinWrapper(wrapped) class JoinWrapper(val wrapped: EntryPoint.Wrapper) extends Wrapper: def adapt[R](op: String => R)(args: Array[String]): R = op(args.mkString(" ")) end join
dotty-staging/dotty
tests/run/decorators/sample-adapters.scala
Scala
apache-2.0
1,193
package pl.newicom.dddd.scheduling import akka.actor.ActorPath import akka.persistence.Recover import org.json4s.JsonAST.JString import org.json4s.{CustomSerializer, FullTypeHints} import pl.newicom.dddd.actor.PassivationConfig import pl.newicom.dddd.aggregate._ import pl.newicom.dddd.eventhandling.EventPublisher import pl.newicom.dddd.messaging.event.EventMessage import pl.newicom.dddd.scheduling.Scheduler.SchedulerState import pl.newicom.dddd.serialization.JsonSerializationHints object Scheduler { // // Serialization hints // object ActorPathSerializer extends CustomSerializer[ActorPath](format => ( { case JString(s) => ActorPath.fromString(s) }, { case x: ActorPath => JString(x.toSerializationFormat) } )) val serializationHints = new JsonSerializationHints { def typeHints = FullTypeHints(List( classOf[EventScheduled], classOf[EventMessage] )) def serializers = List(ActorPathSerializer) } // // State // case class SchedulerState() extends AggregateState { override def apply = { case e: EventScheduled => this } } } class Scheduler(val pc: PassivationConfig, businessUnit: String) extends AggregateRoot[SchedulerState] { this: EventPublisher => override def persistenceId = s"${schedulingOffice.name}-$businessUnit" // Skip recovery override def preStart() = self ! Recover(toSequenceNr = 0L) // Disable automated recovery on restart override def preRestart(reason: Throwable, message: Option[Any]) = () override val factory: AggregateRootFactory = { case EventScheduled(_, _, _, _, _) => SchedulerState() } override def handleCommand: Receive = { case ScheduleEvent(_, target, deadline, msg) => raise( EventScheduled( businessUnit, target, deadline.withSecondOfMinute(0).withMillisOfSecond(0), deadline.getMillis, msg) ) } }
ahjohannessen/akka-ddd
akka-ddd-scheduling/src/main/scala/pl/newicom/dddd/scheduling/Scheduler.scala
Scala
mit
1,923
/* * Copyright 2017 TabMo http://tabmo.io * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package io.tabmo.avro import java.io.Closeable import scala.util.{ Failure, Success, Try } object TWR { def twr[A <: Closeable, B](resource: A)(doWork: A => B): Try[B] = try { Success(doWork(resource)) } catch { case e: Exception => Failure(e) } finally { try { if (resource != null) { resource.close() } } catch { case e: Exception => //log.error(e, e.getMessage) // should be logged } } def twrs[A <: Closeable, B](resources: A*)(doWork: Seq[A] => B): Try[B] = try { Success(doWork(resources.toSeq)) } catch { case e: Exception => Failure(e) } finally { resources.foreach( resource => try { if (resource != null) { resource.close() } } catch { case e: Exception => //log.error(e, e.getMessage) // should be logged } ) } }
tabmo/parquet-avro-shapeless
src/main/scala/io/tabmo/avro/TWR.scala
Scala
apache-2.0
1,545
package longRunning import ilc.examples.MapIntIntBenchData import ilc.examples.MapSuccBaseGenerated import ilc.examples.ReplacementChangeBenchmark /** * Benchmark generated derivative. */ object MapSuccBaseBenchmark extends ReplacementChangeBenchmark(new MapIntIntBenchData(MapSuccBaseGenerated))
inc-lc/ilc-scala
clients/src/test/scala/longRunning/MapSuccBaseBenchmark.scala
Scala
mit
303
/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.spark.scheduler.cluster import java.util.concurrent.TimeUnit import java.util.concurrent.atomic.AtomicInteger import javax.annotation.concurrent.GuardedBy import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet} import scala.concurrent.Future import scala.concurrent.duration.Duration import org.apache.spark.{ExecutorAllocationClient, SparkEnv, SparkException, TaskState} import org.apache.spark.internal.Logging import org.apache.spark.rpc._ import org.apache.spark.scheduler._ import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._ import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.ENDPOINT_NAME import org.apache.spark.util.{RpcUtils, SerializableBuffer, ThreadUtils, Utils} /** * A scheduler backend that waits for coarse-grained executors to connect. * This backend holds onto each executor for the duration of the Spark job rather than relinquishing * executors whenever a task is done and asking the scheduler to launch a new executor for * each new task. Executors may be launched in a variety of ways, such as Mesos tasks for the * coarse-grained Mesos mode or standalone processes for Spark's standalone deploy mode * (spark.deploy.*). */ private[spark] class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: RpcEnv) extends ExecutorAllocationClient with SchedulerBackend with Logging { // Use an atomic variable to track total number of cores in the cluster for simplicity and speed protected val totalCoreCount = new AtomicInteger(0) // Total number of executors that are currently registered protected val totalRegisteredExecutors = new AtomicInteger(0) protected val conf = scheduler.sc.conf private val maxRpcMessageSize = RpcUtils.maxMessageSizeBytes(conf) private val defaultAskTimeout = RpcUtils.askRpcTimeout(conf) // Submit tasks only after (registered resources / total expected resources) // is equal to at least this value, that is double between 0 and 1. private val _minRegisteredRatio = math.min(1, conf.getDouble("spark.scheduler.minRegisteredResourcesRatio", 0)) // Submit tasks after maxRegisteredWaitingTime milliseconds // if minRegisteredRatio has not yet been reached private val maxRegisteredWaitingTimeMs = conf.getTimeAsMs("spark.scheduler.maxRegisteredResourcesWaitingTime", "30s") private val createTime = System.currentTimeMillis() // Accessing `executorDataMap` in `DriverEndpoint.receive/receiveAndReply` doesn't need any // protection. But accessing `executorDataMap` out of `DriverEndpoint.receive/receiveAndReply` // must be protected by `CoarseGrainedSchedulerBackend.this`. Besides, `executorDataMap` should // only be modified in `DriverEndpoint.receive/receiveAndReply` with protection by // `CoarseGrainedSchedulerBackend.this`. private val executorDataMap = new HashMap[String, ExecutorData] // Number of executors requested by the cluster manager, [[ExecutorAllocationManager]] @GuardedBy("CoarseGrainedSchedulerBackend.this") private var requestedTotalExecutors = 0 // Number of executors requested from the cluster manager that have not registered yet @GuardedBy("CoarseGrainedSchedulerBackend.this") private var numPendingExecutors = 0 private val listenerBus = scheduler.sc.listenerBus // Executors we have requested the cluster manager to kill that have not died yet; maps // the executor ID to whether it was explicitly killed by the driver (and thus shouldn't // be considered an app-related failure). @GuardedBy("CoarseGrainedSchedulerBackend.this") private val executorsPendingToRemove = new HashMap[String, Boolean] // A map to store hostname with its possible task number running on it @GuardedBy("CoarseGrainedSchedulerBackend.this") protected var hostToLocalTaskCount: Map[String, Int] = Map.empty // The number of pending tasks which is locality required @GuardedBy("CoarseGrainedSchedulerBackend.this") protected var localityAwareTasks = 0 // The num of current max ExecutorId used to re-register appMaster @volatile protected var currentExecutorIdCounter = 0 class DriverEndpoint(override val rpcEnv: RpcEnv, sparkProperties: Seq[(String, String)]) extends ThreadSafeRpcEndpoint with Logging { // Executors that have been lost, but for which we don't yet know the real exit reason. protected val executorsPendingLossReason = new HashSet[String] protected val addressToExecutorId = new HashMap[RpcAddress, String] private val reviveThread = ThreadUtils.newDaemonSingleThreadScheduledExecutor("driver-revive-thread") override def onStart() { // Periodically revive offers to allow delay scheduling to work val reviveIntervalMs = conf.getTimeAsMs("spark.scheduler.revive.interval", "1s") reviveThread.scheduleAtFixedRate(new Runnable { override def run(): Unit = Utils.tryLogNonFatalError { Option(self).foreach(_.send(ReviveOffers)) } }, 0, reviveIntervalMs, TimeUnit.MILLISECONDS) } override def receive: PartialFunction[Any, Unit] = { case StatusUpdate(executorId, taskId, state, data) => scheduler.statusUpdate(taskId, state, data.value) if (TaskState.isFinished(state)) { executorDataMap.get(executorId) match { case Some(executorInfo) => executorInfo.freeCores += scheduler.CPUS_PER_TASK makeOffers(executorId) case None => // Ignoring the update since we don't know about the executor. logWarning(s"Ignored task status update ($taskId state $state) " + s"from unknown executor with ID $executorId") } } case ReviveOffers => makeOffers() case KillTask(taskId, executorId, interruptThread, reason) => executorDataMap.get(executorId) match { case Some(executorInfo) => executorInfo.executorEndpoint.send( KillTask(taskId, executorId, interruptThread, reason)) case None => // Ignoring the task kill since the executor is not registered. logWarning(s"Attempted to kill task $taskId for unknown executor $executorId.") } case KillExecutorsOnHost(host) => scheduler.getExecutorsAliveOnHost(host).foreach { exec => killExecutors(exec.toSeq, replace = true, force = true) } } override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = { case RegisterExecutor(executorId, executorRef, hostname, cores, logUrls) => if (executorDataMap.contains(executorId)) { executorRef.send(RegisterExecutorFailed("Duplicate executor ID: " + executorId)) context.reply(true) } else if (scheduler.nodeBlacklist != null && scheduler.nodeBlacklist.contains(hostname)) { // If the cluster manager gives us an executor on a blacklisted node (because it // already started allocating those resources before we informed it of our blacklist, // or if it ignored our blacklist), then we reject that executor immediately. logInfo(s"Rejecting $executorId as it has been blacklisted.") executorRef.send(RegisterExecutorFailed(s"Executor is blacklisted: $executorId")) context.reply(true) } else { // If the executor's rpc env is not listening for incoming connections, `hostPort` // will be null, and the client connection should be used to contact the executor. val executorAddress = if (executorRef.address != null) { executorRef.address } else { context.senderAddress } logInfo(s"Registered executor $executorRef ($executorAddress) with ID $executorId") addressToExecutorId(executorAddress) = executorId totalCoreCount.addAndGet(cores) totalRegisteredExecutors.addAndGet(1) val data = new ExecutorData(executorRef, executorRef.address, hostname, cores, cores, logUrls) // This must be synchronized because variables mutated // in this block are read when requesting executors CoarseGrainedSchedulerBackend.this.synchronized { executorDataMap.put(executorId, data) if (currentExecutorIdCounter < executorId.toInt) { currentExecutorIdCounter = executorId.toInt } if (numPendingExecutors > 0) { numPendingExecutors -= 1 logDebug(s"Decremented number of pending executors ($numPendingExecutors left)") } } executorRef.send(RegisteredExecutor) // Note: some tests expect the reply to come after we put the executor in the map context.reply(true) listenerBus.post( SparkListenerExecutorAdded(System.currentTimeMillis(), executorId, data)) makeOffers() } case StopDriver => context.reply(true) stop() case StopExecutors => logInfo("Asking each executor to shut down") for ((_, executorData) <- executorDataMap) { executorData.executorEndpoint.send(StopExecutor) } context.reply(true) case RemoveExecutor(executorId, reason) => // We will remove the executor's state and cannot restore it. However, the connection // between the driver and the executor may be still alive so that the executor won't exit // automatically, so try to tell the executor to stop itself. See SPARK-13519. executorDataMap.get(executorId).foreach(_.executorEndpoint.send(StopExecutor)) removeExecutor(executorId, reason) context.reply(true) case RetrieveSparkAppConfig => val reply = SparkAppConfig(sparkProperties, SparkEnv.get.securityManager.getIOEncryptionKey()) context.reply(reply) } // Make fake resource offers on all executors private def makeOffers() { // Make sure no executor is killed while some task is launching on it val taskDescs = CoarseGrainedSchedulerBackend.this.synchronized { // Filter out executors under killing val activeExecutors = executorDataMap.filterKeys(executorIsAlive) val workOffers = activeExecutors.map { case (id, executorData) => new WorkerOffer(id, executorData.executorHost, executorData.freeCores) }.toIndexedSeq scheduler.resourceOffers(workOffers) } if (!taskDescs.isEmpty) { launchTasks(taskDescs) } } override def onDisconnected(remoteAddress: RpcAddress): Unit = { addressToExecutorId .get(remoteAddress) .foreach(removeExecutor(_, SlaveLost("Remote RPC client disassociated. Likely due to " + "containers exceeding thresholds, or network issues. Check driver logs for WARN " + "messages."))) } // Make fake resource offers on just one executor private def makeOffers(executorId: String) { // Make sure no executor is killed while some task is launching on it val taskDescs = CoarseGrainedSchedulerBackend.this.synchronized { // Filter out executors under killing if (executorIsAlive(executorId)) { val executorData = executorDataMap(executorId) val workOffers = IndexedSeq( new WorkerOffer(executorId, executorData.executorHost, executorData.freeCores)) scheduler.resourceOffers(workOffers) } else { Seq.empty } } if (!taskDescs.isEmpty) { launchTasks(taskDescs) } } private def executorIsAlive(executorId: String): Boolean = synchronized { !executorsPendingToRemove.contains(executorId) && !executorsPendingLossReason.contains(executorId) } // Launch tasks returned by a set of resource offers private def launchTasks(tasks: Seq[Seq[TaskDescription]]) { for (task <- tasks.flatten) { val serializedTask = TaskDescription.encode(task) if (serializedTask.limit >= maxRpcMessageSize) { scheduler.taskIdToTaskSetManager.get(task.taskId).foreach { taskSetMgr => try { var msg = "Serialized task %s:%d was %d bytes, which exceeds max allowed: " + "spark.rpc.message.maxSize (%d bytes). Consider increasing " + "spark.rpc.message.maxSize or using broadcast variables for large values." msg = msg.format(task.taskId, task.index, serializedTask.limit, maxRpcMessageSize) taskSetMgr.abort(msg) } catch { case e: Exception => logError("Exception in error callback", e) } } } else { val executorData = executorDataMap(task.executorId) executorData.freeCores -= scheduler.CPUS_PER_TASK logDebug(s"Launching task ${task.taskId} on executor id: ${task.executorId} hostname: " + s"${executorData.executorHost}.") executorData.executorEndpoint.send(LaunchTask(new SerializableBuffer(serializedTask))) } } } // Remove a disconnected slave from the cluster private def removeExecutor(executorId: String, reason: ExecutorLossReason): Unit = { logDebug(s"Asked to remove executor $executorId with reason $reason") executorDataMap.get(executorId) match { case Some(executorInfo) => // This must be synchronized because variables mutated // in this block are read when requesting executors val killed = CoarseGrainedSchedulerBackend.this.synchronized { addressToExecutorId -= executorInfo.executorAddress executorDataMap -= executorId executorsPendingLossReason -= executorId executorsPendingToRemove.remove(executorId).getOrElse(false) } totalCoreCount.addAndGet(-executorInfo.totalCores) totalRegisteredExecutors.addAndGet(-1) scheduler.executorLost(executorId, if (killed) ExecutorKilled else reason) listenerBus.post( SparkListenerExecutorRemoved(System.currentTimeMillis(), executorId, reason.toString)) case None => // SPARK-15262: If an executor is still alive even after the scheduler has removed // its metadata, we may receive a heartbeat from that executor and tell its block // manager to reregister itself. If that happens, the block manager master will know // about the executor, but the scheduler will not. Therefore, we should remove the // executor from the block manager when we hit this case. scheduler.sc.env.blockManager.master.removeExecutorAsync(executorId) logInfo(s"Asked to remove non-existent executor $executorId") } } /** * Stop making resource offers for the given executor. The executor is marked as lost with * the loss reason still pending. * * @return Whether executor should be disabled */ protected def disableExecutor(executorId: String): Boolean = { val shouldDisable = CoarseGrainedSchedulerBackend.this.synchronized { if (executorIsAlive(executorId)) { executorsPendingLossReason += executorId true } else { // Returns true for explicitly killed executors, we also need to get pending loss reasons; // For others return false. executorsPendingToRemove.contains(executorId) } } if (shouldDisable) { logInfo(s"Disabling executor $executorId.") scheduler.executorLost(executorId, LossReasonPending) } shouldDisable } override def onStop() { reviveThread.shutdownNow() } } var driverEndpoint: RpcEndpointRef = null protected def minRegisteredRatio: Double = _minRegisteredRatio override def start() { val properties = new ArrayBuffer[(String, String)] for ((key, value) <- scheduler.sc.conf.getAll) { if (key.startsWith("spark.")) { properties += ((key, value)) } } // TODO (prashant) send conf instead of properties driverEndpoint = createDriverEndpointRef(properties) } protected def createDriverEndpointRef( properties: ArrayBuffer[(String, String)]): RpcEndpointRef = { rpcEnv.setupEndpoint(ENDPOINT_NAME, createDriverEndpoint(properties)) } protected def createDriverEndpoint(properties: Seq[(String, String)]): DriverEndpoint = { new DriverEndpoint(rpcEnv, properties) } def stopExecutors() { try { if (driverEndpoint != null) { logInfo("Shutting down all executors") driverEndpoint.askSync[Boolean](StopExecutors) } } catch { case e: Exception => throw new SparkException("Error asking standalone scheduler to shut down executors", e) } } override def stop() { stopExecutors() try { if (driverEndpoint != null) { driverEndpoint.askSync[Boolean](StopDriver) } } catch { case e: Exception => throw new SparkException("Error stopping standalone scheduler's driver endpoint", e) } } /** * Reset the state of CoarseGrainedSchedulerBackend to the initial state. Currently it will only * be called in the yarn-client mode when AM re-registers after a failure. * */ protected def reset(): Unit = { val executors = synchronized { requestedTotalExecutors = 0 numPendingExecutors = 0 executorsPendingToRemove.clear() Set() ++ executorDataMap.keys } // Remove all the lingering executors that should be removed but not yet. The reason might be // because (1) disconnected event is not yet received; (2) executors die silently. executors.foreach { eid => removeExecutor(eid, SlaveLost("Stale executor after cluster manager re-registered.")) } } override def reviveOffers() { driverEndpoint.send(ReviveOffers) } override def killTask( taskId: Long, executorId: