id stringlengths 36 36 | document stringlengths 3 3k | metadata stringlengths 23 69 | embeddings listlengths 384 384 |
|---|---|---|---|
a21bf0c9-a9d8-4a7c-aef4-9cce6bc400d7 | Restore from the incremental backup {#restore-from-the-incremental-backup}
This command restores the incremental backup into a new table,
data3
. Note that when an incremental backup is restored, the base backup is also included. Specify only the incremental backup when restoring:
sql
RESTORE TABLE data AS data3 ... | {"source_file": "backup.md"} | [
-0.09017294645309448,
-0.047178227454423904,
-0.026244834065437317,
0.01683354564011097,
0.030910415574908257,
-0.03811066597700119,
-0.013922109268605709,
-0.046584147959947586,
0.019460083916783333,
0.08921259641647339,
0.0704539492726326,
-0.012219532392919064,
0.10650555789470673,
-0.1... |
b6a8d077-42f0-4757-af92-10bfc36bd356 | Duplicating source data somewhere else {#duplicating-source-data-somewhere-else}
Often data that is ingested into ClickHouse is delivered through some sort of persistent queue, such as
Apache Kafka
. In this case it is possible to configure an additional set of subscribers that will read the same data stream while i... | {"source_file": "backup.md"} | [
-0.06976637244224548,
-0.061547014862298965,
-0.045187633484601974,
0.05137517675757408,
-0.0037521691992878914,
-0.08096811175346375,
-0.017896952107548714,
-0.02434232458472252,
0.04369210824370384,
0.053234297782182693,
-0.0017037641955539584,
0.05519780516624451,
0.046114299446344376,
... |
5f7ae13e-98d6-431c-9455-4539f6f76311 | The default value for both is true, so by default concurrent backup/restores are allowed.
When these settings are false on a cluster, only 1 backup/restore is allowed to run on a cluster at a time.
Configuring BACKUP/RESTORE to use an AzureBlobStorage Endpoint {#configuring-backuprestore-to-use-an-azureblobstorage-en... | {"source_file": "backup.md"} | [
0.04092180356383324,
-0.06423487514257431,
-0.05390992388129234,
0.06964097172021866,
-0.09016969799995422,
0.1045318990945816,
0.03554939478635788,
-0.05347927287220955,
-0.03836233541369438,
0.09594845026731491,
-0.03374509885907173,
-0.028311850503087044,
0.08488888293504715,
-0.0324676... |
b3cbd977-8094-4088-ad47-8ebb5a0115d5 | This feature ensures that the access control configuration of a ClickHouse cluster can be backed up and restored as part of the cluster's overall setup.
Note: This functionality only works for configurations managed through SQL commands (referred to as
"SQL-driven Access Control and Account Management"
). Access con... | {"source_file": "backup.md"} | [
-0.02261715568602085,
-0.05913877859711647,
-0.04381662607192993,
0.054249461740255356,
-0.03502849116921425,
0.015536661259829998,
0.06635070592164993,
-0.13589338958263397,
-0.03669506311416626,
-0.029645927250385284,
0.02429519034922123,
0.09637629985809326,
0.058730628341436386,
-0.086... |
1cdb22c3-ae06-4bd1-ab12-5b416ca1490e | description: 'When performing queries, ClickHouse uses different caches.'
sidebar_label: 'Caches'
sidebar_position: 65
slug: /operations/caches
title: 'Cache types'
keywords: ['cache']
doc_type: 'reference'
Cache types
When performing queries, ClickHouse uses different caches to speed up queries
and reduce the ne... | {"source_file": "caches.md"} | [
0.020645318552851677,
-0.049746621400117874,
-0.006340401247143745,
-0.015171178616583347,
-0.021237151697278023,
-0.09793957322835922,
0.027852896600961685,
-0.0191548690199852,
0.023983865976333618,
0.04561929032206535,
0.009343989193439484,
0.05126386508345604,
-0.03935961797833443,
-0.... |
f9bd7a10-947f-4e21-8f4c-ff1605947cbd | description: 'Documentation for highlight-next-line'
sidebar_label: 'External disks for storing data'
sidebar_position: 68
slug: /operations/storing-data
title: 'External disks for storing data'
doc_type: 'guide'
Data processed in ClickHouse is usually stored in the local file system of the
machine on which ClickH... | {"source_file": "storing-data.md"} | [
-0.009962862357497215,
-0.061663515865802765,
-0.10384803265333176,
0.005207079462707043,
-0.018557634204626083,
0.022793982177972794,
-0.02678842283785343,
0.006415096111595631,
0.031114233657717705,
0.08981026709079742,
0.02443579211831093,
0.04713602364063263,
0.10284028947353363,
-0.01... |
3962626b-681c-4a48-96e1-89d6a8b193e3 | is equal to the following configuration (from version
24.1
):
xml
<s3>
<type>object_storage</type>
<object_storage_type>s3</object_storage_type>
<metadata_type>local</metadata_type>
<endpoint>https://s3.eu-west-1.amazonaws.com/clickhouse-eu-west-1.clickhouse.com/data/</endpoint>
<use_environment_... | {"source_file": "storing-data.md"} | [
0.0022505728993564844,
-0.02216983772814274,
-0.1315307468175888,
-0.05686333030462265,
0.05344993993639946,
-0.037890177220106125,
-0.05250006169080734,
-0.043169181793928146,
0.04135869815945625,
-0.00243445485830307,
0.07055137306451797,
-0.03243233263492584,
0.03442378342151642,
-0.055... |
2206db57-df42-43d9-85a3-11ee549ceb5d | sql
CREATE TABLE test (a Int32, b String)
ENGINE = MergeTree() ORDER BY a
SETTINGS storage_policy = 's3';
You can also use
disk
instead of
storage_policy
. In this case it is not necessary
to have the
storage_policy
section in the configuration file, and a
disk
section is enough.
