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8e690c4b-14c5-4393-bbbb-66accfcc7062
Now Grafana will see the results of the alias table instead of the results from DESC example_table : Both types of aliasing can be used to perform complex type conversions or JSON field extraction. All YAML options {#all-yaml-options} These are all of the YAML configuration options made available by the plugin....
{"source_file": "config.md"}
[ -0.10111738741397858, 0.011910910718142986, -0.045331958681344986, -0.009549847804009914, -0.08327840268611908, -0.08854611217975616, -0.06032722070813179, -0.03739726543426514, -0.011242221109569073, 0.05352409929037094, 0.027951324358582497, -0.060898952186107635, -0.03177853301167488, -...
9f5509a3-2e7a-42b8-b514-3c8a6afbcda0
sidebar_label: 'Query Builder' sidebar_position: 2 slug: /integrations/grafana/query-builder description: 'Using the Query Builder in the ClickHouse Grafana plugin' title: 'Query Builder' doc_type: 'guide' keywords: ['grafana', 'query builder', 'visualization', 'dashboards', 'plugin'] import Image from '@theme/Idea...
{"source_file": "query-builder.md"}
[ -0.048638541251420975, 0.058568213135004044, -0.038518860936164856, 0.05437993258237839, -0.061452411115169525, -0.004407224711030722, -0.007459629792720079, 0.05267786979675293, -0.03731360659003258, 0.015193847008049488, 0.028439415618777275, -0.0653594359755516, 0.07056548446416855, -0....
496205a0-299a-4396-ab04-b6bbc128d89d
Table {#table} The most flexible query type is the table query. This is a catch-all for the other query builders designed to handle simple and aggregate queries. | Field | Description | |----|----| | Builder Mode | Simple queries exclude Aggregates and Group By, while aggregate queries include these options. | | ...
{"source_file": "query-builder.md"}
[ -0.01917649246752262, 0.00209156540222466, -0.0024863029830157757, 0.09643885493278503, -0.0021704440005123615, -0.01535074133425951, 0.016996759921312332, 0.02109619416296482, 0.024535106495022774, 0.053694434463977814, -0.00612984923645854, 0.012265895493328571, 0.03910267725586891, 0.01...
e6e6b896-d394-4d8e-a790-b1287f77ad26
Extra columns that are selected in the query can be viewed in the expanded log row: Time series {#time-series} The time series query type is similar to table , but with a focus on time series data. The two views are mostly the same, with these notable differences: - A dedicated Time field. - In Aggregate mode...
{"source_file": "query-builder.md"}
[ -0.022095656022429466, -0.03239075094461441, 0.007855177856981754, 0.0763702243566513, -0.014702466316521168, 0.006236612796783447, -0.027436843141913414, 0.024137387052178383, 0.048905257135629654, 0.010050494223833084, 0.007351268548518419, -0.05338384211063385, -0.03164982795715332, 0.0...
9cb5071d-4b1e-4b41-80b8-b56f55a5e45e
The trace query type supports data links . | Field | Description | |----|----| | Trace Mode | Changes the query from Trace Search to Trace ID lookup. | | Use OTel | Enables OpenTelemetry columns. Will overwrite the selected columns to use columns defined by the selected OTel schema version (Disables column selection...
{"source_file": "query-builder.md"}
[ -0.09180589765310287, -0.05956374108791351, -0.08456944674253464, 0.04453536495566368, -0.06838320940732956, -0.08113797754049301, -0.02736021764576435, -0.011932672001421452, -0.02563396282494068, -0.009705672971904278, 0.022051431238651276, -0.04222242534160614, -0.006952309515327215, -0...
d3f58709-768c-44d9-8116-cb560f946008
If OpenTelemetry is enabled in a log or trace query, a trace ID column will be included automatically. By including a trace ID column, the " View Trace " and " View Logs " links will be attached to the data. Linking abilities {#linking-abilities} With the data links present, you can open traces and logs using...