String, interruptThread: Boolean, reason: String) { driverEndpoint.send(KillTask(taskId, executorId, interruptThread, reason)) } override def defaultParallelism(): Int = { conf.getInt("spark.default.parallelism", math.max(totalCoreCount.get(), 2)) } /** * Called by subclasses when notified of a lost worker. It just fires the message and returns * at once. */ protected def removeExecutor(executorId: String, reason: ExecutorLossReason): Unit = { // Only log the failure since we don't care about the result. driverEndpoint.ask[Boolean](RemoveExecutor(executorId, reason)).onFailure { case t => logError(t.getMessage, t) }(ThreadUtils.sameThread) } def sufficientResourcesRegistered(): Boolean = true override def isReady(): Boolean = { if (sufficientResourcesRegistered) { logInfo("SchedulerBackend is ready for scheduling beginning after " + s"reached minRegisteredResourcesRatio: $minRegisteredRatio") return true } if ((System.currentTimeMillis() - createTime) >= maxRegisteredWaitingTimeMs) { logInfo("SchedulerBackend is ready for scheduling beginning after waiting " + s"maxRegisteredResourcesWaitingTime: $maxRegisteredWaitingTimeMs(ms)") return true } false } /** * Return the number of executors currently registered with this backend. */ private def numExistingExecutors: Int = executorDataMap.size override def getExecutorIds(): Seq[String] = { executorDataMap.keySet.toSeq } /** * Request an additional number of executors from the cluster manager. * @return whether the request is acknowledged. */ final override def requestExecutors(numAdditionalExecutors: Int): Boolean = { if (numAdditionalExecutors < 0) { throw new IllegalArgumentException( "Attempted to request a negative number of additional executor(s) " + s"$numAdditionalExecutors from the cluster manager. Please specify a positive number!") } logInfo(s"Requesting $numAdditionalExecutors additional executor(s) from the cluster manager") val response = synchronized { requestedTotalExecutors += numAdditionalExecutors numPendingExecutors += numAdditionalExecutors logDebug(s"Number of pending executors is now $numPendingExecutors") if (requestedTotalExecutors != (numExistingExecutors + numPendingExecutors - executorsPendingToRemove.size)) { logDebug( s"""requestExecutors($numAdditionalExecutors): Executor request doesn't match: |requestedTotalExecutors = $requestedTotalExecutors |numExistingExecutors = $numExistingExecutors |numPendingExecutors = $numPendingExecutors |executorsPendingToRemove = ${executorsPendingToRemove.size}""".stripMargin) } // Account for executors pending to be added or removed doRequestTotalExecutors(requestedTotalExecutors) } defaultAskTimeout.awaitResult(response) } /** * Update the cluster manager on our scheduling needs. Three bits of information are included * to help it make decisions. * @param numExecutors The total number of executors we'd like to have. The cluster manager * shouldn't kill any running executor to reach this number, but, * if all existing executors were to die, this is the number of executors * we'd want to be allocated. * @param localityAwareTasks The number of tasks in all active stages that have a locality * preferences. This includes running, pending, and completed tasks. * @param hostToLocalTaskCount A map of hosts to the number of tasks from all active stages * that would like to like to run on that host. * This includes running, pending, and completed tasks. * @return whether the request is acknowledged by the cluster manager. */ final override def requestTotalExecutors( numExecutors: Int, localityAwareTasks: Int, hostToLocalTaskCount: Map[String, Int] ): Boolean = { if (numExecutors < 0) { throw new IllegalArgumentException( "Attempted to request a negative number of executor(s) " + s"$numExecutors from the cluster manager. Please specify a positive number!") } val response = synchronized { this.requestedTotalExecutors = numExecutors this.localityAwareTasks = localityAwareTasks this.hostToLocalTaskCount = hostToLocalTaskCount numPendingExecutors = math.max(numExecutors - numExistingExecutors + executorsPendingToRemove.size, 0) doRequestTotalExecutors(numExecutors) } defaultAskTimeout.awaitResult(response) } /** * Request executors from the cluster manager by specifying the total number desired, * including existing pending and running executors. * * The semantics here guarantee that we do not over-allocate executors for this application, * since a later request overrides the value of any prior request. The alternative interface * of requesting a delta of executors risks double counting new executors when there are * insufficient resources to satisfy the first request. We make the assumption here that the * cluster manager will eventually fulfill all requests when resources free up. * * @return a future whose evaluation indicates whether the request is acknowledged. */ protected def doRequestTotalExecutors(requestedTotal: Int): Future[Boolean] = Future.successful(false) /** * Request that the cluster manager kill the specified executors. * * When asking the executor to be replaced, the executor loss is considered a failure, and * killed tasks that are running on the executor will count towards the failure limits. If no * replacement is being requested, then the tasks will not count towards the limit. * * @param executorIds identifiers of executors to kill * @param replace whether to replace the killed executors with new ones, default false * @param force whether to force kill busy executors, default false * @return the ids of the executors acknowledged by the cluster manager to be removed. */ final override def killExecutors( executorIds: Seq[String], replace: Boolean, force: Boolean): Seq[String] = { logInfo(s"Requesting to kill executor(s) ${executorIds.mkString(", ")}") val response = synchronized { val (knownExecutors, unknownExecutors) = executorIds.partition(executorDataMap.contains) unknownExecutors.foreach { id => logWarning(s"Executor to kill $id does not exist!") } // If an executor is already pending to be removed, do not kill it again (SPARK-9795) // If this executor is busy, do not kill it unless we are told to force kill it (SPARK-9552) val executorsToKill = knownExecutors .filter { id => !executorsPendingToRemove.contains(id) } .filter { id => force || !scheduler.isExecutorBusy(id) } executorsToKill.foreach { id => executorsPendingToRemove(id) = !replace } logInfo(s"Actual list of executor(s) to be killed is ${executorsToKill.mkString(", ")}") // If we do not wish to replace the executors we kill, sync the target number of executors // with the cluster manager to avoid allocating new ones. When computing the new target, // take into account executors that are pending to be added or removed. val adjustTotalExecutors = if (!replace) { requestedTotalExecutors = math.max(requestedTotalExecutors - executorsToKill.size, 0) if (requestedTotalExecutors != (numExistingExecutors + numPendingExecutors - executorsPendingToRemove.size)) { logDebug( s"""killExecutors($executorIds, $replace, $force): Executor counts do not match: |requestedTotalExecutors = $requestedTotalExecutors |numExistingExecutors = $numExistingExecutors |numPendingExecutors = $numPendingExecutors |executorsPendingToRemove = ${executorsPendingToRemove.size}""".stripMargin) } doRequestTotalExecutors(requestedTotalExecutors) } else { numPendingExecutors += knownExecutors.size Future.successful(true) } val killExecutors: Boolean => Future[Boolean] = if (!executorsToKill.isEmpty) { _ => doKillExecutors(executorsToKill) } else { _ => Future.successful(false) } val killResponse = adjustTotalExecutors.flatMap(killExecutors)(ThreadUtils.sameThread) killResponse.flatMap(killSuccessful => Future.successful (if (killSuccessful) executorsToKill else Seq.empty[String]) )(ThreadUtils.sameThread) } defaultAskTimeout.awaitResult(response) } /** * Kill the given list of executors through the cluster manager. * @return whether the kill request is acknowledged. */ protected def doKillExecutors(executorIds: Seq[String]): Future[Boolean] = Future.successful(false) /** * Request that the cluster manager kill all executors on a given host. * @return whether the kill request is acknowledged. */ final override def killExecutorsOnHost(host: String): Boolean = { logInfo(s"Requesting to kill any and all executors on host ${host}") // A potential race exists if a new executor attempts to register on a host // that is on the blacklist and is no no longer valid. To avoid this race, // all executor registration and killing happens in the event loop. This way, either // an executor will fail to register, or will be killed when all executors on a host // are killed. // Kill all the executors on this host in an event loop to ensure serialization. driverEndpoint.send(KillExecutorsOnHost(host)) true } } private[spark] object CoarseGrainedSchedulerBackend { val ENDPOINT_NAME = "CoarseGrainedScheduler" }
saturday-shi/spark
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
Scala
apache-2.0
28,972
/** * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package kafka.server import java.util.Properties import junit.framework.Assert._ import kafka.api.{ApiVersion, KAFKA_082} import kafka.message._ import kafka.utils.{CoreUtils, TestUtils} import org.apache.kafka.common.config.ConfigException import org.apache.kafka.common.protocol.SecurityProtocol import org.junit.{Assert, Test} import org.scalatest.Assertions.intercept class KafkaConfigTest { @Test def testLogRetentionTimeHoursProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.LogRetentionTimeHoursProp, "1") val cfg = KafkaConfig.fromProps(props) assertEquals(60L * 60L * 1000L, cfg.logRetentionTimeMillis) } @Test def testLogRetentionTimeMinutesProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.LogRetentionTimeMinutesProp, "30") val cfg = KafkaConfig.fromProps(props) assertEquals(30 * 60L * 1000L, cfg.logRetentionTimeMillis) } @Test def testLogRetentionTimeMsProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.LogRetentionTimeMillisProp, "1800000") val cfg = KafkaConfig.fromProps(props) assertEquals(30 * 60L * 1000L, cfg.logRetentionTimeMillis) } @Test def testLogRetentionTimeNoConfigProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) val cfg = KafkaConfig.fromProps(props) assertEquals(24 * 7 * 60L * 60L * 1000L, cfg.logRetentionTimeMillis) } @Test def testLogRetentionTimeBothMinutesAndHoursProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.LogRetentionTimeMinutesProp, "30") props.put(KafkaConfig.LogRetentionTimeHoursProp, "1") val cfg = KafkaConfig.fromProps(props) assertEquals( 30 * 60L * 1000L, cfg.logRetentionTimeMillis) } @Test def testLogRetentionTimeBothMinutesAndMsProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.LogRetentionTimeMillisProp, "1800000") props.put(KafkaConfig.LogRetentionTimeMinutesProp, "10") val cfg = KafkaConfig.fromProps(props) assertEquals( 30 * 60L * 1000L, cfg.logRetentionTimeMillis) } @Test def testLogRetentionUnlimited() { val props1 = TestUtils.createBrokerConfig(0,TestUtils.MockZkConnect, port = 8181) val props2 = TestUtils.createBrokerConfig(0,TestUtils.MockZkConnect, port = 8181) val props3 = TestUtils.createBrokerConfig(0,TestUtils.MockZkConnect, port = 8181) val props4 = TestUtils.createBrokerConfig(0,TestUtils.MockZkConnect, port = 8181) val props5 = TestUtils.createBrokerConfig(0,TestUtils.MockZkConnect, port = 8181) props1.put("log.retention.ms", "-1") props2.put("log.retention.minutes", "-1") props3.put("log.retention.hours", "-1") val cfg1 = KafkaConfig.fromProps(props1) val cfg2 = KafkaConfig.fromProps(props2) val cfg3 = KafkaConfig.fromProps(props3) assertEquals("Should be -1", -1, cfg1.logRetentionTimeMillis) assertEquals("Should be -1", -1, cfg2.logRetentionTimeMillis) assertEquals("Should be -1", -1, cfg3.logRetentionTimeMillis) props4.put("log.retention.ms", "-1") props4.put("log.retention.minutes", "30") val cfg4 = KafkaConfig.fromProps(props4) assertEquals("Should be -1", -1, cfg4.logRetentionTimeMillis) props5.put("log.retention.ms", "0") intercept[IllegalArgumentException] { val cfg5 = KafkaConfig.fromProps(props5) } } @Test def testLogRetentionValid { val props1 = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) val props2 = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) val props3 = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props1.put("log.retention.ms", "0") props2.put("log.retention.minutes", "0") props3.put("log.retention.hours", "0") intercept[IllegalArgumentException] { val cfg1 = KafkaConfig.fromProps(props1) } intercept[IllegalArgumentException] { val cfg2 = KafkaConfig.fromProps(props2) } intercept[IllegalArgumentException] { val cfg3 = KafkaConfig.fromProps(props3) } } @Test def testAdvertiseDefaults() { val port = "9999" val hostName = "fake-host" val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect) props.remove(KafkaConfig.ListenersProp) props.put(KafkaConfig.HostNameProp, hostName) props.put(KafkaConfig.PortProp, port) val serverConfig = KafkaConfig.fromProps(props) val endpoints = serverConfig.advertisedListeners val endpoint = endpoints.get(SecurityProtocol.PLAINTEXT).get assertEquals(endpoint.host, hostName) assertEquals(endpoint.port, port.toInt) } @Test def testAdvertiseConfigured() { val advertisedHostName = "routable-host" val advertisedPort = "1234" val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect) props.put(KafkaConfig.AdvertisedHostNameProp, advertisedHostName) props.put(KafkaConfig.AdvertisedPortProp, advertisedPort) val serverConfig = KafkaConfig.fromProps(props) val endpoints = serverConfig.advertisedListeners val endpoint = endpoints.get(SecurityProtocol.PLAINTEXT).get assertEquals(endpoint.host, advertisedHostName) assertEquals(endpoint.port, advertisedPort.toInt) } @Test def testAdvertisePortDefault() { val advertisedHostName = "routable-host" val port = "9999" val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect) props.put(KafkaConfig.AdvertisedHostNameProp, advertisedHostName) props.put(KafkaConfig.PortProp, port) val serverConfig = KafkaConfig.fromProps(props) val endpoints = serverConfig.advertisedListeners val endpoint = endpoints.get(SecurityProtocol.PLAINTEXT).get assertEquals(endpoint.host, advertisedHostName) assertEquals(endpoint.port, port.toInt) } @Test def testAdvertiseHostNameDefault() { val hostName = "routable-host" val advertisedPort = "9999" val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect) props.put(KafkaConfig.HostNameProp, hostName) props.put(KafkaConfig.AdvertisedPortProp, advertisedPort) val serverConfig = KafkaConfig.fromProps(props) val endpoints = serverConfig.advertisedListeners val endpoint = endpoints.get(SecurityProtocol.PLAINTEXT).get assertEquals(endpoint.host, hostName) assertEquals(endpoint.port, advertisedPort.toInt) } @Test def testDuplicateListeners() { val props = new Properties() props.put(KafkaConfig.BrokerIdProp, "1") props.put(KafkaConfig.ZkConnectProp, "localhost:2181") // listeners with duplicate port props.put(KafkaConfig.ListenersProp, "PLAINTEXT://localhost:9091,TRACE://localhost:9091") assert(!isValidKafkaConfig(props)) // listeners with duplicate protocol props.put(KafkaConfig.ListenersProp, "PLAINTEXT://localhost:9091,PLAINTEXT://localhost:9092") assert(!isValidKafkaConfig(props)) // advertised listeners with duplicate port props.put(KafkaConfig.AdvertisedListenersProp, "PLAINTEXT://localhost:9091,TRACE://localhost:9091") assert(!isValidKafkaConfig(props)) } @Test def testBadListenerProtocol() { val props = new Properties() props.put(KafkaConfig.BrokerIdProp, "1") props.put(KafkaConfig.ZkConnectProp, "localhost:2181") props.put(KafkaConfig.ListenersProp, "BAD://localhost:9091") assert(!isValidKafkaConfig(props)) } @Test def testListenerDefaults() { val props = new Properties() props.put(KafkaConfig.BrokerIdProp, "1") props.put(KafkaConfig.ZkConnectProp, "localhost:2181") // configuration with host and port, but no listeners props.put(KafkaConfig.HostNameProp, "myhost") props.put(KafkaConfig.PortProp, "1111") val conf = KafkaConfig.fromProps(props) assertEquals(CoreUtils.listenerListToEndPoints("PLAINTEXT://myhost:1111"), conf.listeners) // configuration with null host props.remove(KafkaConfig.HostNameProp) val conf2 = KafkaConfig.fromProps(props) assertEquals(CoreUtils.listenerListToEndPoints("PLAINTEXT://:1111"), conf2.listeners) assertEquals(CoreUtils.listenerListToEndPoints("PLAINTEXT://:1111"), conf2.advertisedListeners) assertEquals(null, conf2.listeners(SecurityProtocol.PLAINTEXT).host) // configuration with advertised host and port, and no advertised listeners props.put(KafkaConfig.AdvertisedHostNameProp, "otherhost") props.put(KafkaConfig.AdvertisedPortProp, "2222") val conf3 = KafkaConfig.fromProps(props) assertEquals(conf3.advertisedListeners, CoreUtils.listenerListToEndPoints("PLAINTEXT://otherhost:2222")) } @Test def testVersionConfiguration() { val props = new Properties() props.put(KafkaConfig.BrokerIdProp, "1") props.put(KafkaConfig.ZkConnectProp, "localhost:2181") val conf = KafkaConfig.fromProps(props) assertEquals(ApiVersion.latestVersion, conf.interBrokerProtocolVersion) props.put(KafkaConfig.InterBrokerProtocolVersionProp,"0.8.2.0") val conf2 = KafkaConfig.fromProps(props) assertEquals(KAFKA_082, conf2.interBrokerProtocolVersion) // check that 0.8.2.0 is the same as 0.8.2.1 props.put(KafkaConfig.InterBrokerProtocolVersionProp,"0.8.2.1") val conf3 = KafkaConfig.fromProps(props) assertEquals(KAFKA_082, conf3.interBrokerProtocolVersion) //check that latest is newer than 0.8.2 assert(ApiVersion.latestVersion.onOrAfter(conf3.interBrokerProtocolVersion)) } private def isValidKafkaConfig(props: Properties): Boolean = { try { KafkaConfig.fromProps(props) true } catch { case e: IllegalArgumentException => false } } @Test def testUncleanLeaderElectionDefault() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) val serverConfig = KafkaConfig.fromProps(props) assertEquals(serverConfig.uncleanLeaderElectionEnable, true) } @Test def testUncleanElectionDisabled() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.UncleanLeaderElectionEnableProp, String.valueOf(false)) val serverConfig = KafkaConfig.fromProps(props) assertEquals(serverConfig.uncleanLeaderElectionEnable, false) } @Test def testUncleanElectionEnabled() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.UncleanLeaderElectionEnableProp, String.valueOf(true)) val serverConfig = KafkaConfig.fromProps(props) assertEquals(serverConfig.uncleanLeaderElectionEnable, true) } @Test def testUncleanElectionInvalid() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.UncleanLeaderElectionEnableProp, "invalid") intercept[ConfigException] { KafkaConfig.fromProps(props) } } @Test def testLogRollTimeMsProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.LogRollTimeMillisProp, "1800000") val cfg = KafkaConfig.fromProps(props) assertEquals(30 * 60L * 1000L, cfg.logRollTimeMillis) } @Test def testLogRollTimeBothMsAndHoursProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.LogRollTimeMillisProp, "1800000") props.put(KafkaConfig.LogRollTimeHoursProp, "1") val