sql
CREATE TABLE test (a In... | {"source_file": "storing-data.md"} | [
0.03780202195048332,
-0.023583944886922836,
-0.07142627239227295,
0.047609541565179825,
-0.11451355367898941,
-0.04869135469198227,
0.03607850894331932,
0.04084131866693497,
-0.043300360441207886,
0.04573033004999161,
0.02370373159646988,
-0.0257034283131361,
0.0932614803314209,
-0.0343764... |
1bbc51ef-02b7-49c3-bab6-faceaa9aac59 | A combination of config-based configuration and sql-defined configuration is
also possible:
sql
ATTACH TABLE uk_price_paid UUID 'cf712b4f-2ca8-435c-ac23-c4393efe52f7'
(
price UInt32,
date Date,
postcode1 LowCardinality(String),
postcode2 LowCardinality(String),
type Enum8('other' = 0, 'terraced' ... | {"source_file": "storing-data.md"} | [
0.06585098803043365,
-0.06382040679454803,
-0.02631630189716816,
0.010131302289664745,
-0.10664766281843185,
-0.040336478501558304,
-0.007387929130345583,
0.028316350653767586,
-0.13615940511226654,
0.015724200755357742,
0.10629288107156754,
-0.11020273715257645,
0.028157895430922508,
-0.0... |
bbfdf9e7-567d-4d20-b59c-85365ab7806b | | Parameter | Description | Default Value ... | {"source_file": "storing-data.md"} | [
0.04249017685651779,
0.08142649382352829,
-0.06255344301462173,
0.007414470426738262,
-0.09843405336141586,
0.046565137803554535,
0.032099299132823944,
0.0641661211848259,
-0.0004241623100824654,
-0.05043478682637215,
0.03937699645757675,
-0.07939525693655014,
0.0021902478765696287,
-0.067... |
0c8e3096-d5d0-4e2b-9001-09864a2696cb | 10000
(10 seconds) |
|
request_timeout_ms
| Request timeout in milliseconds. ... | {"source_file": "storing-data.md"} | [
-0.03827250748872757,
-0.04299914464354515,
-0.11970482766628265,
-0.013262332417070866,
0.019922325387597084,
-0.024083446711301804,
-0.04482204467058182,
-0.008890585973858833,
0.043620165437459946,
0.026890337467193604,
0.00464872969314456,
0.03764094039797783,
0.08217000216245651,
-0.0... |
23ba5a17-f35b-425d-8f5f-13cab386945a | SSE-KMS encryption
. Empty string uses AWS managed S3 key. | - |
|
server_side_encryption_kms_encryption_context
| Encryption context header for SSE-KMS (used with
server_side_encryption_kms_key_id
). ... | {"source_file": "storing-data.md"} | [
-0.0500820018351078,
-0.0002903595450334251,
-0.0983923003077507,
0.029833273962140083,
-0.0038949314039200544,
-0.0027225168887525797,
0.009892962872982025,
0.01956789195537567,
0.04337024688720703,
0.004803103860467672,
-0.03008328378200531,
-0.004543911665678024,
0.10696656256914139,
-0... |
c5743f0f-3c9f-48ad-9dee-5f4cecc27eff | re2
syntax. Requires
storage_metadata_write_full_object_key
flag. Incompatible with
root path
in
endpoint
. Requires
key_compatibility_prefix
. | - |
|
key_compatibility_prefix
| Required with
key_template
. Specifies the previous
root path
from
e... | {"source_file": "storing-data.md"} | [
0.023761801421642303,
-0.04758802056312561,
-0.00295458035543561,
-0.0344030037522316,
0.01269579865038395,
-0.04999278113245964,
-0.06947055459022522,
0.04192875325679779,
-0.012538489885628223,
0.08820145577192307,
0.04675788804888725,
0.020302405580878258,
0.028373293578624725,
-0.04687... |
46af007a-c253-4221-b973-06b80833e3cd | Using Plain Storage {#plain-storage}
In
22.10
a new disk type
s3_plain
was introduced, which provides a write-once storage.
Configuration parameters for it are the same as for the
s3
disk type.
Unlike the
s3
disk type, it stores data as is. In other words,
instead of having randomly generated blob names, it ... | {"source_file": "storing-data.md"} | [
-0.02390718087553978,
-0.053972966969013214,
-0.059225473552942276,
0.02641345001757145,
0.016261832788586617,
-0.044212181121110916,
-0.0014343839138746262,
0.016995882615447044,
-0.021032113581895828,
0.008872087113559246,
0.11594521999359131,
0.05557282269001007,
0.11404392868280411,
-0... |
da61f0f6-db1e-4b8e-993b-cb0978f54bb8 | is equal to
xml
<s3_plain_rewritable>
<type>object_storage</type>
<object_storage_type>s3</object_storage_type>
<metadata_type>plain_rewritable</metadata_type>
<endpoint>https://s3.eu-west-1.amazonaws.com/clickhouse-eu-west-1.clickhouse.com/data/</endpoint>
<use_environment_credentials>1</use_envi... | {"source_file": "storing-data.md"} | [
0.009024010971188545,
-0.05643770471215248,
-0.1141892820596695,
-0.008749612607061863,
-0.03519352525472641,
0.02363784797489643,
-0.05013161897659302,
-0.015617629513144493,
-0.04043375328183174,
0.06233501434326172,
0.024436000734567642,
-0.02752726525068283,
0.0874130055308342,
-0.0031... |
b0db841a-444b-4e24-988c-d1dd4a12f1aa | Authentication parameters (the disk will try all available methods
and
Managed Identity Credential):
| Parameter | Description |
|---------------------|-----------------------------------------------------------------|
|
connection_string
| For authent... | {"source_file": "storing-data.md"} | [
-0.003581271506845951,
-0.0027518898714333773,
-0.11634565889835358,
0.02077854983508587,
-0.09752121567726135,
0.027827642858028412,
0.11036693304777145,
0.021624304354190826,
0.027522334828972816,
0.0852244570851326,
0.0191977359354496,
-0.07884427905082703,
0.14241142570972443,
0.010243... |
edf0a005-2cc9-4d3c-b02b-54f8749f1ae6 | Examples of working configurations can be found in integration tests directory (see e.g.
test_merge_tree_azure_blob_storage
or
test_azure_blob_storage_zero_copy_replication
).
:::note Zero-copy replication is not ready for production
Zero-copy replication is disabled by default in ClickHouse version 22.8 and highe... | {"source_file": "storing-data.md"} | [
0.017247168347239494,
-0.07604595273733139,
-0.05226880684494972,
0.01560608297586441,
-0.025081869214773178,
-0.02630719728767872,
-0.04593610763549805,
-0.04975924268364906,
-0.0013691309140995145,
0.1118711531162262,
0.06951228529214859,
0.005628633312880993,
0.10564734041690826,
0.0446... |
39f1c065-5800-4594-b794-7c466ecf1d5a | Required Parameters {#required-parameters-encrypted-disk}
| Parameter | Type | Description |
|------------|--------|----------------------------------------------------------------------... | {"source_file": "storing-data.md"} | [
0.0013258696999400854,
0.024724094197154045,
-0.13712641596794128,
-0.0209815576672554,
-0.07827235013246536,
-0.02358996495604515,
0.0460965633392334,
0.06730299443006516,
-0.035803623497486115,
-0.007224461529403925,
0.043601151555776596,
-0.08416007459163666,
0.10529059916734695,
-0.028... |
54538f12-49db-4b12-ab7b-cf7fe61f13b3 | Example of configuration for versions later or equal to 22.8:
xml
<clickhouse>
<storage_configuration>
<disks>
<s3>
<type>s3</type>
<endpoint>...</endpoint>
... s3 configuration ...