cfg = KafkaConfig.fromProps(props) assertEquals( 30 * 60L * 1000L, cfg.logRollTimeMillis) } @Test def testLogRollTimeNoConfigProvided() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) val cfg = KafkaConfig.fromProps(props) assertEquals(24 * 7 * 60L * 60L * 1000L, cfg.logRollTimeMillis ) } @Test def testDefaultCompressionType() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) val serverConfig = KafkaConfig.fromProps(props) assertEquals(serverConfig.compressionType, "producer") } @Test def testValidCompressionType() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put("compression.type", "gzip") val serverConfig = KafkaConfig.fromProps(props) assertEquals(serverConfig.compressionType, "gzip") } @Test def testInvalidCompressionType() { val props = TestUtils.createBrokerConfig(0, TestUtils.MockZkConnect, port = 8181) props.put(KafkaConfig.CompressionTypeProp, "abc") intercept[IllegalArgumentException] { KafkaConfig.fromProps(props) } } @Test def testFromPropsInvalid() { def getBaseProperties(): Properties = { val validRequiredProperties = new Properties() validRequiredProperties.put(KafkaConfig.ZkConnectProp, "127.0.0.1:2181") validRequiredProperties } // to ensure a basis is valid - bootstraps all needed validation KafkaConfig.fromProps(getBaseProperties()) KafkaConfig.configNames().foreach(name => { name match { case KafkaConfig.ZkConnectProp => // ignore string case KafkaConfig.ZkSessionTimeoutMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ZkConnectionTimeoutMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ZkSyncTimeMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ZkEnableSecureAclsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_boolean") case KafkaConfig.BrokerIdProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.NumNetworkThreadsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.NumIoThreadsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.BackgroundThreadsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.QueuedMaxRequestsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.RequestTimeoutMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.AuthorizerClassNameProp => //ignore string case KafkaConfig.PortProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.HostNameProp => // ignore string case KafkaConfig.AdvertisedHostNameProp => //ignore string case KafkaConfig.AdvertisedPortProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.SocketSendBufferBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.SocketReceiveBufferBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.MaxConnectionsPerIpOverridesProp => assertPropertyInvalid(getBaseProperties(), name, "127.0.0.1:not_a_number") case KafkaConfig.ConnectionsMaxIdleMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.NumPartitionsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.LogDirsProp => // ignore string case KafkaConfig.LogDirProp => // ignore string case KafkaConfig.LogSegmentBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", Message.MinHeaderSize - 1) case KafkaConfig.LogRollTimeMillisProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.LogRollTimeHoursProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.LogRetentionTimeMillisProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.LogRetentionTimeMinutesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.LogRetentionTimeHoursProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.LogRetentionBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.LogCleanupIntervalMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.LogCleanupPolicyProp => assertPropertyInvalid(getBaseProperties(), name, "unknown_policy", "0") case KafkaConfig.LogCleanerIoMaxBytesPerSecondProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.LogCleanerDedupeBufferSizeProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "1024") case KafkaConfig.LogCleanerDedupeBufferLoadFactorProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.LogCleanerEnableProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_boolean") case KafkaConfig.LogCleanerDeleteRetentionMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.LogCleanerMinCleanRatioProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.LogIndexSizeMaxBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "3") case KafkaConfig.LogFlushIntervalMessagesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.LogFlushSchedulerIntervalMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.LogFlushIntervalMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.NumRecoveryThreadsPerDataDirProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.AutoCreateTopicsEnableProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_boolean", "0") case KafkaConfig.MinInSyncReplicasProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.ControllerSocketTimeoutMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.DefaultReplicationFactorProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ReplicaLagTimeMaxMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ReplicaSocketTimeoutMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "-2") case KafkaConfig.ReplicaSocketReceiveBufferBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ReplicaFetchMaxBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ReplicaFetchWaitMaxMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ReplicaFetchMinBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.NumReplicaFetchersProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ReplicaHighWatermarkCheckpointIntervalMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.FetchPurgatoryPurgeIntervalRequestsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ProducerPurgatoryPurgeIntervalRequestsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.AutoLeaderRebalanceEnableProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_boolean", "0") case KafkaConfig.LeaderImbalancePerBrokerPercentageProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.LeaderImbalanceCheckIntervalSecondsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.UncleanLeaderElectionEnableProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_boolean", "0") case KafkaConfig.ControlledShutdownMaxRetriesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ControlledShutdownRetryBackoffMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.ControlledShutdownEnableProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_boolean", "0") case KafkaConfig.GroupMinSessionTimeoutMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.GroupMaxSessionTimeoutMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.OffsetMetadataMaxSizeProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number") case KafkaConfig.OffsetsLoadBufferSizeProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.OffsetsTopicReplicationFactorProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.OffsetsTopicPartitionsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.OffsetsTopicSegmentBytesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.OffsetsTopicCompressionCodecProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "-1") case KafkaConfig.OffsetsRetentionMinutesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.OffsetsRetentionCheckIntervalMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.OffsetCommitTimeoutMsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.OffsetCommitRequiredAcksProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "-2") case KafkaConfig.ProducerQuotaBytesPerSecondDefaultProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.ConsumerQuotaBytesPerSecondDefaultProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.NumQuotaSamplesProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.QuotaWindowSizeSecondsProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "0") case KafkaConfig.DeleteTopicEnableProp => assertPropertyInvalid(getBaseProperties(), name, "not_a_boolean", "0") case KafkaConfig.MetricNumSamplesProp => assertPropertyInvalid(getBaseProperties, name, "not_a_number", "-1", "0") case KafkaConfig.MetricSampleWindowMsProp => assertPropertyInvalid(getBaseProperties, name, "not_a_number", "-1", "0") case KafkaConfig.MetricReporterClassesProp => // ignore string //SSL Configs case KafkaConfig.PrincipalBuilderClassProp => case KafkaConfig.SslProtocolProp => // ignore string case KafkaConfig.SslProviderProp => // ignore string case KafkaConfig.SslEnabledProtocolsProp => case KafkaConfig.SslKeystoreTypeProp => // ignore string case KafkaConfig.SslKeystoreLocationProp => // ignore string case KafkaConfig.SslKeystorePasswordProp => // ignore string case KafkaConfig.SslKeyPasswordProp => // ignore string case KafkaConfig.SslTruststoreTypeProp => // ignore string case KafkaConfig.SslTruststorePasswordProp => // ignore string case KafkaConfig.SslTruststoreLocationProp => // ignore string case KafkaConfig.SslKeyManagerAlgorithmProp => case KafkaConfig.SslTrustManagerAlgorithmProp => case KafkaConfig.SslClientAuthProp => // ignore string case KafkaConfig.SslEndpointIdentificationAlgorithmProp => // ignore string case KafkaConfig.SslCipherSuitesProp => // ignore string //Sasl Configs case KafkaConfig.SaslKerberosServiceNameProp => // ignore string case KafkaConfig.SaslKerberosKinitCmdProp => case KafkaConfig.SaslKerberosTicketRenewWindowFactorProp => case KafkaConfig.SaslKerberosTicketRenewJitterProp => case KafkaConfig.SaslKerberosMinTimeBeforeReloginProp => case KafkaConfig.AuthToLocalProp => // ignore string case nonNegativeIntProperty => assertPropertyInvalid(getBaseProperties(), name, "not_a_number", "-1") } }) } @Test def testSpecificProperties(): Unit = { val defaults = new Properties() defaults.put(KafkaConfig.ZkConnectProp, "127.0.0.1:2181") // For ZkConnectionTimeoutMs defaults.put(KafkaConfig.ZkSessionTimeoutMsProp, "1234") defaults.put(KafkaConfig.MaxReservedBrokerIdProp, "1") defaults.put(KafkaConfig.BrokerIdProp, "1") defaults.put(KafkaConfig.HostNameProp, "127.0.0.1") defaults.put(KafkaConfig.PortProp, "1122") defaults.put(KafkaConfig.MaxConnectionsPerIpOverridesProp, "127.0.0.1:2, 127.0.0.2:3") defaults.put(KafkaConfig.LogDirProp, "/tmp1,/tmp2") defaults.put(KafkaConfig.LogRollTimeHoursProp, "12") defaults.put(KafkaConfig.LogRollTimeJitterHoursProp, "11") defaults.put(KafkaConfig.LogRetentionTimeHoursProp, "10") //For LogFlushIntervalMsProp defaults.put(KafkaConfig.LogFlushSchedulerIntervalMsProp, "123") defaults.put(KafkaConfig.OffsetsTopicCompressionCodecProp, SnappyCompressionCodec.codec.toString) val config = KafkaConfig.fromProps(defaults) Assert.assertEquals("127.0.0.1:2181", config.zkConnect) Assert.assertEquals(1234, config.zkConnectionTimeoutMs) Assert.assertEquals(1, config.maxReservedBrokerId) Assert.assertEquals(1, config.brokerId) Assert.assertEquals("127.0.0.1", config.hostName) Assert.assertEquals(1122, config.advertisedPort) Assert.assertEquals("127.0.0.1", config.advertisedHostName) Assert.assertEquals(Map("127.0.0.1" -> 2, "127.0.0.2" -> 3), config.maxConnectionsPerIpOverrides) Assert.assertEquals(List("/tmp1", "/tmp2"), config.logDirs) Assert.assertEquals(12 * 60L * 1000L * 60, config.logRollTimeMillis) Assert.assertEquals(11 * 60L * 1000L * 60, config.logRollTimeJitterMillis) Assert.assertEquals(10 * 60L * 1000L * 60, config.logRetentionTimeMillis) Assert.assertEquals(123L, config.logFlushIntervalMs) Assert.assertEquals(SnappyCompressionCodec, config.offsetsTopicCompressionCodec) } private def assertPropertyInvalid(validRequiredProps: => Properties, name: String, values: Any*) { values.foreach((value) => { val props = validRequiredProps props.setProperty(name, value.toString) intercept[Exception] { KafkaConfig.fromProps(props) } }) } }
bluebreezecf/kafka
core/src/test/scala/unit/kafka/server/KafkaConfigTest.scala
Scala
apache-2.0
27,979
package com.eevolution.context.dictionary.infrastructure.repository import com.eevolution.context.dictionary.domain.model.PinStance import com.eevolution.context.dictionary.infrastructure.db.DbContext._ /** * Copyright (C) 2003-2017, e-Evolution Consultants S.A. , http://www.e-evolution.com * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. * Email: emeris.hernandez@e-evolution.com, http://www.e-evolution.com , http://github.com/EmerisScala * Created by emeris.hernandez@e-evolution.com , www.e-evolution.com on 26/10/17. */ /** * Pin Stance Mapping */ trait PinStanceMapping { val queryPinStance = quote { querySchema[PinStance]("AD_PinStance", _.pinStanceId-> "AD_PinStance_ID", _.tenantId-> "AD_Client_ID", _.organizationId-> "AD_Org_ID", _.processId-> "AD_Process_ID", _.recordId-> "Record_ID", _.isProcessing-> "IsProcessing", _.created-> "Created", _.userId-> "AD_User_ID", _.updated-> "Updated", _.result-> "Result", _.errorMsg-> "ErrorMsg", _.createdBy-> "CreatedBy", _.updatedBy-> "UpdatedBy", _.isActive-> "IsActive", _.name-> "Name", _.reportType-> "ReportType", _.printFormatId-> "AD_PrintFormat_ID", _.uuid-> "UUID") } }
adempiere/ADReactiveSystem
dictionary-impl/src/main/scala/com/eevolution/context/dictionary/infrastructure/repository/PinStanceMapping.scala
Scala
gpl-3.0
1,869
package com.recursivity.bowler.stub import com.recursivity.bowler.Component /** * Created by IntelliJ IDEA. * User: wfaler * Date: Nov 10, 2010 * Time: 10:55:16 PM * To change this template use File | Settings | File Templates. */ class ListModelComponent extends Component(None){ }
rossabaker/Handlebar
src/test/scala/com/recursivity/bowler/stub/ListModelComponent.scala
Scala
bsd-3-clause
294
/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.spark.util.collection /** * An append-only, non-threadsafe, array-backed vector that is optimized for primitive types. */ private[spark] class PrimitiveVector[@specialized(Long, Int, Double) V: ClassManifest](initialSize: Int = 64) { private var _numElements = 0 private var _array: Array[V] = _ // NB: This must be separate from the declaration, otherwise the specialized parent class // will get its own array with the same initial size. _array = new Array[V](initialSize) def apply(index: Int): V = { require(index < _numElements) _array(index) } def +=(value: V) { if (_numElements == _array.length) { resize(_array.length * 2) } _array(_numElements) = value _numElements += 1 } def capacity: Int = _array.length def length: Int = _numElements def size: Int = _numElements /** Gets the underlying array backing this vector. */ def array: Array[V] = _array /** Trims this vector so that the capacity is equal to the size. */ def trim(): PrimitiveVector[V] = resize(size) /** Resizes the array, dropping elements if the total length decreases. */ def resize(newLength: Int): PrimitiveVector[V] = { val newArray = new Array[V](newLength) _array.copyToArray(newArray) _array = newArray if (newLength < _numElements) { _numElements = newLength } this } }
windeye/spark
core/src/main/scala/org/apache/spark/util/collection/PrimitiveVector.scala
Scala
apache-2.0
2,185
package util import scala.concurrent._ import ExecutionContext.Implicits.global import org.apache.commons.mail.{DefaultAuthenticator, HtmlEmail} import org.slf4j.LoggerFactory import app.Context import service.{AccountService, RepositoryService, IssuesService, SystemSettingsService} import servlet.Database import SystemSettingsService.Smtp import _root_.util.ControlUtil.defining trait Notifier extends RepositoryService with AccountService with IssuesService { def toNotify(r: RepositoryService.RepositoryInfo, issueId: Int, content: String) (msg: String => String)(implicit context: Context): Unit protected def recipients(issue: model.Issue)(notify: String => Unit)(implicit context: Context) = ( // individual repository's owner issue.userName :: // collaborators getCollaborators(issue.userName, issue.repositoryName) ::: // participants issue.openedUserName :: getComments(issue.userName, issue.repositoryName, issue.issueId).map(_.commentedUserName) ) .distinct .withFilter ( _ != context.loginAccount.get.userName ) // the operation in person is excluded .withFilter ( _ == issue.assignedUserName) // assigined user only. .foreach ( getAccountByUserName(_) filterNot (_.isGroupAccount) foreach (x => notify(x.mailAddress)) ) } object Notifier { // TODO We want to be able to switch to mock. def apply(): Notifier = new SystemSettingsService {}.loadSystemSettings match { case settings if settings.notification => new Mailer(settings.smtp.get) case _ => new MockMailer } def msgIssue(url: String) = (content: String) => s""" |${content}<br/> |--<br/> |<a href="${url}">View it on GitBucket</a> """.stripMargin def msgPullRequest(url: String) = (content: String) => s""" |${content}<hr/> |View, comment on, or merge it at:<br/> |<a href="${url}">${url}</a> """.stripMargin def msgComment(url: String) = (content: String) => s""" |${content}<br/> |--<br/> |<a href="${url}">View it on GitBucket</a> """.stripMargin def msgStatus(url: String) = (content: String) => s""" |${content} <a href="${url}">#${url split('/') last}</a> """.stripMargin } class Mailer(private val smtp: Smtp) extends Notifier { private val logger = LoggerFactory.getLogger(classOf[Mailer]) def toNotify(r: RepositoryService.RepositoryInfo, issueId: Int, content: String) (msg: String => String)(implicit context: Context) = { val database = Database(context.request.getServletContext) val f = future { // TODO Can we use the Database Session in other than Transaction Filter? database withSession { getIssue(r.owner, r.name, issueId.toString) foreach { issue => defining( s"[${r.name}] ${issue.title} (#${issueId})" -> msg(view.Markdown.toHtml(content, r, false, true))) { case (subject, msg) => recipients(issue) { to => val email = new HtmlEmail email.setHostName(smtp.host) email.setSmtpPort(smtp.port.get) smtp.user.foreach { user => email.setAuthenticator(new DefaultAuthenticator(user, smtp.password.getOrElse(""))) } smtp.ssl.foreach { ssl => email.setSSLOnConnect(ssl) } smtp.fromAddress .map (_ -> smtp.fromName.orNull) .orElse (Some("notifications@gitbucket.com" -> context.loginAccount.get.userName)) .foreach { case (address, name) => email.setFrom(address, name) } email.setCharset("UTF-8") email.setSubject(subject) email.setHtmlMsg(msg) email.addTo(to).send } } } } "Notifications Successful." } f onSuccess { case s => logger.debug(s) } f onFailure { case t => logger.error("Notifications Failed.", t) } } } class MockMailer extends Notifier { def toNotify(r: RepositoryService.RepositoryInfo, issueId: Int, content: String) (msg: String => String)(implicit context: Context): Unit = {} }
toshi-saito/gitbucket
src/main/scala/util/Notifier.scala
Scala
apache-2.0
4,336
/* APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "{}" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright {2017} {Jamie Xia, Calvin Liu, Aditya Prasad} Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ import scala.language.postfixOps; object test extends RapBattle{ object DJKHALED extends Rapper{ name = "DJ Khaled"; } object SNOOPDOG extends Rapper{ name = "Snoop Dog"; } def main(args: Array[String]): Unit = { SNOOPDOG YO; SPIT VERSE "Gimme a number for collatz fam"; I GET PAID; FO SHIZZLE; SPIT FIRE; EVERYBODY SQUAT 2; PEACE OUT; STRAIGHT OUTTA COMPTON; HALF A MIL; I GOT 2 PROBLEMS; STRAIGHT OUTTA COMPTON; I HAVE 3 STACKS; ANOTHER ONE; BOTTLES N MODELS; BOTTLES N MODELS; DJKHALED YO; ANOTHER ONE; MY NIZZLE; SPIT VERSE "It took this many turns to get to 1: " DJKHALED YO; SPIT FIRE; } }
xiazilla/Rap-Concert
src/test.scala
Scala
apache-2.0
1,916
package com.sksamuel.avro4s.schemas import com.sksamuel.avro4s.typeutils.{CaseClassShape, DatatypeShape, SealedTraitShape} import com.sksamuel.avro4s.{SchemaFor} import magnolia1.{CaseClass, AutoDerivation, SealedTrait, TypeInfo} import org.apache.avro.{Schema, SchemaBuilder} import scala.deriving.Mirror trait MagnoliaDerivedSchemas extends AutoDerivation[SchemaFor] : def join[T](ctx: CaseClass[SchemaFor, T]): SchemaFor[T] = DatatypeShape.of(ctx) match { case CaseClassShape.Record => Records.schema(ctx) case CaseClassShape.ValueType => ??? } override def split[T](ctx: SealedTrait[SchemaFor, T]): SchemaFor[T] = DatatypeShape.of[T](ctx) match { case SealedTraitShape.TypeUnion => TypeUnions.schema(ctx) case SealedTraitShape.Enum => SchemaFor[T](SealedTraits.schema(ctx)) }
sksamuel/avro4s
avro4s-core/src/main/scala/com/sksamuel/avro4s/schemas/magnolia.scala
Scala
apache-2.0
828
package org.jetbrains.plugins.scala package extensions import com.intellij.psi.PsiElement /** * Pavel Fatin */ object ElementText { def unapply(e: PsiElement): Some[String] = Some(e.getText) }
triggerNZ/intellij-scala
src/org/jetbrains/plugins/scala/extensions/ElementText.scala
Scala
apache-2.0
199
package com.scalableminds.webknossos.datastore.helpers import com.scalableminds.util.tools.Fox import com.typesafe.scalalogging.LazyLogging import net.liftweb.common.Full import java.io.File import java.nio.file.{Files, Path} import scala.annotation.tailrec import scala.concurrent.ExecutionContext trait DataSetDeleter extends LazyLogging with DirectoryConstants { def dataBaseDir: Path def deleteOnDisk(organizationName: String, dataSetName: String, isInConversion: Boolean = false, reason: Option[String] = None)(implicit ec: ExecutionContext): Fox[Unit] = { @tailrec def deleteWithRetry(sourcePath: Path, targetPath: Path, retryCount: Int = 0): Fox[Unit] = try { val deduplicatedTargetPath = if (retryCount == 0) targetPath else targetPath.resolveSibling(targetPath.getFileName + s"($retryCount)") val path = Files.move(sourcePath, deduplicatedTargetPath) if (path == null) { throw new Exception("Deleting dataset failed") } logger.info(s"Successfully moved dataset from $sourcePath to $targetPath...") Fox.successful(()) } catch { case _: java.nio.file.FileAlreadyExistsException => deleteWithRetry(sourcePath, targetPath, retryCount + 1) case e: Exception => Fox.failure(s"Deleting dataset failed: ${e.toString}", Full(e)) } val dataSourcePath = if (isInConversion) dataBaseDir.resolve(organizationName).resolve(forConversionDir).resolve(dataSetName) else dataBaseDir.resolve(organizationName).resolve(dataSetName) val trashPath: Path = dataBaseDir.resolve(organizationName).resolve(trashDir) val targetPath = trashPath.resolve(dataSetName) new File(trashPath.toString).mkdirs() logger.info( s"Deleting dataset by moving it from $dataSourcePath to $targetPath${if (reason.isDefined) s" because ${reason.getOrElse("")}" else "..."}") deleteWithRetry(dataSourcePath, targetPath) } }
scalableminds/webknossos
webknossos-datastore/app/com/scalableminds/webknossos/datastore/helpers/DataSetDeleter.scala
Scala
agpl-3.0
2,044
package com.twitter.finagle.thrift.exp.partitioning import com.twitter.conversions.DurationOps._ import com.twitter.delivery.thriftscala.DeliveryService._ import com.twitter.delivery.thriftscala._ import com.twitter.finagle.Addr import com.twitter.finagle.addr.WeightedAddress import com.twitter.finagle.loadbalancer.BalancerRegistry import com.twitter.finagle.param.CommonParams import com.twitter.finagle.partitioning.ConsistentHashPartitioningService.NoPartitioningKeys import com.twitter.finagle.partitioning.PartitionNodeManager.NoPartitionException import com.twitter.finagle.partitioning.zk.ZkMetadata import com.twitter.finagle.stats.InMemoryStatsReceiver import com.twitter.finagle.thrift.exp.partitioning.PartitioningStrategy._ import com.twitter.finagle.thrift.exp.partitioning.ThriftPartitioningService.PartitioningStrategyException import com.twitter.finagle.thrift.{ThriftRichClient, ThriftRichServer} import com.twitter.finagle.{Address, ListeningServer, Name, Stack} import com.twitter.scrooge.ThriftStructIface import com.twitter.util.{Activity, Await, Awaitable, Duration, Future, Return, Throw, Var} import java.net.{InetAddress, InetSocketAddress} import org.scalatest.funsuite.AnyFunSuite abstract class PartitionAwareClientEndToEndTest extends AnyFunSuite { def await[T](a: Awaitable[T], d: Duration = 5.seconds): T = Await.result(a, d) type ClientType <: Stack.Parameterized[ClientType] with WithThriftPartitioningStrategy[ ClientType ] with ThriftRichClient type ServerType <: Stack.Parameterized[ServerType] with CommonParams[ ServerType ] with ThriftRichServer def clientImpl(): ClientType def serverImpl(): ServerType def newAddress(inet: InetSocketAddress, weight: Int): Address = { val shardId = inet.getPort val md = ZkMetadata.toAddrMetadata(ZkMetadata(Some(shardId))) val addr = new Address.Inet(inet, md) { override def toString: String = s"Address(${inet.getPort})-($shardId)" } WeightedAddress(addr, weight) } trait Ctx { val iface = new DeliveryService.MethodPerEndpoint { def getBox(addrInfo: AddrInfo, passcode: Byte): Future[Box] = Future.value(Box(addrInfo, "hi")) def getBoxes( addrs: collection.Seq[AddrInfo], passcode: Byte ): Future[collection.Seq[Box]] = Future.value( addrs.map(Box(_, s"size: ${addrs.size}")) // shows how many sub-requests hit an endpoint ) def sendBox(box: Box): Future[String] = Future.value(box.item) def sendBoxes(boxes: collection.Seq[Box]): Future[String] = Future.value(boxes.map(_.item).mkString(",")) } // response merger functions val getBoxesRepMerger: ResponseMerger[Seq[Box]] = (successes, failures) => if (successes.nonEmpty) Return(successes.flatten) else Throw(failures.head) val sendBoxesRepMerger: ResponseMerger[String] = (successes, failures) => if (successes.nonEmpty) Return(successes.mkString(";")) else Throw(failures.head) val inetAddresses: Seq[InetSocketAddress] = (0 until 5).map(_ => new InetSocketAddress(InetAddress.getLoopbackAddress, 0)) val servers: Seq[ListeningServer] = inetAddresses.map(inet => serverImpl().serveIface(inet, iface)) def fixedInetAddresses = servers.map(_.boundAddress.asInstanceOf[InetSocketAddress]) def addresses = servers.map { server => val inet = server.boundAddress.asInstanceOf[InetSocketAddress] newAddress(inet, 1) } val addrInfo0 = AddrInfo("zero", 12345) val addrInfo1 = AddrInfo("one", 11111) val addrInfo11 = AddrInfo("one", 11112) val addrInfo2 = AddrInfo("two", 22222) val addrInfo3 = AddrInfo("three", 33333) val addrInfo4 = AddrInfo("four", 44444) } trait HashingPartitioningCtx extends Ctx { // request merger functions -- only used for hashing case when multiple keys fall in the same shard val getBoxesReqMerger: RequestMerger[GetBoxes.Args] = listGetBoxes => GetBoxes.Args(listGetBoxes.map(_.listAddrInfo).flatten, listGetBoxes.head.passcode) val sendBoxesReqMerger: RequestMerger[SendBoxes.Args] = listSendBoxes => SendBoxes.Args(listSendBoxes.flatMap(_.boxes)) val hashingPartitioningStrategy = new ClientHashingStrategy({ case getBox: GetBox.Args => Map(getBox.addrInfo.name -> getBox) case getBoxes: GetBoxes.Args => getBoxes.listAddrInfo .groupBy { _.name }.map { case (hashingKey, subListAddrInfo) => hashingKey -> GetBoxes.Args(subListAddrInfo, getBoxes.passcode) } case sendBoxes: SendBoxes.Args => sendBoxes.boxes.groupBy(_.addrInfo.name).map { case (hashingKey, boxes) => hashingKey -> SendBoxes.Args(boxes) } }) hashingPartitioningStrategy.requestMergerRegistry .add(GetBoxes, getBoxesReqMerger) .add(SendBoxes, sendBoxesReqMerger) hashingPartitioningStrategy.responseMergerRegistry .add(GetBoxes, getBoxesRepMerger) .add(SendBoxes, sendBoxesRepMerger) } test("without partition strategy") { new Ctx { val client = clientImpl() .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") val expectedOneNode = Seq(Box(addrInfo1, "size: 3"), Box(addrInfo2, "size: 3"), Box(addrInfo3, "size: 3")) val result = await(client.getBoxes(Seq(addrInfo1, addrInfo2, addrInfo3), Byte.MinValue)) assert(result == expectedOneNode) assert(await(client.sendBox(Box(addrInfo1, "test"))) == "test") assert( await( client.sendBoxes(Seq(Box(addrInfo1, "test1"), Box(addrInfo2, "test2")))) == "test1,test2") assert(await(client.getBox(addrInfo1, Byte.MinValue)) == Box(addrInfo1, "hi")) client.asClosable.close() servers.map(_.close()) } } test("with consistent hashing strategy") { new HashingPartitioningCtx { val client = clientImpl().withPartitioning .strategy(hashingPartitioningStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") // addrInfo1 and addrInfo11 have the same key ("one") // addrInfo2 key ("two") val expectedTwoNodes = Seq(Box(addrInfo1, "size: 2"), Box(addrInfo11, "size: 2"), Box(addrInfo2, "size: 1")).toSet val expectedOneNode = Seq(Box(addrInfo1, "size: 3"), Box(addrInfo11, "size: 3"), Box(addrInfo2, "size: 3")).toSet val result = await(client.getBoxes(Seq(addrInfo1, addrInfo2, addrInfo11), Byte.MinValue)).toSet // if two keys hash to a singleton partition, expect one node, otherwise, two nodes. // local servers have random ports that are not consistent assert(result == expectedOneNode || result == expectedTwoNodes) client.asClosable.close() servers.map(_.close()) } } test("with consistent hashing strategy, unspecified endpoint returns error") { new HashingPartitioningCtx { val client = clientImpl().withPartitioning .strategy(hashingPartitioningStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") val e = intercept[NoPartitioningKeys] { await(client.sendBox(Box(addrInfo1, "test"))) } assert(e.getMessage.contains("sendBox")) client.asClosable.close() servers.map(_.close()) } } test("with errored hashing strategy") { val erroredHashingPartitioningStrategy = new ClientHashingStrategy({ case getBox: GetBox.Args => throw new Exception("something wrong") }) new HashingPartitioningCtx { val client = clientImpl().withPartitioning .strategy(erroredHashingPartitioningStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") intercept[PartitioningStrategyException] { await(client.getBox(addrInfo1, Byte.MinValue)) } client.asClosable.close() servers.map(_.close()) } } test("with custom partitioning strategy, each shard is a partition") { new Ctx { // structs with key zero/two are routed to partition 0, // and structs with key one are routed to partition 1 def lookUp(addrInfo: AddrInfo): Int = { addrInfo.name match { case "zero" | "two" => fixedInetAddresses(0).getPort case "one" => fixedInetAddresses(1).getPort } } val customPartitioningStrategy = ClientCustomStrategy.noResharding({ case getBox: GetBox.Args => Future.value(Map(lookUp(getBox.addrInfo) -> getBox)) case getBoxes: GetBoxes.Args => val partitionIdAndRequest: Map[Int, ThriftStructIface] = getBoxes.listAddrInfo.groupBy(lookUp).map { case (partitionId, listAddrInfo) => partitionId -> GetBoxes.Args(listAddrInfo, getBoxes.passcode) } Future.value(partitionIdAndRequest) }) customPartitioningStrategy.responseMergerRegistry.add(GetBoxes, getBoxesRepMerger) val client = clientImpl().withPartitioning .strategy(customPartitioningStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") val expectedTwoNodes = Seq(Box(addrInfo0, "size: 2"), Box(addrInfo2, "size: 2"), Box(addrInfo1, "size: 1")).toSet val result = await(client.getBoxes(Seq(addrInfo0, addrInfo1, addrInfo2), Byte.MinValue)).toSet assert(result == expectedTwoNodes) } } class CustomPartitioningCtx(lookUp: AddrInfo => Int) extends Ctx { val customPartitioningStrategy = ClientCustomStrategy.noResharding( { case getBox: GetBox.Args => Future.value(Map(lookUp(getBox.addrInfo) -> getBox)) case getBoxes: GetBoxes.Args => val partitionIdAndRequest: Map[Int, ThriftStructIface] = getBoxes.listAddrInfo.groupBy(lookUp).map { case (partitionId, listAddrInfo) => partitionId -> GetBoxes.Args(listAddrInfo, getBoxes.passcode) } Future.value(partitionIdAndRequest) }, { instance: Int => // p0(0,1), p1(1,2), p2(3, 4) val partitionPositions = List(0.to(1), 1.to(2), 3.until(fixedInetAddresses.size)) val position = fixedInetAddresses.indexWhere(_.getPort == instance) partitionPositions.zipWithIndex .filter { case (range, _) => range.contains(position) }.map(_._2) } ) customPartitioningStrategy.responseMergerRegistry.add(GetBoxes, getBoxesRepMerger) } test("with custom partitioning strategy, logical partition") { // struct keys to partition Ids def lookUp(addrInfo: AddrInfo): Int = { addrInfo.name match { case "four" => 0 case "three" | "two" => 1 case "one" | "zero" => 2 } } new CustomPartitioningCtx(lookUp) { val client = clientImpl().withPartitioning .strategy(customPartitioningStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") val expectedThreeNodes = Seq( Box(addrInfo0, "size: 2"), Box(addrInfo1, "size: 2"), Box(addrInfo2, "size: 2"), Box(addrInfo3, "size: 2"), Box(addrInfo4, "size: 1")).toSet val result = await( client.getBoxes( Seq(addrInfo0, addrInfo1, addrInfo2, addrInfo3, addrInfo4), Byte.MinValue)).toSet assert(result == expectedThreeNodes) } } test("with errored custom strategy") { val erroredCustomPartitioningStrategy = ClientCustomStrategy.noResharding({ case getBox: GetBox.Args => throw new Exception("something wrong") }) new Ctx { val client = clientImpl().withPartitioning .strategy(erroredCustomPartitioningStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") intercept[PartitioningStrategyException] { await(client.getBox(addrInfo0, Byte.MinValue)) } client.asClosable.close() servers.map(_.close()) } } test("with custom strategy, no logical partition") { def lookUp(addrInfo: AddrInfo): Int = { addrInfo.name match { case _ => 4 } } new CustomPartitioningCtx(lookUp) { val client = clientImpl().withPartitioning .strategy(customPartitioningStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") intercept[NoPartitionException] { await( client .getBoxes(Seq(addrInfo0, addrInfo1, addrInfo2, addrInfo3, addrInfo4), Byte.MinValue)) } } } test("with custom strategy, unset endpoint") { // struct keys to partition Ids def lookUp(addrInfo: AddrInfo): Int = { addrInfo.name match { case "four" => 0 case "three" | "two" => 1 case "one" | "zero" => 2 } } new CustomPartitioningCtx(lookUp) { val client = clientImpl().withPartitioning .strategy(customPartitioningStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") intercept[PartitioningStrategyException] { await(client.sendBoxes(Seq(Box(addrInfo1, "test1"), Box(addrInfo2, "test2")))) } } } test("with custom strategy, partitioning strategy dynamically changing") { new Ctx { val sr0 = new InMemoryStatsReceiver val sr1 = new InMemoryStatsReceiver var index = 0 // for testing purpose, set separate statsReceivers for instance0 and instance1 override val servers: Seq[ListeningServer] = inetAddresses.map { inet => if (index == 0) { index = index + 1 serverImpl().withStatsReceiver(sr0).serveIface(inet, iface) } else if (index == 1) { index = index + 1 serverImpl().withStatsReceiver(sr1).serveIface(inet, iface) } else { serverImpl().serveIface(inet, iface) } } // the observable state is a dynamic Integer, // when state changed, we route requests to a partition with current Integer as the Id val dynamic = Var(0) val observable: Activity[Int] = Activity(dynamic.map(Activity.Ok(_))) val getPartitionIdAndRequest: Int => ClientCustomStrategy.ToPartitionedMap = { state => { case sendBox: SendBox.Args => Future.value(Map(state -> sendBox)) } } val getLogicalPartitionId: Int => Int => Seq[Int] = { _ => { instance: Int => Seq(fixedInetAddresses.indexWhere(_.getPort == instance)) } } val dynamicStrategy = ClientCustomStrategy.resharding[Int]( getPartitionIdAndRequest, getLogicalPartitionId, observable ) val client = clientImpl().withPartitioning .strategy(dynamicStrategy) .build[DeliveryService.MethodPerEndpoint](Name.bound(addresses: _*), "client") val numBalancersBeforeRepartition = BalancerRegistry.get.allMetadata.size await(client.sendBox(Box(addrInfo0, ""))) dynamic() += 1 // Ensure that the number of balancers remain the same after the repartition assert(numBalancersBeforeRepartition == BalancerRegistry.get.allMetadata.size) await(client.sendBox(Box(addrInfo0, ""))) val server0Request = if (sr0.counters.isDefinedAt(Seq("requests"))) sr0.counters(Seq("requests")) else sr0.counters(Seq("thrift", "requests")) val server1Request = if (sr1.counters.isDefinedAt(Seq("requests"))) sr1.counters(Seq("requests")) else sr1.counters(Seq("thrift", "requests")) assert(server0Request == 1) assert(server1Request == 1) } } test("with cluster resharding, expanding cluster's instances") { new Ctx { val sr = new InMemoryStatsReceiver var index = 0 // set instance 1 a stats receiver override val servers: Seq[ListeningServer] = inetAddresses.map { inet => if (index == 0) { index = index + 1 serverImpl().serveIface(inet, iface) } else if (index == 1) { index = index + 1 serverImpl().withStatsReceiver(sr).serveIface(inet, iface) } else { serverImpl().serveIface(inet, iface) } } val getPartitionIdAndRequest: Set[Address] => ClientCustomStrategy.ToPartitionedMap = { _ => { case sendBox: SendBox.Args => Future.value(Map(1 -> sendBox)) // always route requests to partition 1 } } val getLogicalPartitionId: Set[Address] => Int => Seq[Int] = { cluster => { instance: Int => if (cluster.size == 2) { // p0(0) p1(1) Seq(fixedInetAddresses.indexWhere(_.getPort == instance)) } else { //p0(0,1) p1(2,3,4) val partitionPositions = List(0.to(1), 2.until(fixedInetAddresses.size)) val position = fixedInetAddresses.indexWhere(_.getPort == instance) partitionPositions.zipWithIndex .filter { case (range, _) => range.contains(position) }.map(_._2) } } } val clusterResharding = ClientCustomStrategy.clusterResharding(getPartitionIdAndRequest, getLogicalPartitionId) val dynamicAddresses = Var(Addr.Bound(addresses.take(2): _*)) val client = clientImpl().withPartitioning .strategy(clusterResharding) .build[DeliveryService.MethodPerEndpoint]( Name.Bound(dynamicAddresses, dynamicAddresses()), "client") // pre-resharding, the request goes to server1, // post-resharding, the request goes to server2/3/4 await(client.sendBox(Box(addrInfo0, ""))) val server1Request = if (sr.counters.isDefinedAt(Seq("requests"))) sr.counters(Seq("requests")) else sr.counters(Seq("thrift", "requests")) val numBalancersBeforeRepartition = BalancerRegistry.get.allMetadata.size assert(server1Request == 1) dynamicAddresses() = Addr.Bound(addresses: _*) // Ensure that the number of balancers remain the same after the repartition assert(numBalancersBeforeRepartition == BalancerRegistry.get.allMetadata.size) await(client.sendBox(Box(addrInfo0, ""))) assert(server1Request == 1) } } }