</s3>
<cache>
<type>cach... | {"source_file": "storing-data.md"} | [
0.03278345987200737,
-0.014108889736235142,
-0.05439480021595955,
-0.06262268126010895,
0.02954273670911789,
-0.019476210698485374,
-0.07960091531276703,
0.027294447645545006,
-0.018143748864531517,
0.01518682949244976,
0.06556158512830734,
0.09004688262939453,
0.004969719797372818,
-0.049... |
2bc8333e-f34e-43d7-a320-4fe6e3b5e473 | | Parameter | Type | Default | Description |
|---------------------------------------|---------|------------|... | {"source_file": "storing-data.md"} | [
0.03475789725780487,
0.05141118913888931,
-0.033738814294338226,
0.009789017029106617,
-0.08381658792495728,
0.04203931242227554,
0.027381030842661858,
0.04271918162703514,
0.0031522971112281084,
-0.0500001385807991,
0.0207861065864563,
-0.053667742758989334,
-0.011882828548550606,
-0.0629... |
f7124fd1-ade8-4ae1-ba6f-99485a4c804f | |
max_elements
| Integer |
10000000
| Maximum number of cache files. |
|
load_metadata_threads
| Integer |
16
|... | {"source_file": "storing-data.md"} | [
0.04831887036561966,
0.005787931382656097,
-0.08945991843938828,
-0.029751939699053764,
0.0018839662661775947,
-0.062182217836380005,
0.005436497740447521,
0.05651332437992096,
-0.05555709823966026,
-0.006784971337765455,
0.0058837346732616425,
0.017243050038814545,
-0.008985564112663269,
... |
8a17bab0-fbc8-4d66-979e-14541953936c | Note
: Size values support units like
ki
,
Mi
,
Gi
, etc. (e.g.,
10Gi
).
File Cache Query/Profile Settings {#file-cache-query-profile-settings}
| Setting | Type | Default | Description ... | {"source_file": "storing-data.md"} | [
0.07885651290416718,
0.04276491701602936,
-0.07830876857042313,
0.0819091945886612,
-0.10823115706443787,
-0.033026073127985,
0.01048959419131279,
0.10102254152297974,
-0.059291865676641464,
0.013861516490578651,
0.011177128180861473,
-0.038871970027685165,
-0.006706381682306528,
-0.034269... |
fb486fea-8da7-4296-b49a-a82e2a83844e | Cache system tables {#cache-system-tables-file-cache}
| Table Name | Description | Requirements |
|-------------------------------|-----------------------------------------------------|-----------------------------------------... | {"source_file": "storing-data.md"} | [
0.0036662982311099768,
-0.020636815577745438,
-0.0808556005358696,
0.014127248898148537,
0.032080382108688354,
-0.09237496554851532,
0.06687544286251068,
0.08683482557535172,
-0.042473290115594864,
0.07899540662765503,
0.02768026664853096,
-0.039065245538949966,
-0.005562517326325178,
-0.0... |
efd8af60-3bcf-4d23-b085-a4844687e3f3 | | Cache current metrics | Cache asynchronous metrics | Cache profile events |
|---------------------------|----------------------------|-------------------------------------------------------------------------------------------|
|
FilesystemCache... | {"source_file": "storing-data.md"} | [
0.020267030224204063,
-0.023912254720926285,
-0.09559768438339233,
0.0005395048065111041,
0.013910860754549503,
-0.012796883471310139,
0.08302439749240875,
0.0029518259689211845,
0.00023625753237865865,
0.03129177168011665,
0.0453948900103569,
-0.05290994048118591,
0.041167519986629486,
-0... |
0c5d9348-92ba-4db4-9416-ee9cddf2f916 | :::tip
Storage can also be configured temporarily within a query, if a web dataset is
not expected to be used routinely, see
dynamic configuration
and skip
editing the configuration file.
A
demo dataset
is hosted in GitHub. To prepare your own tables for web
storage see the tool
clickhouse-static-files-uploa... | {"source_file": "storing-data.md"} | [
0.010607474483549595,
-0.062483031302690506,
-0.13807259500026703,
0.09635156393051147,
0.007883251644670963,
-0.013768806122243404,
0.005355526227504015,
0.04300416260957718,
-0.06292902678251266,
0.03805217519402504,
0.1276937574148178,
-0.053515151143074036,
0.07329419255256653,
-0.0654... |
1c421241-dd63-47ff-a9ec-22d7604809cf | sql
ATTACH TABLE test_hits UUID '1ae36516-d62d-4218-9ae3-6516d62da218'
(
WatchID UInt64,
JavaEnable UInt8,
Title String,
GoodEvent Int16,
EventTime DateTime,
EventDate Date,
CounterID UInt32,
ClientIP UInt32,
ClientIP6 FixedString(16),
RegionID UInt32,
UserID UInt64,
Coun... | {"source_file": "storing-data.md"} | [
0.038943201303482056,
-0.036282557994127274,
-0.06751041114330292,
0.025097772479057312,
-0.06296183913946152,
-0.005500344093888998,
0.04652673378586769,
-0.0074294754303991795,
-0.028403451666235924,
0.05444561317563057,
0.05231894552707672,
-0.07316774129867554,
0.04650069773197174,
-0.... |
c730fe24-376b-4086-9f3a-a78a9eef0580 | OpenstatAdID String,
OpenstatSourceID String,
UTMSource String,
UTMMedium String,
UTMCampaign String,
UTMContent String,
UTMTerm String,
FromTag String,
HasGCLID UInt8,
RefererHash UInt64,
URLHash UInt64,
CLID UInt32,
YCLID UInt64,
ShareService String,
ShareURL St... | {"source_file": "storing-data.md"} | [
0.019476046785712242,
0.0025816934648901224,
-0.027211179956793785,
-0.05152246356010437,
-0.10860489308834076,
-0.005735213868319988,
0.003105033887550235,
0.05028410255908966,
-0.018256794661283493,
0.03201176971197128,
0.07726351171731949,
-0.03729277104139328,
0.08109363913536072,
-0.0... |
9630d19d-cf2f-4fb3-8533-c75e4dc63b4e | Required parameters {#static-web-storage-required-parameters}
| Parameter | Description |
|------------|---------------------------------------------------------------------------------------------------------------... | {"source_file": "storing-data.md"} | [
0.004004235845059156,
-0.010054376907646656,
-0.12807996571063995,
0.049661699682474136,
-0.004768740851432085,
-0.04119742289185524,
-0.04958658665418625,
0.044125381857156754,
-0.03199830278754234,
0.06306282430887222,
0.04765217378735542,
-0.06354357302188873,
0.0809711366891861,
0.0026... |
b3641d2a-f0c1-4a6b-bc74-36dfd28572da | description: 'Page detailing allocation profiling in ClickHouse'
sidebar_label: 'Allocation profiling for versions before 25.9'
slug: /operations/allocation-profiling-old
title: 'Allocation profiling for versions before 25.9'
doc_type: 'reference'
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem'... | {"source_file": "allocation-profiling-old.md"} | [
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-0.... |
30dabf71-1356-4c05-9769-99e378a61167 | In general, the
jeprof
command is used as:
sh
jeprof path/to/binary path/to/heap/profile --output_format [ > output_file]
If you want to compare which allocations happened between two profiles you can set the
base
argument:
sh
jeprof path/to/binary --base path/to/first/heap/profile path/to/second/heap/profile... | {"source_file": "allocation-profiling-old.md"} | [
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0.0... |
2ee141ab-2716-4917-89dd-fabc1e80c29a | Other resources {#other-resources}
ClickHouse/Keeper expose
jemalloc
related metrics in many different ways.
:::warning Warning
It's important to be aware that none of these metrics are synchronized with each other and values may drift.
:::
System table
asynchronous_metrics
{#system-table-asynchronous_metrics... | {"source_file": "allocation-profiling-old.md"} | [
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0bdd0c16-7e81-466a-8160-ee9faea1cf3f | description: 'Guide to using and configuring the query condition cache feature in ClickHouse'
sidebar_label: 'Query condition cache'
sidebar_position: 64
slug: /operations/query-condition-cache
title: 'Query condition cache'
doc_type: 'guide'
Query condition cache
:::note
The query condition cache only works when... | {"source_file": "query-condition-cache.md"} | [
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be224d3e-d1cb-48ea-bc50-6c92f970d910 | Memory consumption {#memory-consumption}
Since the query condition cache stores only a single bit per filter condition and granule, it consumes only little memory.
The maximum size of the query condition cache can be configured using server settings
query_condition_cache_size
(default: 100 MB).
A cache size of 100 ... | {"source_file": "query-condition-cache.md"} | [
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-0.096259... |
36cf1462-e312-464f-b6a3-94f04898e27c | description: 'Guide to using OpenTelemetry for distributed tracing and metrics collection
in ClickHouse'
sidebar_label: 'Tracing ClickHouse with OpenTelemetry'
sidebar_position: 62
slug: /operations/opentelemetry
title: 'Tracing ClickHouse with OpenTelemetry'
doc_type: 'guide'
OpenTelemetry
is an open standard f... | {"source_file": "opentelemetry.md"} | [
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b731830a-b6b3-4239-babf-4119c147b8f1 | Integration with monitoring systems {#integration-with-monitoring-systems}
At the moment, there is no ready tool that can export the tracing data from ClickHouse to a monitoring system.
For testing, it is possible to setup the export using a materialized view with the
URL
engine over the
system.opentelemetry_spa... | {"source_file": "opentelemetry.md"} | [
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-0.008227773942053318,
0.044708333909511566,
... |
20d4f9ed-68d7-4b88-91f3-5b1b432db1b0 | description: 'You can monitor the utilization of hardware resources and also ClickHouse
server metrics.'
keywords: ['monitoring', 'observability', 'advanced dashboard', 'dashboard', 'observability
dashboard']
sidebar_label: 'Monitoring'
sidebar_position: 45
slug: /operations/monitoring
title: 'Monitoring'
doc_typ... | {"source_file": "monitoring.md"} | [
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0.... |
82a532b9-69ca-4d9b-a25a-d89c725437a6 | Additionally, you can monitor server availability through the HTTP API. Send the
HTTP GET
request to
/ping
. If the server is available, it responds with
200 OK
.
To monitor servers in a cluster configuration, you should set the
max_replica_delay_for_distributed_queries
parameter and use the HTTP resource
/rep... | {"source_file": "monitoring.md"} | [
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0.01873747445642948,
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9e0b5024-9e74-4c3a-a708-3092eaf14ebb | description: 'Page detailing the ClickHouse query analyzer'
keywords: ['analyzer']
sidebar_label: 'Analyzer'
slug: /operations/analyzer
title: 'Analyzer'
doc_type: 'reference'
Analyzer
In ClickHouse version
24.3
, the new query analyzer was enabled by default.
You can read more details about how it works
here
.... | {"source_file": "analyzer.md"} | [
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0.027... |
c469ea97-2dae-49d1-8535-8133dc9f43ad | JOIN
using a column from a projection {#join-using-column-from-projection}
An alias from the
SELECT
list can not be used as a
JOIN USING
key by default.
A new setting,
analyzer_compatibility_join_using_top_level_identifier
, when enabled, alters the behavior of
JOIN USING
to prefer resolving identifiers bas... | {"source_file": "analyzer.md"} | [
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0.07981248199939728,
-0... |
30a32f62-9a9b-4305-b6fe-b8833b5d7b8e | For example:
sql
SELECT id, toTypeName(id)
FROM VALUES('id LowCardinality(String)', ('a')) AS t1
FULL OUTER JOIN VALUES('id String', ('b')) AS t2
USING (id);
In this query, the common supertype for
id
is determined as
String
, discarding the
LowCardinality
modifier from
t1
.
Projection column names changes ... | {"source_file": "analyzer.md"} | [
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0.0016... |
85c4df18-c7d0-430f-9e18-62fc1166fe72 | description: 'Documentation for Syntax'
displayed_sidebar: 'sqlreference'
sidebar_label: 'Syntax'
sidebar_position: 2
slug: /sql-reference/syntax
title: 'Syntax'
doc_type: 'reference'
In this section, we will take a look at ClickHouse's SQL syntax.
ClickHouse uses a syntax based on SQL but offers a number of exten... | {"source_file": "syntax.md"} | [
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0.003413791535422206,
0.081056147813797,
-0.08970... |
298082ef-eb28-4f9d-9b32-3663389888c6 | Keywords are
case-insensitive
when they correspond to:
SQL standard. For example,
SELECT
,
select
and
SeLeCt
are all valid.
Implementation in some popular DBMS (MySQL or Postgres). For example,
DateTime
is the same as
datetime
.
:::note
You can check whether a data type name is case-sensitive in the... | {"source_file": "syntax.md"} | [
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0.04637666791677475,
-0.0016776574775576591,
0.1337205469608307,
-... |
078f94fd-56fb-4359-9eda-7185d73cb842 | :::note
The backslash loses its special meaning i.e. it is interpreted literally should it precede characters other than the ones listed below.