twitter/finagle
finagle-thrift/src/test/scala/com/twitter/finagle/thrift/exp/partitioning/PartitionAwareClientEndtoEndTest.scala
Scala
apache-2.0
18,436
package at.ac.tuwien.ifs.ir.model /** * Created by aldo on 10/10/14. */ class RunRecord(val iteration: String, val document: Document, val rank: Int, val score: Float) { override def toString: String = s"$iteration ${document.id} $rank $score" } object RunRecord { def apply(iteration: String, document: Document, rank: Int, score: Float) = new RunRecord(iteration, document, rank, score) def fromItems(arr: Array[String]): RunRecord = try { new RunRecord(arr(0), new Document(arr(1)), arr(2).toInt, arr(3).toFloat) } catch { case e: Exception => { println(arr.mkString(" ")); throw e } } }
aldolipani/PoolBiasEstimators
src/main/scala/at/ac/tuwien/ifs/ir/model/RunRecord.scala
Scala
apache-2.0
631
package com.mizhi.nlp.stemmers.huskpaice import com.mizhi.nlp.stemmers.huskpaice.RuleAction._ import org.mockito.Mockito.{doReturn, spy} class RuleSpec extends UnitSpec { val rule = Rule("suffix", None, true, stop) describe("apply") { val state = StemmingState("asuffix", true, None) describe("when rule is applied") { val spiedRule = spy(rule.copy(append=Some("thing"))) doReturn(true, Array[Object](): _*).when(spiedRule).ruleApplies(state) doReturn(true, Array[Object](): _*).when(spiedRule).stemAcceptable(state.word) it("removes suffix") { spiedRule(state).word should be("athing") } it("sets intact to false") { spiedRule(state).intact should be(false) } it("sets the nextAction to the rule's action") { spiedRule(state).nextAction should be (Some(spiedRule.nextAction)) } } describe("when rule is not applied") { val spiedRule = spy(rule.copy(append=Some("thing"))) doReturn(false, Array[Object](): _*).when(spiedRule).ruleApplies(state) it("returns same state") { spiedRule(state) should be(state) } } } describe("applyStringTransform") { describe("when append is None") { it("leaves stem alone") { rule.applyStringTransform("prefixwordsuffix") should be("prefixwordsuffix") } } describe("when append is the empty string") { it("strips suffix") { rule.copy(append=Some("")).applyStringTransform("prefixwordsuffix") should be("prefixword") } } describe("when append is not empty") { it("replaces suffix") { rule.copy(append=Some("newstring")).applyStringTransform("prefixwordsuffix") should be("prefixwordnewstring") } } } describe("endingMatches") { it("detects when ending matches suffix") { rule.endingMatches("somefoolstringsuffix") should be(true) } it("detects when ending doesn't match suffix") { rule.endingMatches("somefoolstring") should be(false) } } describe("intactnessIsGood") { val intactState = StemmingState("foo", true, None) val modifiedStem = intactState.copy(intact=false) describe("when rule requires the word to be intact") { it("is true when stem is intact") { rule.intactnessIsGood(intactState) should be(true) } it("is false when stem is not intact") { rule.intactnessIsGood(modifiedStem) should be(false) } } describe("when rule does not require the word to be intact") { val modifiedRule = rule.copy(intactOnly = false) it("is true when stem is intact") { modifiedRule.intactnessIsGood(intactState) should be(true) } it("is true when stem is not intact") { modifiedRule.intactnessIsGood(modifiedStem) should be(true) } } } describe("stemAcceptable") { describe("when word starts with vowel") { it("returns true when length is >= 2") { rule.stemAcceptable("ace") should be(true) } it("returns false when length is < 2") { rule.stemAcceptable("a") should be(false) } it("works with empty string") { rule.stemAcceptable("") should be(false) } } describe("when word starts with consonant") { it("returns true when length is >= 3 and has a vowel") { rule.stemAcceptable("cad") should be(true) } it("returns true when vowel is a y") { rule.stemAcceptable("cry") should be(true) } it("returns false when length is < 3") { rule.stemAcceptable("cr") should be (false) } it("returns false when there are no vowels") { rule.stemAcceptable("str") should be (false) } } } }
mizhi/scala-stemmer
src/test/scala/com/mizhi/nlp/stemmers/huskpaice/RuleSpec.scala
Scala
mit
3,755
/* * SPDX-License-Identifier: Apache-2.0 * * Copyright 2015-2021 Andre White. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * https://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package io.truthencode.ddo.model.feats import io.truthencode.ddo.model.race.Race import io.truthencode.ddo.model.race.Race.Warforged import io.truthencode.ddo.support.requisite.{RaceRequisiteImpl, RequiresNoneOfRace} /** * Created by adarr on 4/6/2017. */ trait EberronReligionNonWarforged extends RaceRequisiteImpl with RequiresNoneOfRace with EberronReligionBase { self: DeityFeat => override def noneOfRace: Seq[(Race, Int)] = List((Warforged, 1)) }
adarro/ddo-calc
subprojects/common/ddo-core/src/main/scala/io/truthencode/ddo/model/feats/EberronReligionNonWarforged.scala
Scala
apache-2.0
1,138
/* * Copyright 2022 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package iht.controllers.application.assets.stocksAndShares import iht.config.AppConfig import iht.controllers.application.ApplicationControllerTest import iht.forms.ApplicationForms._ import iht.models.application.ApplicationDetails import iht.testhelpers.CommonBuilder import iht.testhelpers.TestHelper._ import iht.utils.CommonHelper import iht.views.html.application.asset.stocksAndShares.stocks_and_shares_not_listed import play.api.mvc.MessagesControllerComponents import play.api.test.Helpers.{contentAsString, _} import uk.gov.hmrc.play.bootstrap.frontend.controller.FrontendController class StocksAndSharesNotListedControllerTest extends ApplicationControllerTest { lazy val submitUrl = CommonHelper.addFragmentIdentifierToUrl(routes.StocksAndSharesOverviewController.onPageLoad().url, AssetsStocksNotListedID) def setUpTests(applicationDetails: ApplicationDetails) = { createMocksForApplication(mockCachingConnector, mockIhtConnector, appDetails = Some(applicationDetails), getAppDetails = true, saveAppDetails = true, storeAppDetailsInCache = true) } protected abstract class TestController extends FrontendController(mockControllerComponents) with StocksAndSharesNotListedController { override val cc: MessagesControllerComponents = mockControllerComponents override implicit val appConfig: AppConfig = mockAppConfig override val stocksAndSharesNotListedView: stocks_and_shares_not_listed = app.injector.instanceOf[stocks_and_shares_not_listed] } def stocksAndSharesNotListedController = new TestController { val authConnector = mockAuthConnector override val cachingConnector = mockCachingConnector override val ihtConnector = mockIhtConnector } def stocksAndSharesNotListedControllerNotAuthorised = new TestController { val authConnector = mockAuthConnector override val cachingConnector = mockCachingConnector override val ihtConnector = mockIhtConnector } "StocksAndSharesNotListedController" must { "redirect to login page on PageLoad if the user is not logged in" in { val result = stocksAndSharesNotListedControllerNotAuthorised.onPageLoad(createFakeRequest(isAuthorised = false)) status(result) must be(SEE_OTHER) redirectLocation(result) must be (Some(loginUrl)) } "redirect to login page on Submit if the user is not logged in" in { val result = stocksAndSharesNotListedControllerNotAuthorised.onSubmit(createFakeRequest(isAuthorised = false)) status(result) must be(SEE_OTHER) redirectLocation(result) must be (Some(loginUrl)) } "respond with OK on page load" in { val applicationDetails = CommonBuilder.buildApplicationDetails setUpTests(applicationDetails) val result = stocksAndSharesNotListedController.onPageLoad(createFakeRequest()) status(result) must be(OK) } "save application and go to stocksAndShares overview page on submit" in { val applicationDetails = CommonBuilder.buildApplicationDetails val formFill = stockAndShareNotListedForm.fill(CommonBuilder.buildStockAndShare.copy(isNotListed = Some(true), valueNotListed = Some(200))) implicit val request = createFakeRequest().withFormUrlEncodedBody(formFill.data.toSeq: _*) setUpTests(applicationDetails) val result = stocksAndSharesNotListedController.onSubmit()(request) status(result) must be (SEE_OTHER) redirectLocation(result) must be (Some(submitUrl)) } "wipe out the sharesNotListed value if user selects No, save application and go to stocksAndShares overview page on submit" in { val sharesNotListed = CommonBuilder.buildStockAndShare.copy(isNotListed = Some(false), valueNotListed = Some(200)) val applicationDetails = CommonBuilder.buildApplicationDetails.copy( allAssets = Some(CommonBuilder.buildAllAssets.copy( stockAndShare = Some(sharesNotListed)))) val formFill = stockAndShareNotListedForm.fill(sharesNotListed) implicit val request = createFakeRequest().withFormUrlEncodedBody(formFill.data.toSeq: _*) setUpTests(applicationDetails) val result = stocksAndSharesNotListedController.onSubmit()(request) status(result) must be (SEE_OTHER) redirectLocation(result) must be (Some(submitUrl)) val capturedValue = verifyAndReturnSavedApplicationDetails(mockIhtConnector) val expectedAppDetails = applicationDetails.copy(allAssets = applicationDetails.allAssets.map(_.copy( stockAndShare = Some(CommonBuilder.buildStockAndShare.copy(valueNotListed = None, isNotListed = Some(false)))))) capturedValue mustBe expectedAppDetails } "display validation message when form is submitted with no values entered" in { val applicationDetails = CommonBuilder.buildApplicationDetails implicit val request = createFakeRequest() setUpTests(applicationDetails) val result = stocksAndSharesNotListedController.onSubmit()(request) status(result) must be (BAD_REQUEST) contentAsString(result) must include (messagesApi("error.problem")) } "redirect to overview when form is submitted with answer yes and a value entered" in { val applicationDetails = CommonBuilder.buildApplicationDetails implicit val request = createFakeRequest().withFormUrlEncodedBody(("isNotListed", "true"), ("valueNotListed", "233")) setUpTests(applicationDetails) val result = stocksAndSharesNotListedController.onSubmit()(request) status(result) must be (SEE_OTHER) redirectLocation(result) must be (Some(submitUrl)) } "respond with bad request when incorrect value are entered on the page" in { implicit val fakePostRequest = createFakeRequest().withFormUrlEncodedBody(("value", "utytyyterrrrrrrrrrrrrr")) createMockToGetRegDetailsFromCacheNoOption(mockCachingConnector) val result = stocksAndSharesNotListedController.onSubmit (fakePostRequest) status(result) mustBe (BAD_REQUEST) } behave like controllerOnPageLoadWithNoExistingRegistrationDetails(mockCachingConnector, stocksAndSharesNotListedController.onPageLoad(createFakeRequest())) } }
hmrc/iht-frontend
test/iht/controllers/application/assets/stocksAndShares/StocksAndSharesNotListedControllerTest.scala
Scala
apache-2.0
6,863
/** * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package kafka.server import java.util.Properties import junit.framework.Assert._ import org.easymock.{Capture, EasyMock} import org.junit.Test import kafka.integration.KafkaServerTestHarness import kafka.utils._ import kafka.common._ import kafka.log.LogConfig import kafka.admin.{AdminOperationException, AdminUtils} class DynamicConfigChangeTest extends KafkaServerTestHarness { def generateConfigs() = List(KafkaConfig.fromProps(TestUtils.createBrokerConfig(0, zkConnect))) @Test def testConfigChange() { assertTrue("Should contain a ConfigHandler for topics", this.servers(0).dynamicConfigHandlers.contains(ConfigType.Topic)) val oldVal: java.lang.Long = 100000L val newVal: java.lang.Long = 200000L val tp = TopicAndPartition("test", 0) val logProps = new Properties() logProps.put(LogConfig.FlushMessagesProp, oldVal.toString) AdminUtils.createTopic(zkUtils, tp.topic, 1, 1, logProps) TestUtils.retry(10000) { val logOpt = this.servers(0).logManager.getLog(tp) assertTrue(logOpt.isDefined) assertEquals(oldVal, logOpt.get.config.flushInterval) } logProps.put(LogConfig.FlushMessagesProp, newVal.toString) AdminUtils.changeTopicConfig(zkUtils, tp.topic, logProps) TestUtils.retry(10000) { assertEquals(newVal, this.servers(0).logManager.getLog(tp).get.config.flushInterval) } } // For now client config changes do not do anything. Simply verify that the call was made @Test def testClientConfigChange() { assertTrue("Should contain a ConfigHandler for topics", this.servers(0).dynamicConfigHandlers.contains(ConfigType.Client)) val clientId = "testClient" val props = new Properties() props.put("a.b", "c") props.put("x.y", "z") AdminUtils.changeClientIdConfig(zkUtils, clientId, props) TestUtils.retry(10000) { val configHandler = this.servers(0).dynamicConfigHandlers(ConfigType.Client).asInstanceOf[ClientIdConfigHandler] assertTrue("ClientId testClient must exist", configHandler.configPool.contains(clientId)) assertEquals("ClientId testClient must be the only override", 1, configHandler.configPool.size) assertEquals("c", configHandler.configPool.get(clientId).getProperty("a.b")) assertEquals("z", configHandler.configPool.get(clientId).getProperty("x.y")) } } @Test def testConfigChangeOnNonExistingTopic() { val topic = TestUtils.tempTopic try { val logProps = new Properties() logProps.put(LogConfig.FlushMessagesProp, 10000: java.lang.Integer) AdminUtils.changeTopicConfig(zkUtils, topic, logProps) fail("Should fail with AdminOperationException for topic doesn't exist") } catch { case e: AdminOperationException => // expected } } @Test def testProcessNotification { val props = new Properties() props.put("a.b", "10") // Create a mock ConfigHandler to record config changes it is asked to process val entityArgument = new Capture[String]() val propertiesArgument = new Capture[Properties]() val handler = EasyMock.createNiceMock(classOf[ConfigHandler]) handler.processConfigChanges( EasyMock.and(EasyMock.capture(entityArgument), EasyMock.isA(classOf[String])), EasyMock.and(EasyMock.capture(propertiesArgument), EasyMock.isA(classOf[Properties]))) EasyMock.expectLastCall().once() EasyMock.replay(handler) val configManager = new DynamicConfigManager(zkUtils, Map(ConfigType.Topic -> handler)) // Notifications created using the old TopicConfigManager are ignored. configManager.processNotification(Some("not json")) // Incorrect Map. No version try { val jsonMap = Map("v" -> 1, "x" -> 2) configManager.processNotification(Some(Json.encode(jsonMap))) fail("Should have thrown an Exception while parsing incorrect notification " + jsonMap) } catch { case t: Throwable => } // Version is provided. EntityType is incorrect try { val jsonMap = Map("version" -> 1, "entity_type" -> "garbage", "entity_name" -> "x") configManager.processNotification(Some(Json.encode(jsonMap))) fail("Should have thrown an Exception while parsing incorrect notification " + jsonMap) } catch { case t: Throwable => } // EntityName isn't provided try { val jsonMap = Map("version" -> 1, "entity_type" -> ConfigType.Topic) configManager.processNotification(Some(Json.encode(jsonMap))) fail("Should have thrown an Exception while parsing incorrect notification " + jsonMap) } catch { case t: Throwable => } // Everything is provided val jsonMap = Map("version" -> 1, "entity_type" -> ConfigType.Topic, "entity_name" -> "x") configManager.processNotification(Some(Json.encode(jsonMap))) // Verify that processConfigChanges was only called once EasyMock.verify(handler) } }
vkroz/kafka
core/src/test/scala/unit/kafka/server/DynamicConfigChangeTest.scala
Scala
apache-2.0
5,736
package ch.wsl.box.rest.routes.enablers.twirl import akka.http.scaladsl.marshalling.{Marshaller, _} import akka.http.scaladsl.model.MediaType import akka.http.scaladsl.model.MediaTypes._ import play.twirl.api.{Html, Txt, Xml} object Implicits { /** Twirl marshallers for Xml, Html and Txt mediatypes */ implicit val twirlHtmlMarshaller = twirlMarshaller[Html](`text/html`) implicit val twirlTxtMarshaller = twirlMarshaller[Txt](`text/plain`) implicit val twirlXmlMarshaller = twirlMarshaller[Xml](`text/xml`) def twirlMarshaller[A](contentType: MediaType): ToEntityMarshaller[A] = { Marshaller.StringMarshaller.wrap(contentType)(_.toString) } }
Insubric/box
server/src/main/scala/ch/wsl/box/rest/routes/enablers/twirl/Implicits.scala
Scala
apache-2.0
667
/* * Copyright 2018 Michal Harish, michal.harish@gmail.com * * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package io.amient.affinity.core.util import java.util.concurrent.ConcurrentHashMap import akka.actor.ActorSystem import akka.http.scaladsl.model.HttpResponse import com.codahale.metrics.{MetricRegistry, Timer} import scala.concurrent.{Future, Promise} import scala.util.{Failure, Success} object AffinityMetrics { private val reporters = scala.collection.mutable.ListBuffer[MetricRegistry => Unit]() def apply(f: MetricRegistry => Unit): Unit = reporters += f private val metricsRegistries = new ConcurrentHashMap[ActorSystem, AffinityMetrics]() def forActorSystem(system: ActorSystem): AffinityMetrics = { metricsRegistries.get(system) match { case null => val registry = new AffinityMetrics reporters.foreach(_(registry)) metricsRegistries.put(system, registry) registry case registry => registry } } } class AffinityMetrics extends MetricRegistry { private implicit val executor = scala.concurrent.ExecutionContext.Implicits.global private val processMetricsMap = new ConcurrentHashMap[String, ProcessMetrics]() def meterAndHistogram(name: String): ProcessMetrics = { processMetricsMap.get(name) match { case null => val m = new ProcessMetrics(name) processMetricsMap.put(name, m) m case some => some } } def process(groupName: String, result: Promise[_]): Unit = process(groupName, result.future) def process(groupName: String, result: Future[Any]): Unit = { val metrics = meterAndHistogram(groupName) val startTime = metrics.markStart() result.onComplete { case Success(response: HttpResponse) => if (response.status.intValue() < 400) metrics.markSuccess(startTime) else metrics.markFailure(startTime) case Success(_) => metrics.markSuccess(startTime) case Failure(_) => metrics.markFailure(startTime) } } class ProcessMetrics(name: String) { val durations = timer(s"$name.timer") val successes = meter(s"$name.success") val failures = meter(s"$name.failure") def markStart(): Timer.Context = durations.time() def markSuccess(context: Timer.Context, n: Long = 1): Unit = { context.stop successes.mark(n) } def markFailure(context: Timer.Context): Unit = { context.stop failures.mark() } } }
amient/affinity
core/src/main/scala/io/amient/affinity/core/util/AffinityMetrics.scala
Scala
apache-2.0
3,192