:::
| Supported Escape | Description |
|-------------------------------------|-----------------... | {"source_file": "syntax.md"} | [
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0.09657812118530273,
-0.0791160... |
02e3a424-4815-4823-8034-7045296d782e | If the value is prefixed with
0b
or
0x
/
0X
, the number is parsed as binary or hexadecimal, respectively.
If the value is negative and the absolute magnitude is greater than 2
63
, an error is returned.
If unsuccessful, the value is next parsed as a floating-point number using the
strtod
function.
Otherwise... | {"source_file": "syntax.md"} | [
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0.02196534536778927,
-0.0... |
6c0ef63e-749e-4b8a-8437-1d3d94eefe24 | NULL {#null}
NULL
is used to indicate that a value is missing.
To store
NULL
in a table field, it must be of the
Nullable
type.
:::note
The following should be noted for
NULL
:
Depending on the data format (input or output),
NULL
may have a different representation. For more information, see
data form... | {"source_file": "syntax.md"} | [
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0.02468583732843399,
-0.08691... |
95b77e1a-7ebb-4958-8d0a-bacdcc5d4689 | ```bash
clickhouse-client --param_message='hello' --query="SELECT {message: String}"
hello
```
If the query parameter represents the name of a database, table, function or other identifier, use `Identifier` for its type. For example, the following query returns rows from a table named `uk_price_paid`:
```sql
SET par... | {"source_file": "syntax.md"} | [
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0.08420634269714355,
-0.0... |
6fffc450-2ce5-40ea-9a7c-16dcd2ed284c | Expression Aliases {#expression-aliases}
An alias is a user-defined name for an
expression
in a query.
sql
expr AS alias
The parts of the syntax above are explained below.
| Part of syntax | Description ... | {"source_file": "syntax.md"} | [
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0.007711211685091257,
0.05526835843920708,
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0.10737205296754837,
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0.03264152258634567,
0.020093156024813652,
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0.08252140879631042,
-0.032545... |
56c6afa1-d98a-4f88-a934-4f2d3f84168b | ```sql
CREATE TABLE t
(
a Int,
b Int
)
ENGINE = TinyLog();
SELECT
argMax(a, b),
sum(b) AS b
FROM t;
Received exception from server (version 18.14.17):
Code: 184. DB::Exception: Received from localhost:9000, 127.0.0.1. DB::Exception: Aggregate function sum(b) is found inside another aggregate functio... | {"source_file": "syntax.md"} | [
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0.04907627031207085,
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0.06133255362510681,
-0.0710... |
7e6e3b21-a8bb-4742-9625-8a4fffa10bd3 | description: 'Documentation for Distributed Ddl'
sidebar_label: 'Distributed DDL'
sidebar_position: 3
slug: /sql-reference/distributed-ddl
title: 'Distributed DDL Queries (ON CLUSTER Clause)'
doc_type: 'reference'
By default, the
CREATE
,
DROP
,
ALTER
, and
RENAME
queries affect only the current server where t... | {"source_file": "distributed-ddl.md"} | [
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0.007494418416172266,
0.015635373070836067,
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0.06206046789884567,
-0... |
025cdef5-bac0-48ec-b866-8a4e9d42ff2f | description: 'Documentation for ClickHouse SQL Reference'
keywords: ['clickhouse', 'docs', 'sql reference', 'sql statements', 'sql', 'syntax']
slug: /sql-reference
title: 'SQL Reference'
doc_type: 'reference'
import { TwoColumnList } from '/src/components/two_column_list'
import { ClickableSquare } from '/src/compo... | {"source_file": "index.md"} | [
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0.010579336434602737,
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0.0235088... |
1aed6f18-405f-4987-a497-73e8e1e3659f | description: 'Page describing transactional (ACID) support in ClickHouse'
slug: /guides/developer/transactional
title: 'Transactional (ACID) support'
doc_type: 'guide'
import ExperimentalBadge from '@theme/badges/ExperimentalBadge';
import CloudNotSupportedBadge from '@theme/badges/CloudNotSupportedBadge';
Transa... | {"source_file": "transactions.md"} | [
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0.013202790170907974,
0.09583358466625214,
-0.069... |
1bc7b671-625c-48cd-855c-559c52471622 | Notes {#notes}
rows inserted from the client in some data format are packed into a single block when:
the insert format is row-based (like CSV, TSV, Values, JSONEachRow, etc) and the data contains less then
max_insert_block_size
rows (~1 000 000 by default) or less then
min_chunk_bytes_for_parallel_parsing
by... | {"source_file": "transactions.md"} | [
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0.06553277373313904,
-0.06465... |
4f6b646c-6862-416c-9ca6-d3c9b74bbaf9 | xml title=/etc/clickhouse-server/config.d/transactions.xml
<clickhouse>
<allow_experimental_transactions>1</allow_experimental_transactions>
</clickhouse>
Basic configuration for a single ClickHouse server node with ClickHouse Keeper enabled {#basic-configuration-for-a-single-clickhouse-server-node-with-clickhous... | {"source_file": "transactions.md"} | [
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cf404033-55a7-4de4-9357-9fdd438fd8a5 | sql
ROLLBACK
response
Ok.
Create a table for testing {#create-a-table-for-testing}
:::tip
Creation of tables is not transactional. Run this DDL query outside of a transaction.
:::
sql
CREATE TABLE mergetree_table
(
`n` Int64
)
ENGINE = MergeTree
ORDER BY n
response
Ok.
Begin a transaction and insert a ... | {"source_file": "transactions.md"} | [
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2b4d1f98-9ea4-44e8-9950-98856e5cab87 | slug: /use-cases
title: 'Use Case Guides'
pagination_prev: null
pagination_next: null
description: 'Landing page for use case guides'
doc_type: 'landing-page'
keywords: ['use cases', 'observability', 'time-series', 'data lake', 'machine learning', 'AI']
In this section of the docs you can find our use case guides.
... | {"source_file": "index.md"} | [
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2043d041-31d8-4baf-ab09-e71777046a59 | description: 'The ClickHouse Playground allows people to experiment with ClickHouse
by running queries instantly, without setting up their server or cluster.'
keywords: ['clickhouse', 'playground', 'getting', 'started', 'docs']
sidebar_label: 'ClickHouse playground'
slug: /getting-started/playground
title: 'ClickHous... | {"source_file": "playground.md"} | [
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1f275efb-bb77-4f96-a2c3-bb0ddd00d00d | description: 'Get started with ClickHouse using our tutorials and example datasets'
keywords: ['clickhouse', 'install', 'tutorial', 'sample', 'datasets']
pagination_next: tutorial
sidebar_label: 'Overview'
sidebar_position: 0
slug: /getting-started/example-datasets/
title: 'Tutorials and Example Datasets'
doc_type: 'la... | {"source_file": "index.md"} | [
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d56953ac-05bb-4f17-842b-bebb126a9983 | | Page | Description |
|-----|-----|
|
Amazon Customer Review
| Over 150M customer reviews of Amazon products |
|
AMPLab Big Data Benchmark
| A benchmark dataset used for comparing the performance of data warehousing solutions. |
|
Analyzing Stack Overflow data with ClickHouse
| Analyzing Stack Overflow data with... | {"source_file": "index.md"} | [
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9ad93c11-4012-4bd7-919e-c60782948873 | | 131 million rows of weather observation data for the last 128 yrs |
|
Terabyte click logs from Criteo
| A terabyte of click logs from Criteo |
|
The UK property prices dataset
| Learn how to use projections to improve the performance of queries that you run frequently using the UK property dataset, which contains... | {"source_file": "index.md"} | [
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2cbebbeb-f88d-4253-a455-baa137f6acb7 | title: 'Inserting ClickHouse data'
description: 'How to insert data into ClickHouse'
keywords: ['INSERT', 'Batch Insert']
sidebar_label: 'Inserting ClickHouse data'
slug: /guides/inserting-data
show_related_blogs: true
doc_type: 'guide'
import postgres_inserts from '@site/static/images/guides/postgres-inserts.png';... | {"source_file": "inserting-data.md"} | [
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4f0d67aa-c1f9-4267-ac3d-60e08b8cc6a2 | This means inserts remain resilient in the following cases:
If the node receiving the data has issues, the insert query will time out (or give a more specific error) and not get an acknowledgment.
If the data got written by the node but the acknowledgement can't be returned to the sender of the query ... | {"source_file": "inserting-data.md"} | [
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093a8ff4-112b-4c67-a957-80775a1a8901 | Before the buffer gets flushed, the data of other asynchronous insert queries from the same or other clients can be collected in the buffer.
The part created from the buffer flush will potentially contain the data from several asynchronous insert queries.
Generally, these mechanics shift the batching of data from the c... | {"source_file": "inserting-data.md"} | [
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fabbbafa-14d5-494b-a472-9df6c415bb7d | Use the HTTP interface {#use-the-http-interface}
Unlike many traditional databases, ClickHouse supports an HTTP interface.
Users can use this for both inserting and querying data, using any of the above formats.
This is often preferable to ClickHouse's native protocol as it allows traffic to be easily switched with l... | {"source_file": "inserting-data.md"} | [
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ff51f520-cfcb-4698-913f-836152cda0e2 | Data can be exported from PostgreSQL in CSV format. This can then be inserted into ClickHouse from either local files or via object storage using table functions.
:::note Need help inserting large datasets?
If you need help inserting large datasets or encounter any errors when importing data into ClickHouse Cloud, ... | {"source_file": "inserting-data.md"} | [
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cfb6f6cd-362b-48ab-be2c-3f59faf61b51 | :::note
When inserting data with clickhouse-client in interactive mode, it is possible to let ClickHouse handle the decompression for you on insert using the
COMPRESSION
clause. ClickHouse can automatically detect the compression type from the file extension, but you can also specify it explicitly.
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... |
7bd6ed0b-24ae-4d0a-8761-b9881dbcabff | title: 'Troubleshooting'
description: 'Installation troubleshooting guide'
slug: /guides/troubleshooting
doc_type: 'guide'
keywords: ['troubleshooting', 'debugging', 'problem solving', 'errors', 'diagnostics']
Installation {#installation}
Cannot import GPG keys from keyserver.ubuntu.com with apt-key {#cannot-impo... | {"source_file": "troubleshooting.md"} | [
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38cc6580-8f53-493d-a83a-f78a0bb8923d | Possible issue: the cache is wrong, maybe it's broken after updated GPG key in 2022-09.
The solution is to clean out the cache and lib directory for Yum:
shell
sudo find /var/lib/yum/repos/ /var/cache/yum/ -name 'clickhouse-*' -type d -exec rm -rf {} +
sudo rm -f /etc/yum.repos.d/clickhouse.repo
After that follow... | {"source_file": "troubleshooting.md"} | [
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d061c0dd-c515-4161-938b-813bfb2580d1 | Start clickhouse-server in interactive mode {#start-clickhouse-server-in-interactive-mode}
shell
sudo -u clickhouse /usr/bin/clickhouse-server --config-file /etc/clickhouse-server/config.xml
This command starts the server as an interactive app with standard parameters of the autostart script. In this mode
clickhou... | {"source_file": "troubleshooting.md"} | [
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... |
47e3737e-4da0-4bf2-8991-83fdd9f8f5c2 | title: 'Manage and Deploy Overview'
description: 'Overview page for Manage and Deploy'
slug: /guides/manage-and-deploy-index
doc_type: 'landing-page'
keywords: ['deployment', 'management', 'administration', 'operations', 'guides']
Manage and deploy
This section contains the following topics: | {"source_file": "manage-and-deploy-index.md"} | [
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d3b4e2d8-a9b7-4b74-a7fe-0ead63e0049c | | Topic | Description |
|---------------------------------------------------------------------------------... | {"source_file": "manage-and-deploy-index.md"} | [
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9422433e-c191-44cc-9495-5e30d075c4ec | |
Secured Communication with Zookeeper
| Guide to setting up secured communication between ClickHouse and Zookeeper. |
|
Startup Scripts
| Example of how to run startup scripts during sta... | {"source_file": "manage-and-deploy-index.md"} | [
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a5258569-bbc4-4d0f-88df-5f02c6e76972 | sidebar_position: 1
sidebar_label: 'Creating tables'
title: 'Creating tables in ClickHouse'
slug: /guides/creating-tables
description: 'Learn about Creating Tables in ClickHouse'
keywords: ['creating tables', 'CREATE TABLE', 'table creation', 'database guide', 'MergeTree engine']
doc_type: 'guide'
Creating tables i... | {"source_file": "creating-tables.md"} | [
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4c16b9b6-4e4a-44a6-a1df-208ee4a72dcb | title: 'Using JOINs in ClickHouse'
description: 'How to join tables in ClickHouse'
keywords: ['joins', 'join tables']
slug: /guides/joining-tables
doc_type: 'guide'
import Image from '@theme/IdealImage';
import joins_1 from '@site/static/images/guides/joins-1.png';
import joins_2 from '@site/static/images/guides/jo... | {"source_file": "joining-tables.md"} | [
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371ee028-921f-4eba-90c7-92b7ec9cdb67 | 1 row in set. Elapsed: 2.284 sec. Processed 150.20 million rows, 16.61 GB (65.76 million rows/s., 7.27 GB/s.)