//: ---------------------------------------------------------------------------- //: Copyright (C) 2015 Verizon. All Rights Reserved. //: //: Licensed under the Apache License, Version 2.0 (the "License"); //: you may not use this file except in compliance with the License. //: You may obtain a copy of the License at //: //: http://www.apache.org/licenses/LICENSE-2.0 //: //: Unless required by applicable law or agreed to in writing, software //: distributed under the License is distributed on an "AS IS" BASIS, //: WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. //: See the License for the specific language governing permissions and //: limitations under the License. //: //: ---------------------------------------------------------------------------- package funnel package elastic import argonaut._ import java.io.File import journal.Logger import java.util.Date import java.text.SimpleDateFormat import java.util.concurrent.{ExecutorService, Executors} import scala.util.control.NonFatal import scalaz.stream.Process import scalaz.concurrent.{Strategy, Task} import Process.constant import scalaz._ import scalaz.stream.async.mutable.ScalazHack object Elastic { import Argonaut._ import Kleisli.ask import scalaz.syntax.kleisli._ import scalaz.syntax.monad._ // pulls in *> import scala.concurrent.duration._ type SourceURL = String type ExperimentID = String type GroupID = String type Window = String type Path = List[String] type ES[A] = Kleisli[Task, ElasticCfg, A] private[this] val log = Logger[Elastic.type] val esPool: ExecutorService = Executors.newFixedThreadPool(8, Monitoring.daemonThreads("elastic-publisher-thread")) /** * */ val getConfig: ES[ElasticCfg] = ask[Task, ElasticCfg] /** * Not in Scalaz until 7.2 so duplicating here. */ def lower[M[_]:Monad,A,B](k: Kleisli[M,A,B]): Kleisli[M,A,M[B]] = Kleisli(a => Monad[M].pure(k(a))) /** * natural transformation between task and ES, which is a kleisli * in Task. provided for explicitness, instead of using the `liftKleisli` * syntax all through the code. */ def lift: Task ~> ES = new (Task ~> ES) { def apply[A](t: Task[A]) = t.liftKleisli } /** * get a handle on the subscriptionTimeout without having an ES instance */ def duration: Reader[ElasticCfg, FiniteDuration] = Reader { es => es.subscriptionTimeout } /** * build a function that sends string-like inputs to the specified request * using HTTP GET verb which will be handled using the customised `handler`. * * @see funnel.elastic.Elastic.handler */ def elasticString(req: HttpOp)(H: HttpLayer): ES[String] = H.http(req) /** * send the supplied json string to the configured elastic search endpoint * using HTTP POST. */ def elastic(req: HttpOp)(H: HttpLayer): ES[Unit] = for { ta <- lower(elasticString(req)(H)) _ <- lift(ta.attempt.map(_.fold( e => log.error(s"Unable to send document to elastic search due to '$e'. Request was: \\n $req"), _ => ()))) } yield () /** * retries any non-HTTP errors with exponential backoff */ def retry[A](task: Task[A])(m: ElasticMetrics): Task[A] = { val schedule = Stream.iterate(2)(_ * 2).take(30).map(_.seconds) val t = task.attempt.flatMap(_.fold( { case e: HttpException => Task.delay { if (e.serverError) m.HttpResponse5xx.increment else if (e.clientError) m.HttpResponse4xx.increment }.flatMap(_ => Task.fail(e)) case e => Task.delay { log.error(s"Error contacting ElasticSearch: $e. Retrying...") m.NonHttpErrors.increment } >>= (_ => Task.fail(e)) }, a => Task.now(a) )) t.retry(schedule, { case e: HttpException if e.clientError => false case e: HttpException => true //retry on server errors like "gateway timeout" case e@NonFatal(_) => true case _ => false }) } private def toBulkPayload(jsons: Seq[Json]): String = jsons.map { js => s"""{ "create": {}}\\n${js.nospaces}\\n""" }.mkString /** * Publishes to an ElasticSearch URL at `esURL`. */ def bufferAndPublish( flaskName: String, flaskCluster: String )(M: Monitoring, E: Strategy, H: HttpLayer, iselfie: ElasticMetrics )(jsonStream: ElasticCfg => Process[Task, Json]): ES[Unit] = { def doPublish(de: Process[Task, Seq[Json]], cfg: ElasticCfg): Process[Task, Unit] = de to constant( (jsons: Seq[Json]) => retry(iselfie.HttpResponse2xx.timeTask( for { //delaying task is important here. Otherwise we will not really retry to send http request u <- Task.delay(esBulkURL) _ = log.debug(s"Posting ${jsons.size} docs.") _ <- H.http(POST(u, Reader((cfg: ElasticCfg) => toBulkPayload(jsons))))(cfg) } yield () ))(iselfie).attempt.map { case \\/-(v) => () case -\\/(t) => //if we fail to publish metric, proceed to the next one // TODO: consider circuit breaker on ES failures (embed into HttpLayer) // TODO: how does publishing dies when flasks stops monitoring target? do we release resources? log.warn(s"[elastic] failed to publish. error=$t cnt=${jsons.size} data=$jsons") iselfie.BufferDropped.increment () } ) for { _ <- ensureTemplate(H) r <- Kleisli.kleisli[Task, ElasticCfg, Unit] { (cfg: ElasticCfg) => log.info(s"Initializing Elastic buffer of size ${cfg.bufferSize}...") val buffer = ScalazHack.observableCircularBuffer[Json]( cfg.bufferSize, iselfie.BufferDropped, iselfie.BufferUsed )(E) log.info(s"Started Elastic subscription (max batch size=${cfg.batchSize})") // Reads from the monitoring instance and posts to the publishing queue val read = jsonStream(cfg).to(buffer.enqueue) // Reads from the publishing queue and writes to ElasticSearch val write = doPublish(buffer.dequeueBatch(cfg.batchSize), cfg) Nondeterminism[Task].reduceUnordered[Unit, Unit](Seq(read.run, write.run)) } } yield r } /****************************** indexing ******************************/ /** * construct the actual url to send documents to based on the configuration * parameters, taking into account the index data pattern and prefix. */ def indexURL: Reader[ElasticCfg, String] = Reader { es => val date = new SimpleDateFormat(es.dateFormat).format(new Date) s"${es.url}/${es.indexName}-$date" } /** * given the ES url, make sure that all our requests are properly set with * the application/json content mime type. */ def esURL: Reader[ElasticCfg, String] = Reader { es => s"${indexURL(es)}/${es.typeName}" } def esBulkURL: Reader[ElasticCfg, String] = Reader { es => s"${indexURL(es)}/${es.typeName}/_bulk" } private def esTemplateURL: Reader[ElasticCfg, String] = Reader { es => s"${es.url}/_template/${es.templateName}" } private def esTemplate: Reader[ElasticCfg, String] = Reader { cfg => cfg.templateLocation.map( f => scala.io.Source.fromFile(new File(f).getAbsolutePath).mkString ).getOrElse( sys.error("no index mapping template specified.") ) } /** * returns true if the index was created. False if it already existed. */ def ensureIndex(url: Reader[ElasticCfg, String])(H: HttpLayer): ES[Boolean] = ensureExists( HEAD(url), //create index PUT(url, Reader((cfg: ElasticCfg) => Json("settings" := Json("index.cache.query.enable" := true)).nospaces)) )(H) /** * ensure the index we are trying to send documents too (defined in the config) * exists in the backend elastic search cluster. */ def ensureExists(check: HttpOp, action: HttpOp)(H: HttpLayer): ES[Boolean] = for { s <- H.http(check).mapK(_.attempt) b <- s.fold( { case HttpException(404) => H.http(action).map(_ => true) case e => lift(Task.fail(e)) // SPLODE! }, z => lift(Task.now(false)) ) } yield b /** * load the template specified in the configuration and send it to the index * to ensure that all the document fields we publish are correctly handled by * elastic search / kibana. */ def ensureTemplate(H: HttpLayer): ES[Unit] = ensureExists( HEAD( esTemplateURL.map {s => log.info(s"Ensuring Elastic template $s exists..."); s } ), PUT(esTemplateURL, esTemplate) )(H).map(_ => ()) }
neigor/funnel
elastic/src/main/scala/Elastic.scala
Scala
apache-2.0
8,723
/* * StructuredAlgorithm.scala * Abstract class for algorithms that are structured * * Created By: Brian Ruttenberg (bruttenberg@cra.com) * Creation Date: December 30, 2015 * * Copyright 2015 Avrom J. Pfeffer and Charles River Analytics, Inc. * See http://www.cra.com or email figaro@cra.com for information. * * See http://www.github.com/p2t2/figaro for a copy of the software license. */ package com.cra.figaro.algorithm.structured.algorithm import com.cra.figaro.algorithm.Algorithm import com.cra.figaro.language._ import scala.collection.mutable.Map import com.cra.figaro.algorithm.factored.factors.Factor import com.cra.figaro.algorithm.factored.factors.Semiring import com.cra.figaro.algorithm.structured.Problem import com.cra.figaro.algorithm.structured.ComponentCollection import com.cra.figaro.algorithm.OneTimeMPE import com.cra.figaro.algorithm.AlgorithmException abstract class StructuredMPEAlgorithm(val universe: Universe) extends Algorithm with OneTimeMPE { def run(): Unit val semiring: Semiring[Double] //val targetFactors: Map[Element[_], Factor[Double]] = Map() val cc: ComponentCollection = new ComponentCollection val problem = new Problem(cc, List()) // We have to add all active elements to the problem since these elements, if they are every used, need to have components created at the top level problem universe.permanentElements.foreach(problem.add(_)) val evidenceElems = universe.conditionedElements ::: universe.constrainedElements def initialComponents() = (universe.permanentElements ++ evidenceElems).distinct.map(cc(_)) /** * Returns the most likely value for the target element. */ def mostLikelyValue[T](target: Element[T]): T = { val targetVar = cc(target).variable val factor = problem.recordingFactors(targetVar).asInstanceOf[Factor[T]] if (factor.size != 1) throw new AlgorithmException//("Final factor for most likely value has more than one entry") factor.get(List()) } }
scottcb/figaro
Figaro/src/main/scala/com/cra/figaro/algorithm/structured/algorithm/StructuredMPEAlgorithm.scala
Scala
bsd-3-clause
2,049
/* * Copyright (C) 2012 The Regents of The University California. * All rights reserved. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package shark.memstore2 import java.nio.ByteBuffer import scala.collection.immutable.BitSet import shark.memstore2.column.ColumnIterator import shark.memstore2.column.ColumnIteratorFactory /** * An iterator for a partition of data. Each element returns a ColumnarStruct * that can be read by a ColumnarStructObjectInspector. * * @param numRows: total number of rows in this partition. * @param columnIterators: iterators for all columns. * @param columnUsed: an optional bitmap indicating whether a column is used. */ class TablePartitionIterator( val numRows: Long, val columnIterators: Array[ColumnIterator], val columnUsed: BitSet = null) extends Iterator[ColumnarStruct] { private val _struct = new ColumnarStruct(columnIterators) private var _position: Long = 0 def hasNext(): Boolean = _position < numRows def next(): ColumnarStruct = { _position += 1 var i = 0 while (i < _columnIteratorsToAdvance.size) { _columnIteratorsToAdvance(i).next i += 1 } _struct } // Track the list of columns we need to call next on. private val _columnIteratorsToAdvance: Array[ColumnIterator] = { if (columnUsed == null) { columnIterators } else { columnUsed.map(colId => columnIterators(colId)).toArray } } }
vax11780/shark
src/main/scala/shark/memstore2/TablePartitionIterator.scala
Scala
apache-2.0
1,956
package com.bradbrok.filmomatic.state object Direction extends Enumeration { type Direction = Value val In, Out, Alternate = Value }
bradbrok/Film-O-Matic
core/src/main/scala/com/bradbrok/filmomatic/state/Direction.scala
Scala
mit
138
/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you under the Apache License, Version 2.0 (the * "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.spark.sql import org.apache.kylin.cube.CubeInstance import org.apache.kylin.cube.cuboid.Cuboid import org.apache.spark.sql.types.StructType import org.apache.spark.sql.execution.datasource.FilePruner import org.apache.spark.sql.execution.datasources.HadoopFsRelation import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat import scala.collection.mutable.{HashMap => MutableHashMap} class KylinDataFrameManager(sparkSession: SparkSession) { private var extraOptions = new MutableHashMap[String, String]() private var userSpecifiedSchema: Option[StructType] = None /** File format for table */ def format(source: String): KylinDataFrameManager = { option("source", source) this } /** Add key-value to options */ def option(key: String, value: String): KylinDataFrameManager = { this.extraOptions += (key -> value) this } /** Add boolean value to options, for compatibility with Spark */ def option(key: String, value: Boolean): KylinDataFrameManager = { option(key, value.toString) } /** Add long value to options, for compatibility with Spark */ def option(key: String, value: Long): KylinDataFrameManager = { option(key, value.toString) } /** Add double value to options, for compatibility with Spark */ def option(key: String, value: Double): KylinDataFrameManager = { option(key, value.toString) } def isFastBitmapEnabled(isFastBitmapEnabled: Boolean): KylinDataFrameManager = { option("isFastBitmapEnabled", isFastBitmapEnabled.toString) this } def cuboidTable(cubeInstance: CubeInstance, layout: Cuboid): DataFrame = { option("project", cubeInstance.getProject) option("cubeId", cubeInstance.getUuid) option("cuboidId", layout.getId) val indexCatalog = new FilePruner(cubeInstance, layout, sparkSession, options = extraOptions.toMap) sparkSession.baseRelationToDataFrame( HadoopFsRelation( indexCatalog, partitionSchema = indexCatalog.partitionSchema, dataSchema = indexCatalog.dataSchema.asNullable, bucketSpec = None, new ParquetFileFormat, options = extraOptions.toMap)(sparkSession)) } /** * Specifies the input schema. Some data sources (e.g. JSON) can infer the input schema * automatically from data. By specifying the schema here, the underlying data source can * skip the schema inference step, and thus speed up data loading. * * @since 1.4.0 */ def schema(schema: StructType): KylinDataFrameManager = { this.userSpecifiedSchema = Option(schema) this } }
apache/kylin
kylin-spark-project/kylin-spark-common/src/main/scala/org/apache/spark/sql/KylinDataFrameManager.scala
Scala
apache-2.0
3,414
import scala.reflect.runtime.universe._ import scala.reflect.runtime.{currentMirror => cm} import scala.tools.reflect.ToolBox object Test extends App { val toolbox = cm.mkToolBox() def printSource[T](expr: Expr[T]) { val ttree = toolbox typecheck expr.tree println(ttree.toString) } var y = 3 printSource(reify { 5 + y }) }
felixmulder/scala
test/files/run/t5816.scala
Scala
bsd-3-clause
350
/* * Copyright (c) 2018. Yuriy Stul */ package com.stulsoft.ysps.pforcomprehansion import scala.util.Try /** * @author Yuriy Stul */ object Example7 extends App { test1() test2() test3() test4() test5() def test1(): Unit = { println("==>test1") val result = for { _ <- f1(false) _ <- f2(false) } yield "Everything is OK" println(result) println("<==test1") } def test2(): Unit = { println("==>test2") val result = for { _ <- f1(true) _ <- f2(false) } yield "Everything is OK" println(result) println("<==test2") } def f1(toFail: Boolean): Try[Boolean] = { Try(if (toFail) throw new RuntimeException("f1 failed") else true ) } def f2(toFail: Boolean): Try[Boolean] = { Try(if (toFail) throw new RuntimeException("f2 failed") else true ) } def test3(): Unit = { println("==>test3") val result = for { _ <- f1(true) _ <- f2(true) } yield "Everything is OK" println(result) println("<==test3") } def test4(): Unit = { println("==>test4") val result = for { _ <- f1(false) _ <- f2(true) } yield "Everything is OK" println(result) println("<==test4") } def test5(): Unit = { println("==>test5") val result1 = for { _ <- f1(false) _ <- f3(false) } yield "Everything is OK" println(s"result1=$result1") val result2 = for { _ <- f1(false) _ <- f3(true) } yield "Everything is OK" println(s"result2=$result2") println("<==test5") } def f3(toFail: Boolean): Try[Boolean] = { Try { if (toFail) throw new RuntimeException("f3 failed") else true } } }
ysden123/ysps
src/main/scala/com/stulsoft/ysps/pforcomprehansion/Example7.scala
Scala
mit
1,766
package de.sciss.cord package incomplete import de.sciss.cord.audio.AudioProcessingEvent import org.scalajs.dom._ import org.scalajs.dom.html.Canvas import scala.scalajs.js import scalatags.JsDom.all._ import scala.scalajs.js.timers.SetIntervalHandle class Meter { meter => private var lastPeak = 0.0 private var lastRMS = 0.0 private var sqrSum = 0.0 private var sqrMax = 0.0 private var count = 0 lazy val render: Canvas = { val elem = canvas(cls := "meter").render elem } def peak: Double = { if (count > 0) lastPeak = js.Math.sqrt(sqrMax) lastPeak } def rms: Double = { if (count > 0) lastRMS = js.Math.sqrt(sqrSum / count) lastRMS } def reset(): Unit = if (count > 0) { sqrSum = 0.0 sqrMax = 0.0 count = 0 } def node(context: AudioContext): AudioNode = { // println("INIT METER NODE") // val inNode = context.createGain() // val squared = context.createGain() // val isFirefox = navigator.userAgent.toLowerCase.indexOf("firefox") > -1 val blockSize = 512 // 0 // if (isFirefox) 512 else 0 // Chrome doesn't accept any blockSize by default (4096) val analyze = context.createScriptProcessor(blockSize, 1, 1) analyze.onaudioprocess = { e: AudioProcessingEvent => // if (paintCount == 0) println("IN AUDIO LOOP") val input = e.inputBuffer.getChannelData(0) val len = input.length var i = 0; while (i < len) { val x0 = input(i) val x = x0 * x0 sqrSum += x if (x > sqrMax) sqrMax = x i += 1 } count += len } // inNode connect squared // inNode connect squared.gain // squared connect analyze // THIS IS NEEDED FOR CHROME // XXX TODO --- look into Tone.js, they // call some GC-prevention function that might serve the same purpose. val dummy = context.createGain() dummy.gain.value = 0.0 analyze connect dummy dummy connect context.destination // inNode analyze } private var animHandle: SetIntervalHandle = null private def startAnimation(): Unit = { stopAnimation() animHandle = js.timers.setInterval(33.3)(animStep _) } private val ampdbFactor = 20 / js.Math.log(10) private def ampdb(in: Double): Double = js.Math.log(in) * ampdbFactor private var lastPeakPx = 0.0 private var lastRMSPx = 0.0 // private var paintCount = 0 private def animStep(): Unit = { val peakDB = ampdb(peak) val floorDB = -48 val peakNorm = peakDB / -floorDB + 1 val rmsDB = ampdb(rms) val rmsNorm = rmsDB / -floorDB + 1 val elem = render // paintCount = (paintCount + 1) % 20 // if (paintCount == 0) println(f"peak $peakDB%1.1f rms $rmsDB%1.1f sqrSum $sqrSum%1.2f count $count") reset() val w = elem.width val h = elem.height val px0 = js.Math.max(0, js.Math.min(w, peakNorm * w)) val rx0 = js.Math.max(0, js.Math.min(w, rmsNorm * w)) val px = js.Math.max(lastPeakPx - 4, px0) val rx = js.Math.max(lastRMSPx - 4, rx0) if (lastPeakPx != px || lastRMSPx != rx) { lastPeakPx = px lastRMSPx = rx val ctx = elem.getContext("2d").asInstanceOf[CanvasRenderingContext2D] ctx.fillStyle = "#000000" ctx.fillRect(0, 0, w , h) ctx.fillStyle = "#FF0000" ctx.fillRect(0, 0, px, h) ctx.fillStyle = "#0000FF" ctx.fillRect(0, 0, rx, h) } } private def stopAnimation(): Unit = { if (animHandle != null) { js.timers.clearInterval(animHandle) animHandle = null } } }
Sciss/Cord
src/main/scala/de/sciss/cord/incomplete/Meter.scala
Scala
lgpl-2.1
3,611
/** * Copyright (c) 2016 LIBBLE team supervised by Dr. Wu-Jun LI at Nanjing University. * All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package libble.generalizedLinear import libble.linalg.{DenseVector, Vector} import libble.linalg.implicits._ /** * In this class, you should give your own gradient of function. * We give some instances of different losses. * If you want to run optimization on your own function, you should extend * this class, and override functions. */ abstract class LossFunc extends Serializable { /** * The gradient of a convex function is obtained by a deltafactor*x (where x is the data point). * Here, we return this gradient factor. * * @param data * @param label * @param weights * @return delta factor * */ def deltaF(data: Vector, label: Double, weights: WeightsVector): Vector def deltaF(data: Vector, label: Double, weights: Vector): Vector /** * Here we return the gradient factor and loss. * * @param data * @param label * @param weights * @return delta cumulate to cum,and loss */ def deltaFWithLoss(data: Vector, label: Double, weights: Vector): (Vector, Double) /** * Give the prediction on data with the weights. * * @param data * @param weights * @return predict Result */ def predict(data: Vector, weights: Vector): Double def log1pExp(x: Double): Double = { if (x > 0) { x + math.log1p(math.exp(-x)) } else { math.log1p(math.exp(x)) } } } /** * ******************Codes bellow has reference to mllib.optimization._ */ /** * Here we defined the logistic Loss. * * @param classNum */ class LogisticLoss(classNum: Int) extends LossFunc { def this() = this(2) /** * The gradient of a convex function is obtained by a deltafactor*x (where x is the data point). * Here, we return this gradient factor. * * @param data * @param label * @param weights * @return delta factor * */ override def deltaF(data: Vector, label: Double, weights: WeightsVector): Vector = { require((data.size % weights.size) == 0 || classNum == (weights.size / data.size + 1), "weights size not match!!!") classNum match { case 2 => { val margin = -1.0 * (weights * data) val factor = (1.0 / (1.0 + math.exp(margin))) - label new DenseVector(Array(factor)) } case _ => { val dim = data.size var marginY = 0.0 var maxIndex = 0 var maxMargin = Double.NegativeInfinity val margins = Array.tabulate(classNum - 1) { p => var tMargin = 0.0 data.foreachActive((i, v) => { if (v != 0) { tMargin += v * weights(p * dim + i) } }) if (p == (label - 1)) marginY = tMargin if (tMargin > maxMargin) { maxIndex = p maxMargin = tMargin } tMargin } val sum = { var temp = 0.0 if (maxMargin > 0) { for (i <- 0 until classNum - 1) { margins(i) -= maxMargin if (i == maxIndex) { temp += math.exp(-maxMargin) } else { temp += math.exp(margins(i)) } } } else { for (i <- 0 until classNum - 1) { temp += math.exp(margins(i)) } } temp } val deltaFactor = new Array[Double](classNum - 1) for (i <- 0 until classNum - 1) { val la = { if (label != 0.0 && label == i + 1) 1.0 else 0.0 } deltaFactor(i) = math.exp(margins(i)) / (sum + 1.0) - la } new DenseVector(deltaFactor) } } } def deltaF(data: Vector, label: Double, weights: Vector): Vector= { require((data.size % weights.size) == 0 || classNum == (weights.size / data.size + 1), "weights size not match!!!") classNum match { case 2 => { val margin = -1.0 * (weights * data) val factor = (1.0 / (1.0 + math.exp(margin))) - label new DenseVector(Array(factor)) } case _ => { val dim = data.size var marginY = 0.0 var maxIndex = 0 var maxMargin = Double.NegativeInfinity val margins = Array.tabulate(classNum - 1) { p => var tMargin = 0.0 data.foreachActive((i, v) => { if (v != 0) { tMargin += v * weights(p * dim + i) } }) if (p == (label - 1)) marginY = tMargin if (tMargin > maxMargin) { maxIndex = p maxMargin = tMargin } tMargin } val sum = { var temp = 0.0 if (maxMargin > 0) { for (i <- 0 until classNum - 1) { margins(i) -= maxMargin if (i == maxIndex) { temp += math.exp(-maxMargin) } else { temp += math.exp(margins(i)) } } } else { for (i <- 0 until classNum - 1) { temp += math.exp(margins(i)) } } temp } val deltaFactor = new Array[Double](classNum - 1) for (i <- 0 until classNum - 1) { val la = { if (label != 0.0 && label == i + 1) 1.0 else 0.0 } deltaFactor(i) = math.exp(margins(i)) / (sum + 1.0) - la } new DenseVector(deltaFactor) } } } /** * Here we return the gradient factor and loss. * * @param data * @param label * @param weights * @return delta fator,and loss */ override def deltaFWithLoss(data: Vector, label: Double, weights: Vector): (Vector, Double) = { require((data.size % weights.size) == 0 || classNum == (weights.size / data.size + 1), "weights size not match!!!") classNum match { case 2 => { val margin = -1.0 * (data * weights) val factor = (1.0 / (1.0 + math.exp(margin))) - label if (label > 0) { (new DenseVector(Array(factor)), log1pExp(margin)) } else { (new DenseVector(Array(factor)), log1pExp(margin) - margin) } } case _ => { val dim = data.size var marginY = 0.0 var maxIndex = 0 var maxMargin = Double.NegativeInfinity val margins = Array.tabulate(classNum - 1) { p => var tMargin = 0.0 data.foreachActive((i, v) => { if (v != 0.0) { tMargin += v * weights(p * dim + i) } }) if (p == (label - 1)) marginY = tMargin if (tMargin > maxMargin) { maxIndex = p maxMargin = tMargin } tMargin } val sum = { var temp = 0.0 if (maxMargin > 0) { for (i <- 0 until classNum - 1) { margins(i) -= maxMargin if (i == maxIndex) { temp += math.exp(-maxMargin) } else { temp += math.exp(margins(i)) } } } else { for (i <- 0 until classNum - 1) { temp += math.exp(margins(i)) } } temp } val deltaFactor = new Array[Double](classNum - 1) for (i <- 0 until classNum - 1) { val la = { if (label != 0.0 && label == i + 1) 1.0 else 0.0 } deltaFactor(i) = math.exp(margins(i)) / (sum + 1.0) - la } var loss = { if (label > 0.0) { math.log1p(sum) - marginY } else { math.log1p(sum) } } if (maxMargin > 0) { loss += maxMargin } (new DenseVector(deltaFactor), loss) } } } /** * Give the prediction on data with the weights. * * @param data * @param weights * @return predict Result */ override def predict(data: Vector, weights: Vector): Double = { require((data.size % weights.size) == 0 || classNum == (weights.size / data.size + 1), "weights size not match!!!") classNum match { case 2 => val margin = -(data * weights) 1.0 / log1pExp(margin) case _ => var maxMargin = 0.0 var softMax = 0 val dataSize = data.size for (p <- 0 until classNum) { var margin = 0.0 data.foreachActive((i, v) => margin += v * weights(p * dataSize + i) ) if (margin > maxMargin) { maxMargin = margin softMax = p } } softMax } } } /** * Here we defined the hinge Loss */ class HingeLoss extends LossFunc { /** * The gradient of a convex function is obtained by a deltafactor*x (where x is the data point). * Here, we return this gradient factor. * * @param data * @param label * @param weights * @return delta factor * */ override def deltaF(data: Vector, label: Double, weights: WeightsVector): Vector = { val innerP = weights * data val factor = 2 * label - 1.0 if (1.0 > factor * innerP) { new DenseVector(Array(-factor)) } else { new DenseVector(1) } } override def deltaF(data: Vector, label: Double, weights: Vector): Vector = { val innerP = weights * data val factor = 2 * label - 1.0 if (1.0 > factor * innerP) { new DenseVector(Array(-factor)) } else { new DenseVector(1) } } /** * Here we return the gradient factor and loss. * * @param data * @param label * @param weights * @return delta cumulate to cum,and loss */ override def deltaFWithLoss(data: Vector, label: Double, weights: Vector): (Vector, Double) = { val innerP = weights * data val factor = 2 * label - 1.0 if (1.0 > factor * innerP) { (new DenseVector(Array(-factor)), 1.0 - factor * innerP) } else { (new DenseVector(1), 0.0) } } /** * Give the prediction on data with the weights * * @param data * @param weights * @return predict Result */ override def predict(data: Vector, weights: Vector): Double = { weights * data } } /** * Here we defined the least square Loss. */ class LeastSquareLoss extends LossFunc { /** * The gradient of a convex function is obtained by a deltafactor*x (where x is the data point). * Here, we return this gradient factor. * * @param data * @param label * @param weights * @return delta factor * */ override def deltaF(data: Vector, label: Double, weights: WeightsVector): Vector = { new DenseVector(Array(weights * data - label)) } override def deltaF(data: Vector, label: Double, weights: Vector): Vector = { new DenseVector(Array(weights * data - label)) } /** * Here we return the gradient factor and loss. * * @param data * @param label * @param weights * @return delta cumulate to cum,and loss */ override def deltaFWithLoss(data: Vector, label: Double, weights: Vector): (Vector, Double) = { val deltaF = weights * data - label (new DenseVector(Array(deltaF)), deltaF * deltaF / 2.0) } /** * Give the prediction on data with the weights. * * @param data * @param weights * @return predict Result */ override def predict(data: Vector, weights: Vector): Double = { data * weights } } /** ***********************************************************************************/
syh6585/LIBBLE-Spark
src/main/scala/generalizedLinear/LossFunc.scala
Scala
apache-2.0
12,435
package smt.report import smt.{UpMoveState, DownMoveState, MoveState} object MoveStateDescription { def describe(nms: MoveState): String = nms match { case dms: DownMoveState => { dms.crashedDown match { case None => "rolled back." case Some(s) => "roll-back attempted, but crashed at: " + s.name } } case ums: UpMoveState => { ums.crashedUp match { case None => "applied." case Some(s) => "attempted, but crashed at: " + s.name } } } def describe(name: String, nms: MoveState): String = name + ": " + describe(nms) }
davidpeklak/smt
src/main/scala/smt/report/MoveStateDescription.scala
Scala
mit
598
import edu.uta.diql._ import org.apache.spark._ import org.apache.spark.rdd._ object Test { def main ( args: Array[String] ) { val conf = new SparkConf().setAppName("Test") val sc = new SparkContext(conf) explain(true) var M = sc.textFile(args(0)) .map( line => { val a = line.split(",") ((a(0).toInt,a(1).toInt),a(2).toDouble) } ) var N = sc.textFile(args(1)) .map( line => { val a = line.split(",") ((a(0).toInt,a(1).toInt),a(2).toDouble) } ) M.map{ case ((i,j),m) => (j,(i,m)) } .join( N.map{ case ((i,j),n) => (i,(j,n)) } ) .map{ case (k,((i,m),(j,n))) => ((i,j),m*n) } .reduceByKey(_+_) .sortBy(_._1,true,1).take(30).foreach(println) } }
fegaras/DIQL
tests/diablo/spark/MatrixMultiplicationSpark.scala
Scala
apache-2.0
785
package org.json4s package native import org.scalatest.wordspec.AnyWordSpec import org.json4s.prefs.EmptyValueStrategy import org.json4s.MonadicJValue._ class NativeJsonMethodsSpec extends AnyWordSpec { import org.json4s.JsonDSL._ import JsonMethods._ "JsonMethods.parse" should { val stringJson = """{"number": 200}""" "parse StringInput and produce JInt" in { assert((parse(stringJson) \\ "number").isInstanceOf[JInt]) } "parse ReaderInput and produce JInt" in { assert((parse(new java.io.StringReader(stringJson)) \\ "number").isInstanceOf[JInt]) } "parse StreamInput and produce JInt" in { assert((parse(new java.io.ByteArrayInputStream(stringJson.getBytes)) \\ "number").isInstanceOf[JInt]) } "parse StringInput and produce JLong" in { assert((parse(stringJson, useBigIntForLong = false) \\ "number").isInstanceOf[JLong]) } "parse ReaderInput and produce JLong" in { assert((parse(new java.io.StringReader(stringJson), useBigIntForLong = false) \\ "number").isInstanceOf[JLong]) } "parse StreamInput and produce AST using Long" in { assert( (parse( new java.io.ByteArrayInputStream(stringJson.getBytes), useBigIntForLong = false ) \\ "number").isInstanceOf[JLong] ) } } "JsonMethods.write" should { "produce JSON without empty fields" should { "from Seq(Some(1), None, None, Some(2))" in { val seq = Seq(Some(1), None, None, Some(2)) val expected = DocCons(DocText("["), DocCons(DocCons(DocText("1"), DocCons(DocText(","), DocText("2"))), DocText("]"))) assert(render(seq) == expected) } """from Map("a" -> Some(1), "b" -> None, "c" -> None, "d" -> Some(2))""" in { val map = Map("a" -> Some(1), "b" -> None, "c" -> None, "d" -> Some(2)) val expected = DocCons( DocText("{"), DocCons( DocNest( 2, DocCons( DocBreak, DocCons( DocCons(DocText("\\"a\\":"), DocText("1")), DocCons(DocCons(DocText(","), DocBreak), DocCons(DocText("\\"d\\":"), DocText("2"))) ) ) ), DocCons(DocBreak, DocText("}")) ) ) assert(render(map) == expected) } } "produce JSON with empty fields preserved" should { "from Seq(Some(1), None, None, Some(2))" in { val seq = Seq(Some(1), None, None, Some(2)) val expected = DocCons( DocText("["), DocCons( DocCons( DocCons( DocCons(DocText("1"), DocCons(DocText(","), DocText("null"))), DocCons(DocText(","), DocText("null")) ), DocCons(DocText(","), DocText("2")) ), DocText("]") ) ) assert(render(seq, emptyValueStrategy = EmptyValueStrategy.preserve) == expected) } """from Map("a" -> Some(1), "b" -> None, "c" -> None, "d" -> Some(2))""" in { val map = Map("a" -> Some(1), "b" -> None, "c" -> None, "d" -> Some(2)) val expected = DocCons( DocText("{"), DocCons( DocNest( 2, DocCons( DocBreak, DocCons( DocCons( DocCons( DocCons(DocText("\\"a\\":"), DocText("1")), DocCons(DocCons(DocText(","), DocBreak), DocCons(DocText("\\"b\\":"), DocText("null"))) ), DocCons(DocCons(DocText(","), DocBreak), DocCons(DocText("\\"c\\":"), DocText("null"))) ), DocCons(DocCons(DocText(","), DocBreak), DocCons(DocText("\\"d\\":"), DocText("2"))) ) ) ), DocCons(DocBreak, DocText("}")) ) ) assert(render(map, emptyValueStrategy = EmptyValueStrategy.preserve) == expected) } } } }
xuwei-k/json4s
native-core/shared/src/test/scala/org/json4s/native/NativeJsonMethodsSpec.scala
Scala
apache-2.0
4,073
/* * Copyright 2016 Carlo Micieli * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package io.hascalator.benchmarks package lists import io.hascalator.Prelude._ import org.openjdk.jmh.annotations.{ Benchmark, BenchmarkMode, Mode, OutputTimeUnit } import java.util.concurrent.TimeUnit class FoldBenchmarks { import BenchmarkState.sample._ @Benchmark @BenchmarkMode(Array(Mode.Throughput)) @OutputTimeUnit(TimeUnit.SECONDS) def foldLeftListBenchmark(): Int = { list.foldLeft(0)(_ + _) } @Benchmark @BenchmarkMode(Array(Mode.Throughput)) @OutputTimeUnit(TimeUnit.SECONDS) def foldLeftScalaListBenchmark(): Int = { scalaList.foldLeft(0)(_ + _) } @Benchmark @BenchmarkMode(Array(Mode.Throughput)) @OutputTimeUnit(TimeUnit.SECONDS) def foldLeftArrayBenchmark(): Int = { array.foldLeft(0)(_ + _) } @Benchmark @BenchmarkMode(Array(Mode.Throughput)) @OutputTimeUnit(TimeUnit.SECONDS) def foldRightListBenchmark(): Int = { list.foldRight(0)(_ + _) } @Benchmark @BenchmarkMode(Array(Mode.Throughput)) @OutputTimeUnit(TimeUnit.SECONDS) def foldRightScalaListBenchmark(): Int = { scalaList.foldRight(0)(_ + _) } @Benchmark @BenchmarkMode(Array(Mode.Throughput)) @OutputTimeUnit(TimeUnit.SECONDS) def foldRightArrayBenchmark(): Int = { array.foldRight(0)(_ + _) } }
CarloMicieli/hascalator
bench/src/main/scala/io/hascalator/benchmarks/lists/FoldBenchmarks.scala
Scala
apache-2.0
1,836
package org.jetbrains.plugins.scala package script import com.intellij.execution.configurations._ import com.intellij.execution.filters._ import com.intellij.openapi.project.Project import com.intellij.psi.{PsiElement, PsiManager} import com.intellij.openapi.vfs.VirtualFile import com.intellij.openapi.util.JDOMExternalizer import com.intellij.execution.runners.ExecutionEnvironment import com.intellij.execution.{ExecutionException, Executor} import com.intellij.openapi.module.{ModuleUtilCore, Module} import com.intellij.openapi.options.SettingsEditor import lang.psi.api.ScalaFile import com.intellij.vcsUtil.VcsUtil import org.jdom.Element import collection.JavaConversions._ import compiler.ScalacSettings import config.{Libraries, CompilerLibraryData, ScalaFacet} import com.intellij.refactoring.listeners.{RefactoringElementAdapter, RefactoringElementListener} /** * User: Alexander Podkhalyuzin * Date: 04.02.2009 */ class ScalaScriptRunConfiguration(val project: Project, val configurationFactory: ConfigurationFactory, val name: String) extends ModuleBasedConfiguration[RunConfigurationModule](name, new RunConfigurationModule(project), configurationFactory) with RefactoringListenerProvider { val SCALA_HOME = "-Dscala.home=" val CLASSPATH = "-Denv.classpath=\\"%CLASSPATH%\\"" val EMACS = "-Denv.emacs=\\"%EMACS%\\"" val MAIN_CLASS = "scala.tools.nsc.MainGenericRunner" private var scriptPath = "" private var scriptArgs = "" private var javaOptions = "" private var consoleArgs = "" private var workingDirectory = { val base = getProject.getBaseDir if (base != null) base.getPath else "" } def getScriptPath = scriptPath def getScriptArgs = scriptArgs def getJavaOptions = javaOptions def getConsoleArgs = consoleArgs def getWorkingDirectory: String = workingDirectory def setScriptPath(s: String) { scriptPath = s } def setScriptArgs(s: String) { scriptArgs = s } def setJavaOptions(s: String) { javaOptions = s } def setConsoleArgs(s: String) { consoleArgs = s } def setWorkingDirectory(s: String) { workingDirectory = s } def apply(params: ScalaScriptRunConfigurationForm) { setScriptArgs(params.getScriptArgs) setScriptPath(params.getScriptPath) setJavaOptions(params.getJavaOptions) setConsoleArgs(params.getConsoleArgs) setWorkingDirectory(params.getWorkingDirectory) } def getState(executor: Executor, env: ExecutionEnvironment): RunProfileState = { def fileNotFoundError() { throw new ExecutionException("Scala script file not found.") } try { val file: VirtualFile = VcsUtil.getVirtualFile(scriptPath) PsiManager.getInstance(project).findFile(file) match { case f: ScalaFile if f.isScriptFile() && !f.isWorksheetFile => case _ => fileNotFoundError() } } catch { case e: Exception => fileNotFoundError() } val module = getModule if (module == null) throw new ExecutionException("Module is not specified") val script = VcsUtil.getVirtualFile(scriptPath) val state = new JavaCommandLineState(env) { protected override def createJavaParameters: JavaParameters = { val params = new JavaParameters() params.setCharset(null) params.getVMParametersList.addParametersString(getJavaOptions) params.setWorkingDirectory(getWorkingDirectory) // params.getVMParametersList.addParametersString("-Xnoagent -Djava.compiler=NONE -Xdebug -Xrunjdwp:transport=dt_socket,server=y,suspend=y,address=5009") // params.getVMParametersList.add(SCALA_HOME + scalaSdkPath) params.getVMParametersList.add(CLASSPATH) params.getVMParametersList.add(EMACS) params.setMainClass(MAIN_CLASS) params.getProgramParametersList.add("-nocompdaemon") //todo: seems to be a bug in scala compiler. Ticket #1498 params.getProgramParametersList.add("-classpath") params.configureByModule(module, JavaParameters.JDK_AND_CLASSES_AND_TESTS) params.getProgramParametersList.add(params.getClassPath.getPathsString) ScalaFacet.findIn(module).foreach { case facet => val files = if (facet.fsc) { val settings = ScalacSettings.getInstance(getProject) val lib: Option[CompilerLibraryData] = Libraries.findBy(settings.COMPILER_LIBRARY_NAME, settings.COMPILER_LIBRARY_LEVEL, getProject) lib match { case Some(libr) => libr.files case _ => facet.files } } else facet.files files.foreach(params.getClassPath.add) } val array = getConsoleArgs.trim.split("\\\\s+").filter(!