Peak memory usage: 323.52 MiB.
```
Although ClickHouse makes attempts to push down conditions to all join clauses and subqueries, we recommend users always manually apply conditions to all sub-clauses where p... | {"source_file": "joining-tables.md"} | [
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d2ca54c0-311d-4eaf-a1fe-e5a2be2ffcab | These algorithms dictate the manner in which a join query is planned and executed. By default, ClickHouse uses the direct or the hash join algorithm based on the used join type and strictness and engine of the joined tables. Alternatively, ClickHouse can be configured to adaptively choose and dynamically change the joi... | {"source_file": "joining-tables.md"} | [
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ea011467-2375-430c-8022-0eb26d1d50c3 | Partial merge join is optimized for minimizing memory usage when large tables are joined, at the expense of join speed which is quite slow. This is especially the case when the physical row order of the left table doesn't match the join key sorting order.
Grace hash join is the most flexible of the three non-memory-b... | {"source_file": "joining-tables.md"} | [
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... |
a5d0d239-d076-46a3-a076-baaeb3e65e42 | sidebar_position: 3
sidebar_label: 'Selecting data'
title: 'Selecting ClickHouse Data'
slug: /guides/writing-queries
description: 'Learn about Selecting ClickHouse Data'
keywords: ['SELECT', 'data formats']
show_related_blogs: true
doc_type: 'guide'
ClickHouse is a SQL database, and you query your data by writing t... | {"source_file": "writing-queries.md"} | [
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889cedb6-56bb-4e72-a7e3-9550ed5d35b5 | sidebar_position: 1
sidebar_label: 'Separation of storage and compute'
slug: /guides/separation-storage-compute
title: 'Separation of Storage and Compute'
description: 'This guide explores how you can use ClickHouse and S3 to implement an architecture with separated storage and compute.'
doc_type: 'guide'
keywords: ['s... | {"source_file": "separation-storage-compute.md"} | [
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04716d60-d86f-4b98-bd23-47e05af538f2 | Copy the following XML in to the newly created file, replacing
BUCKET
,
ACCESS_KEY_ID
,
SECRET_ACCESS_KEY
with the AWS bucket details where you'd like to store your data:
xml
<clickhouse>
<storage_configuration>
<disks>
<s3_disk>
<type>s3</type>
<endpoint>$BUCKET</endpoint>
<ac... | {"source_file": "separation-storage-compute.md"} | [
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ac5f21e3-ec33-4702-84b1-1289976908ac | Let's verify that our rows were inserted:
sql
SELECT * FROM my_s3_table;
```response
┌─id─┬─column1─┐
│ 1 │ abc │
│ 2 │ xyz │
└────┴─────────┘
2 rows in set. Elapsed: 0.284 sec.
```
In the AWS console, if your data was successfully inserted to S3, you should see that ClickHouse has created new files i... | {"source_file": "separation-storage-compute.md"} | [
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f59f217b-930f-4a1a-bc5e-4af733210233 | sidebar_label: 'Generating random test data'
title: 'Generating random test data in ClickHouse'
slug: /guides/generating-test-data
description: 'Learn about Generating Random Test Data in ClickHouse'
show_related_blogs: true
doc_type: 'guide'
keywords: ['random data', 'test data']
Generating random test data in Cli... | {"source_file": "generating-test-data.md"} | [
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195a36bb-1b84-4314-a5d8-043e1740e3c2 | Use-case
: Emulate system metrics (e.g., CPU usage) that vary over time.
```sql
CREATE TABLE cpu_metrics (
host String,
ts DateTime,
usage Float32
) ENGINE = MergeTree
ORDER BY (host, ts);
INSERT INTO cpu_metrics
SELECT
arrayJoin(['host1','host2','host3']) AS host,
now() - INTERVAL number SECOND AS ts,
... | {"source_file": "generating-test-data.md"} | [
0.07949326187372208,
0.002123456448316574,
-0.004557368811219931,
0.04323028773069382,
-0.09613548964262009,
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0.0026936642825603485,
... |
88194aa6-c756-4cdc-bf50-e6ed0ad18821 | Let's combine both functions for a completely random table.
First, see what structure we'll get:
sql
SELECT generateRandomStructure(7, 123) AS structure FORMAT vertical;
response
┌─structure──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────... | {"source_file": "generating-test-data.md"} | [
0.006521495524793863,
0.013527177274227142,
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0.040472451597452164,
0.024999607354402542,
-0.1236330047249794,
0.019735153764486313,
-0.... |
c4c816ba-8221-4c96-954a-8cb35e28bed9 | DESCRIBE TABLE fully_random_table;
```
response
┌─name─┬─type─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┬─default_type─┬─default_expression─┬─comment─┬─codec_expression─┬─ttl_expression─┐
1. │ ... | {"source_file": "generating-test-data.md"} | [
0.046428874135017395,
0.03333672881126404,
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0.040487468242645264,
-0.... |
20726c12-3305-4b65-9b25-71d57e4103bb | description: 'Table of Contents page for Engines'
slug: /engines
title: 'Engines'
doc_type: 'landing-page'
| Page | Description ... | {"source_file": "index.md"} | [
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67f23c52-a1b9-4e03-a2b5-5216541911f2 | slug: /dictionary
title: 'Dictionary'
keywords: ['dictionary', 'dictionaries']
description: 'A dictionary provides a key-value representation of data for fast lookups.'