_.trim().isEmpty) params.getProgramParametersList.addAll(array: _*) params.getProgramParametersList.add(scriptPath) params.getProgramParametersList.addParametersString(scriptArgs) params } } val consoleBuilder = TextConsoleBuilderFactory.getInstance.createBuilder(getProject) consoleBuilder.addFilter(getFilter(script)) state.setConsoleBuilder(consoleBuilder) state } def getModule: Module = { var module: Module = null try { val file: VirtualFile = VcsUtil.getVirtualFile(scriptPath) module = ModuleUtilCore.findModuleForFile(file, getProject) } catch { case e: Exception => } if (module == null) module = getConfigurationModule.getModule module } def getValidModules: java.util.List[Module] = ScalaFacet.findModulesIn(getProject).toList def getConfigurationEditor: SettingsEditor[_ <: RunConfiguration] = new ScalaScriptRunConfigurationEditor(project, this) override def writeExternal(element: Element) { super.writeExternal(element) writeModule(element) JDOMExternalizer.write(element, "path", getScriptPath) JDOMExternalizer.write(element, "vmparams", getJavaOptions) JDOMExternalizer.write(element, "consoleargs", getConsoleArgs) JDOMExternalizer.write(element, "params", getScriptArgs) JDOMExternalizer.write(element, "workingDirectory", workingDirectory) } override def readExternal(element: Element) { super.readExternal(element) readModule(element) scriptPath = JDOMExternalizer.readString(element, "path") javaOptions = JDOMExternalizer.readString(element, "vmparams") scriptArgs = JDOMExternalizer.readString(element, "params") consoleArgs = JDOMExternalizer.readString(element, "consoleargs") val pp = JDOMExternalizer.readString(element, "workingDirectory") if (pp != null) workingDirectory = pp } private def getFilter(file: VirtualFile): Filter = { import Filter._ new Filter { def applyFilter(line: String, entireLength: Int): Result = { val start = entireLength - line.length var end = entireLength - line.length if (line.startsWith("(fragment of ")) { try { var cache = line.replaceFirst("[(][f][r][a][g][m][e][n][t][ ][o][f][ ]", "") cache = cache.replaceFirst("[^)]*[)][:]", "") val lineNumber = Integer.parseInt(cache.substring(0, cache.indexOf(":"))) cache = cache.replaceFirst("[^:]", "") end += line.length - cache.length val hyperlink = new OpenFileHyperlinkInfo(getProject, file, lineNumber-1) new Result(start, end, hyperlink) } catch { case _: Exception => return null } } else null } } } def getRefactoringElementListener(element: PsiElement): RefactoringElementListener = element match { case file: ScalaFile => new RefactoringElementAdapter { def elementRenamedOrMoved(newElement: PsiElement) = { newElement match { case f: ScalaFile => val newPath = f.getVirtualFile.getPath setScriptPath(newPath) case _ => } } //todo this method does not called when undo of moving action executed def undoElementMovedOrRenamed(newElement: PsiElement, oldQualifiedName: String) { setScriptPath(oldQualifiedName) } } case _ => RefactoringElementListener.DEAF } }
consulo/consulo-scala
src/org/jetbrains/plugins/scala/script/ScalaScriptRunConfiguration.scala
Scala
apache-2.0
8,237
package pl.umk.bugclassification.scmparser.training import java.util import java.util.ArrayList import org.slf4j.LoggerFactory import weka.classifiers.Classifier import weka.core.{Attribute, DenseInstance, FastVector, Instance, Instances} import scala.collection.mutable.ArrayBuilder.ofDouble trait WekaWrapper { val log = LoggerFactory.getLogger(classOf[WekaWrapper]) def generateAttributes(keys: Array[String]): (ArrayList[Attribute], Double, Double) = { log.info("generateAttributes before creation of attributes") val attributes: util.ArrayList[Attribute] = new util.ArrayList[Attribute] keys.foreach(key => attributes.add(new Attribute(key))) val classificationAttributeValues = new util.ArrayList[String] classificationAttributeValues.add("buggy") classificationAttributeValues.add("clean") val classificationAttribute = new Attribute("WekaWrapperClassification", classificationAttributeValues) attributes.add(classificationAttribute) log.info("generateAttributes after creation of attributes") (attributes, classificationAttributeValues.indexOf("buggy").toDouble, classificationAttributeValues.indexOf("clean").toDouble) } def generateInstances(bags: List[ClassifiedBagOfWords], keys: Array[String]): Instances = { val (attributes, buggyValue, cleanValue) = generateAttributes(keys) log.info("generateInstances before createTrainingInstance for each instance ") val instances = new Instances("Training", attributes, 0) bags.par. map(bag => createTrainingInstance(bag, keys, buggyValue, cleanValue)).seq. foreach(instance => instances.add(instance)) instances.setClassIndex(instances.numAttributes() - 1) log.info("generateInstances after createTrainingInstance for each instance ") instances } private def populateValues(bag: BagOfWords, keys: Array[String]): ofDouble = { val bagParMap = bag.map.par val arrayBuilderOfDouble = new ofDouble() arrayBuilderOfDouble.sizeHint(keys.size) var i = 0 while (i < keys.size) { arrayBuilderOfDouble += bagParMap.get(keys(i)).orElse(Some(0)).get.toDouble i += 1 } arrayBuilderOfDouble } def createTrainingInstance(bag: ClassifiedBagOfWords, keys: Array[String], buggyValue: Double, cleanValue: Double): Instance = { val b = populateValues(bag, keys) if (bag.isBug) { b += buggyValue } else { b += cleanValue } val values = b.result val instance = new DenseInstance(1.0, values) instance } def createClassificationInstances(bag: BagOfWords, keys: Array[String]): Instances = { val attributes = generateAttributes(keys) val values = (populateValues(bag, keys) += 0).result val instance = new DenseInstance(1.0, values) val instances = new Instances("Classification", attributes._1, 0) instances.setClassIndex(instances.numAttributes() - 1) instances.add(instance) instances } def train(instances: Instances) def saveModel: Classifier def printEvaluation(instances: Instances) }
mfejzer/CommitClassification
src/main/scala/pl/umk/bugclassification/scmparser/training/WekaWrapper.scala
Scala
bsd-3-clause
3,060
package unluac.parse import java.nio.ByteBuffer class LBooleanType extends BObjectType[LBoolean] { def parse(buffer: ByteBuffer, header: BHeader): LBoolean = { val value: Int = buffer.get if ((value & 0xFFFFFFFE) != 0) { throw new IllegalStateException } else { val bool: LBoolean = if (value == 0) LBoolean.LFALSE else LBoolean.LTRUE if (header.debug) { System.out.println("-- parsed <boolean> " + bool) } bool } } }
danielwegener/unluac-scala
shared/src/main/scala/unluac/parse/LBooleanType.scala
Scala
mit
482
/* * Copyright 2017 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package uk.gov.hmrc.ct.accounts.frs10x.boxes import org.mockito.Mockito._ import org.scalatest.BeforeAndAfterEach import uk.gov.hmrc.ct.accounts.AccountStatementValidationFixture import uk.gov.hmrc.ct.accounts.frs10x.retriever.Frs10xDormancyBoxRetriever class ACQ8990Spec extends AccountStatementValidationFixture[Frs10xDormancyBoxRetriever] with BeforeAndAfterEach { override val boxRetriever = mock[Frs10xDormancyBoxRetriever] (RETURNS_SMART_NULLS) override def setupMocks() = { when(boxRetriever.profitAndLossStatementRequired()).thenReturn(ProfitAndLossStatementRequired(true)) } doStatementValidationTests("ACQ8990", ACQ8990.apply) "ACQ8990 should" should { "validate successfully when not set and notTradedStatementRequired false" in { when(boxRetriever.profitAndLossStatementRequired()).thenReturn(ProfitAndLossStatementRequired(false)) ACQ8990(None).validate(boxRetriever) shouldBe Set.empty } } }
pncampbell/ct-calculations
src/test/scala/uk/gov/hmrc/ct/accounts/frs10x/boxes/ACQ8990Spec.scala
Scala
apache-2.0
1,554
/* * Copyright 2015 Ark International Group * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package spream import scala.reflect.ClassTag import scala.collection.mutable import org.apache.spark.rdd._ import org.apache.spark.{RangePartitioning, Partitioner} object PartitionLocation { sealed trait EnumVal case object Past extends EnumVal case object Current extends EnumVal case object Future extends EnumVal } /** * Given a series indexed by K, it can be parallelised across partitions to a series indexed by PartitionedSeriesKey[K]. * @param partition the id of the partition containing this. This is used to implement efficient partitioning and * probably should not be used by client code. * @param key the underlying key for the series. * @param location whether key is part of this current partition, or duplicated from a * previous (past) or subsequent (future) partition in order to allow moving window computations. * @tparam K */ case class PartitionedSeriesKey[K : Ordering : Numeric : ClassTag](partition : Int, key : K, location : PartitionLocation.EnumVal) object PartitionedSeriesKey { implicit def ordering[K : Ordering] : Ordering[PartitionedSeriesKey[K]] = Ordering.by(x => (x.partition,x.key)) } //TODO write this like PairRDDFunctions and have an implicit conversion, so can convert ordered RDDs to this easily. //TODO prevent the currently required type specification required when calling these functions (the above may help) //TODO type the resulting RDD, e.g. SeriesRDD //TODO implement faster ops on this, because we know it's a type of range partitioning so filtering can be made fast in the same way. //TODO consider writing this ias a subclass of RangePartitioner somehow (though note the duplication cannot be done by getPartition). /** * In order to parallelise moving window computations on series, it is necessary to duplicate data so that there * is an overlap between partitions. * Specifically, a partition p must have enough data from partition p-1 and possibly earlier (and p+1 and possibly * later) to fill the past (and future) windows. */ object MovingWindowPartitioning { type IntervalSets[K] = List[(Option[K],Set[(Int, PartitionLocation.EnumVal)])] /** * Given rangeBounds and desired past and future window widths, determine the (Past,Current,Future) labelling * that should be applied within each interval. * This allows efficient application of labeling. * @param rangeBounds must be sorted according to K * @param pastWindow * @param futureWindow * @return A list of (upper bound, labels), where labels are to be applied until the bound is hit. */ def intervalSets[K : Ordering : Numeric](rangeBounds : Array[K], pastWindow : K, futureWindow : K): IntervalSets[K] = { var numeric = implicitly[Numeric[K]] val Start = 's' val End = 'e' val allBounds = rangeBounds.zipWithIndex.flatMap{ case (ub,p) => (p,PartitionLocation.Current,End,ub) :: (p,PartitionLocation.Future,Start,ub) :: (p,PartitionLocation.Future,End,numeric.plus(ub,futureWindow)) :: (p+1,PartitionLocation.Past,Start,numeric.minus(ub,pastWindow)) :: (p+1,PartitionLocation.Past,End,ub) :: (p+1,PartitionLocation.Current,Start,ub) :: Nil : List[(Int,PartitionLocation.EnumVal,Char,K)] }.sortBy(_._4) type ACC = IntervalSets[K] val empty : ACC = Nil //Anything lower than first split is in "this" of first partition //We start with bound being lower val initial : ACC = (Option.empty[K],Set((0,PartitionLocation.Current : PartitionLocation.EnumVal))) :: Nil val intervalSets: ACC = allBounds.foldLeft(initial){ case (acc,(p,what,se,bound)) => val currBound = acc.head._1 val currSet = acc.head._2 val entry = (p,what) val ns = se match { case Start => currSet + entry case End => currSet - entry } //Note this reverses the list. if (currBound.map(_ == bound).getOrElse(false)) (Some(bound), ns) :: acc.tail else (Some(bound), ns) :: acc }.foldLeft((Option.empty[K],empty)){ //Note this reverses again. Here, we're making the bound upper, rather than lower. case ((prevBound,res),(bound,set)) => (bound,(prevBound,set) :: res) }._2 require(rangeBounds.size+1 <= intervalSets.size) intervalSets } //TODO can we enforce rdd ordered? /** * Applies duplication and labelling as defined by intervalSets in a streaming fashion over each partition. * @param rdd ordered by K * @param intervalSets * @return */ def duplicateToIntervals[K : Ordering : Numeric : ClassTag, V : ClassTag, P <: Product2[K,V] : ClassTag]( rdd: RDD[P], intervalSets : IntervalSets[K]): RDD[Product2[PartitionedSeriesKey[K], V]] = { def f(it : Iterator[P]) = new DuplicateToIntervalsIterator[K,V,P](it,intervalSets) rdd.mapPartitions(f,true) } /** * Apply the pre-computed partitioning. * @param rdd * @param rangeBounds used to pre-label partitions * @return */ def applyPartitioning[K : Ordering : Numeric : ClassTag, V : ClassTag, P <: Product2[PartitionedSeriesKey[K],V] : ClassTag]( rdd: RDD[P], rangeBounds : Array[K], ascending : Boolean): RDD[(PartitionedSeriesKey[K], V)] = { val f = new OrderedRDDFunctions[PartitionedSeriesKey[K], V, P](rdd) f.repartitionAndSortWithinPartitions(new PartitionedSeriesPartitioner(rangeBounds, ascending)) } /** * Convert an RDD of (K,V) ordered by K (a series) into an RDD with appropriate overlaps and labels to allow * moving window computations to be applied. Data is distributed roughly evenly across the resulting partitions. * @param rdd * @param pastWidth defines window width in which past events will be made available in each partition. * @param futureWidth * @param partitions number of partitions desired * @tparam K * @tparam V * @tparam P * @return */ def movingWindowPartitioned[K : Ordering : Numeric : ClassTag, V : ClassTag, P <: Product2[K,V] : ClassTag]( rdd: RDD[P], pastWidth : K, futureWidth : K, partitions : Int): RDD[(PartitionedSeriesKey[K], V)] = { val rb = RangePartitioning.rangeBounds[K,V](rdd,partitions) val is = intervalSets(rb,pastWidth,futureWidth) val d = duplicateToIntervals[K,V,P](rdd,is) applyPartitioning(d,rb,true) } } //TODO extend sRangPartitioner, and if not PartitionedSeriesKey, delegate to that... should work ?? class PartitionedSeriesPartitioner[K : Ordering : ClassTag](val rangeBounds : Array[K], val ascending : Boolean) extends Partitioner { //RangePartitioner[K,Unit](rangeBounds.length+1,null,true) { require(ascending,"Only ascending is completely supported at this stage") private var ordering = implicitly[Ordering[K]] override def numPartitions: Int = rangeBounds.length + 1 // These are used to filter by range def getPartitionTypesafe(key: K): Int = doGetPartition(key) def getPartitionTypesafe(key: PartitionedSeriesKey[K]): Int = key.partition // Used to perform partitioning. No control over the API to improve this... override def getPartition(key: Any): Int = getPartitionTypesafe(key.asInstanceOf[PartitionedSeriesKey[K]]) private var binarySearch: ((Array[K], K) => Int) = org.apache.spark.util.CollectionsUtils.makeBinarySearch[K] // Unfortunately RangePartitioner isn't written in a way where you can inherit from it, so the following // is almost a cut-and-paste of functionality there. private def doGetPartition(k: K): Int = { var partition = 0 if (rangeBounds.length <= 128) { // If we have less than 128 partitions naive search while (partition < rangeBounds.length && ordering.gt(k, rangeBounds(partition))) { partition += 1 } } else { // Determine which binary search method to use only once. partition = binarySearch(rangeBounds, k) // binarySearch either returns the match location or -[insertion point]-1 if (partition < 0) { partition = -partition-1 } if (partition > rangeBounds.length) { partition = rangeBounds.length } } if (ascending) { partition } else { rangeBounds.length - partition } } } /** * Applies interval mapping in a streaming fashion. * @param it * @param intervalSets * @tparam K * @tparam V * @tparam P */ class DuplicateToIntervalsIterator[K : Ordering : Numeric : ClassTag,V,P <: Product2[K,V] : ClassTag]( it : Iterator[P], intervalSets : List[(Option[K],Set[(Int, PartitionLocation.EnumVal)])]) extends Iterator[Product2[PartitionedSeriesKey[K],V]]() { private val ordering = implicitly[Ordering[K]] private val queue = new mutable.Queue[Product2[PartitionedSeriesKey[K],V]]() private val currentIntervals: mutable.Queue[(Option[K], Set[(Int, PartitionLocation.EnumVal)])] = mutable.Queue() ++ intervalSets private var prev : Option[P] = None //Only used to enforce ordering //Skip to correct interval for k (interval is closed below and open above). //In future, could be worth changing queue to an Array and then binary searching it to get to the initial location. //Note: Will probably make little difference in practice though as it will only happen once per partition. def skipTo(k : K) = while (currentIntervals.head._1.map(ordering.gteq(k, _)).getOrElse(false)) currentIntervals.dequeue() override def hasNext: Boolean = !queue.isEmpty || it.hasNext override def next() = { if (queue.isEmpty) { val n: P = it.next() require(prev.map(p => ordering.gteq(n._1,p._1)).getOrElse(true), "Out of order: "+ n._1 + " not >= " + prev.get._1) skipTo(n._1) // Assign n to all currently active intervals queue ++= currentIntervals.head._2.map{ case (partition,what) => (PartitionedSeriesKey(partition,n._1,what),n._2) } prev = Some(n) } queue.dequeue() } }
arkig/spream
src/main/scala/spream/MovingWindowPartitioning.scala
Scala
apache-2.0
10,584
package edu.osu.cse.groenkeb.logic trait Operator { def matches(op: Operator): Boolean override def toString(): String } trait Predicate extends Operator trait Quantifier extends Operator { def evaluate(domain: Domain, functor: Sentence => Boolean, arg: Sentence): Boolean } trait Connective extends Operator { def evaluate(functor: Sentence => Boolean, args: Sentence*): Boolean } abstract class UnaryConnective extends Connective abstract class BinaryConnective extends Connective case class NamedPredicate(val name: String) extends Predicate { require(name != IdentityPredicate.name) def matches(op: Operator) = op match { case NamedPredicate(this.name) => true case _ => false } override def toString = name } case class IdentityPredicate() extends Predicate { def matches(op: Operator) = op match { case IdentityPredicate() => true case _ => false } override def toString = IdentityPredicate.name } case class NullOp() extends Operator { def matches(op: Operator) = op match { case NullOp() => true case _ => false } override def toString() = "" } object IdentityPredicate { def name = "I" }
bgroenks96/PropLogic
core/src/main/scala/edu/osu/cse/groenkeb/logic/operator.scala
Scala
mit
1,169
package com.avsystem.scex package compiler import com.avsystem.scex.compiler.presentation.{CachingScexPresentationCompiler, ScexPresentationCompiler} /** * Created: 17-10-2013 * Author: ghik */ class DefaultScexCompiler(val settings: ScexSettings) extends ScexCompiler with ScexPresentationCompiler with ClassfileReusingScexCompiler with TemplateOptimizingScexCompiler with CachingScexCompiler with CachingScexPresentationCompiler with WeakReferenceWrappingScexCompiler
AVSystem/scex
scex-core/src/main/scala/com/avsystem/scex/compiler/DefaultScexCompiler.scala
Scala
mit
490