doc_type: 'reference'
import dictionaryUseCases from '@site/static/images/dictionary/dictionary-use-cases.png';
import dictionaryLeftAnyJoin from '... | {"source_file": "index.md"} | [
-0.030996039509773254,
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0.05664849653840065,
0.08624549210071564,
0.10742662847042084,
0.015225... |
1462c973-6f21-4cad-a4cf-0e5e2c10f0fc | Row 1:
──────
Id: 25372161
Title: How to add exception handling to SqlDataSource.UpdateCommand
UpVotes: 13
DownVotes: 13
Controversial_ratio: 0
1 rows in set. Elapsed: 1.283 sec. Processed 418.44 million rows, 7.23 GB (326.07 million rows/s., 5.63 GB/s.... | {"source_file": "index.md"} | [
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0.1032288521528244,
-0.07... |
b33126df-59cd-4dd7-b6ea-826776e66575 | Our dictionary requires a primary key on which lookups will be performed. This is conceptually identical to a transactional database primary key and should be unique. Our above query requires a lookup on the join key -
PostId
. The dictionary should in turn be populated with the total of the up and down votes per
Pos... | {"source_file": "index.md"} | [
-0.051438651978969574,
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0.03333333134651184,
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0.044274259358644485,
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0.04349930211901665,
0.000056193250202341005,
0.09924473613500595,
... |
247acbf4-1e6e-4c1e-bdb8-acf46a184de3 | Dictionaries can be used to look up values at query time. These values can be returned in results or used in aggregations. Suppose we create a dictionary to map user IDs to their location:
sql
CREATE DICTIONARY users_dict
(
`Id` Int32,
`Location` String
)
PRIMARY KEY Id
SOURCE(CLICKHOUSE(QUERY 'SELECT Id, Locatio... | {"source_file": "index.md"} | [
-0.0011665672063827515,
0.0023383772931993008,
-0.03253154084086418,
0.013942074961960316,
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0.05664009600877762,
0.017309557646512985,
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0.011313136667013168,
0.024513961747288704,
-0.006956818047910929,
0.06125273555517197,
-0.... |
8f1c86de-b6c0-46bd-abff-6be303728baa | A dictionary provides a mapping from user id to location, backed by the
users
table:
sql
CREATE DICTIONARY users_dict
(
`Id` UInt64,
`Location` String
)
PRIMARY KEY Id
SOURCE(CLICKHOUSE(QUERY 'SELECT Id, Location FROM users WHERE Id >= 0'))
LIFETIME(MIN 600 MAX 900)
LAYOUT(HASHED())
We omit users with a... | {"source_file": "index.md"} | [
0.04435765743255615,
0.023031629621982574,
-0.015956901013851166,
-0.03583487495779991,
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0.02576267160475254,
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0.06268982589244843,
0.08127795904874802,
-0.01257439237087965,
0.08133840560913086,
-0.027... |
637e36c3-75b4-45cb-9c25-cd735c0b6d48 | Refreshing dictionaries {#refreshing-dictionaries}
We have specified a
LIFETIME
for the dictionary of
MIN 600 MAX 900
. LIFETIME is the update interval for the dictionary, with the values here causing a periodic reload at a random interval between 600 and 900s. This random interval is necessary in order to distrib... | {"source_file": "index.md"} | [
-0.03001543879508972,
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0.06333668529987335,
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0.0005901921540498734,
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0.027793634682893753,
0.004687437321990728,
0.0034019513987004757,
0.09221795946359634,
-0.0050069550052285194,
... |
731f2bc6-67ca-4bc5-9faa-90c9e1eeb86c | sidebar_position: 2
sidebar_label: 'What is OLAP?'
description: 'OLAP stands for Online Analytical Processing. It is a broad term that can be looked at from two perspectives: technical and business.'
title: 'What is OLAP?'
slug: /concepts/olap
keywords: ['OLAP']
doc_type: 'reference'
What is OLAP?
OLAP
stands fo... | {"source_file": "olap.md"} | [
-0.06621648371219635,
0.018360944464802742,
-0.048850663006305695,
0.053910452872514725,
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0.033464159816503525,
0.05137196555733681,
... |
b823e534-c0be-4ff6-bc7a-c6f67ef80933 | Even if a DBMS started out as a pure OLAP or pure OLTP, it is forced to move in the HTAP direction to keep up with the competition. ClickHouse is no exception. Initially, it has been designed as a
fast-as-possible OLAP system
and it still does not have full-fledged transaction support, but some features like consiste... | {"source_file": "olap.md"} | [
-0.0022780296858400106,
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0.031181376427412033,
-0.050... |
de9be494-0b48-4f70-9c24-c142c50cfe43 | sidebar_label: 'Glossary'
description: 'This page contains a list of commonly used words and phrases regarding ClickHouse, as well as their definitions.'
title: 'Glossary'
slug: /concepts/glossary
keywords: ['glossary', 'definitions', 'terminology']
doc_type: 'reference'
Glossary
Atomicity {#atomicity}
Atomic... | {"source_file": "glossary.md"} | [
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0.0022883673664182425,
-0.... |
15702cb4-ab82-458d-8b82-11ae6b4e42fd | Lightweight update {#lightweight-update}
A lightweight update in ClickHouse is an experimental feature that allows you to update rows in a table using standard SQL UPDATE syntax, but instead of rewriting entire columns or data parts (as with traditional mutations), it creates "patch parts" containing only the updated... | {"source_file": "glossary.md"} | [
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0.035748496651649475,
0.016199998557567596,
-0... |
4c4a9c82-a9a4-401a-97b4-d41abbe1c0fa | Refreshable materialized view {#refreshable-materialized-view}
Refreshable materialized view is a type of materialized view that periodically re-executes its query over the full dataset and stores the result in a target table. Unlike incremental materialized views, refreshable materialized views are updated on a sche... | {"source_file": "glossary.md"} | [
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0baf916d-4ec5-4474-8d61-4bb5dcc3dfc3 | title: 'Concepts'
slug: /concepts
description: 'Landing page for concepts'
pagination_next: null
pagination_prev: null
keywords: ['concepts', 'OLAP', 'fast']
doc_type: 'landing-page'
In this section of the docs we'll dive into the concepts around what makes ClickHouse so fast and efficient.
| Page ... | {"source_file": "index.md"} | [
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-0.0... |
d6b8e608-6350-45f3-a4f1-1aaf92b48ba0 | slug: /operations/utilities/static-files-disk-uploader
title: 'clickhouse-static-files-disk-uploader'
keywords: ['clickhouse-static-files-disk-uploader', 'utility', 'disk', 'uploader']
description: 'Provides a description of the clickhouse-static-files-disk-uploader utility'
doc_type: 'guide'
clickhouse-static-file... | {"source_file": "static-files-disk-uploader.md"} | [
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-0.006... |
9100ef91-1971-43eb-ac4e-2115bd3f809a | With
test
mode enabled, the table metadata directory is uploaded to the specified URL via a PUT request.
bash
$ clickhouse static-files-disk-uploader --test-mode --url http://nginx:80/test1 --metadata-path ./store/bcc/bccc1cfd-d43d-43cf-a5b6-1cda8178f1ee/
Using the table metadata directory to create a ClickHouse ... | {"source_file": "static-files-disk-uploader.md"} | [
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0.0463... |
8104a247-7ba1-44df-a76a-882a12304dd2 | slug: /native-protocol/basics
sidebar_position: 1
title: 'Basics'
description: 'Native protocol basics'
keywords: ['native protocol', 'TCP protocol', 'protocol basics', 'binary protocol', 'client-server communication']
doc_type: 'guide'
Basics
:::note
Client protocol reference is in progress.
Most examples are ... | {"source_file": "basics.md"} | [
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0.007830190472304821,
0.04120270162820816,
0.037230... |
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