{"source_file": "query-builder.md"}
[ 0.025415822863578796, -0.08675207942724228, -0.05050109326839447, 0.1119411289691925, 0.040575604885816574, 0.0013216338120400906, 0.04614570364356041, -0.006032389122992754, -0.009527930989861488, -0.031624626368284225, -0.005552250891923904, 0.0022768231574445963, 0.024098161607980728, -...
e1dbcdf5-0e85-48cd-a39d-47d091e91ea1
| Macro | Description | Output example ...
{"source_file": "query-builder.md"}
[ 0.0463205948472023, 0.06437702476978302, -0.006618929095566273, 0.01438852772116661, -0.03264516592025757, 0.07528968155384064, 0.03532673418521881, 0.05860888585448265, 0.026235060766339302, -0.0348186120390892, 0.01559611689299345, -0.08186733722686768, 0.00738520547747612, -0.0477271936...
a5a95081-9a86-4737-95eb-82aa897302c1
| $__toTime_ms | Replaced by the ending time of the panel range cast to a DateTime64 . | fromUnixTimestamp64Milli(1447328726456) | | $__timeInterval(colum...
{"source_file": "query-builder.md"}
[ 0.04010468348860741, 0.02849976345896721, -0.051090095192193985, 0.00929525401443243, -0.015015932731330395, 0.06246240809559822, 0.003108585486188531, 0.08842765539884567, -0.0071031940169632435, 0.02209365740418434, -0.02238929644227028, -0.10610245168209076, 0.010208048857748508, -0.030...
dee52084-ee6b-4b9b-be8b-4ba3d5b7948e
sidebar_label: 'Quick Start' sidebar_position: 1 slug: /integrations/grafana description: 'Introduction to using ClickHouse with Grafana' title: 'ClickHouse data source plugin for Grafana' show_related_blogs: true doc_type: 'guide' integration: - support_level: 'partner' - category: 'data_visualization' - website...
{"source_file": "index.md"}
[ -0.09041120111942291, 0.0035623875446617603, -0.07097353041172028, 0.019235141575336456, -0.0613352470099926, -0.028556309640407562, -0.008357150480151176, 0.010819785296916962, -0.07914819568395615, 0.01808328367769718, 0.039939381182193756, -0.045520566403865814, 0.03223831206560135, -0....
9ad8c3f8-29dd-4b43-a387-3f06a34a7b1c
On the next screen, click the Install button: 4. Define a ClickHouse data source {#4-define-a-clickhouse-data-source} Once the installation is complete, click the Add new data source button. (You can also add a data source from the Data sources tab on the Connections page.) Either scroll d...
{"source_file": "index.md"}
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52dddd26-c5c3-4ef2-bd87-6cc6faf8bdf4
sidebar_label: 'Go' sidebar_position: 1 keywords: ['clickhouse', 'go', 'client', 'golang'] slug: /integrations/go description: 'The Go clients for ClickHouse allows users to connect to ClickHouse using either the Go standard database/sql interface or an optimized native interface.' title: 'ClickHouse Go' doc_type: 'ref...
{"source_file": "index.md"}
[ 0.02933814935386181, -0.011773264966905117, -0.09473123401403427, 0.0038542000111192465, -0.11064542084932327, 0.03795555233955383, 0.06998895108699799, 0.052205830812454224, -0.13273003697395325, -0.06811246275901794, 0.029473448172211647, -0.03644883632659912, 0.06598342210054398, 0.0238...
905274f4-2faa-4aba-8716-9ede146e4c75
if err != nil { return nil, err } if err := conn.Ping(ctx); err != nil { if exception, ok := err.(*clickhouse.Exception); ok { fmt.Printf("Exception [%d] %s \n%s\n", exception.Code, exception.Message, exception.StackTrace) } return nil, err ...
{"source_file": "index.md"}
[ 0.027705945074558258, 0.022493980824947357, -0.0592329204082489, -0.006525856908410788, -0.04032609984278679, -0.06607135385274887, 0.03679738938808441, 0.0370384082198143, -0.03158872202038765, -0.06298309564590454, 0.020824506878852844, -0.049132101237773895, -0.05531872808933258, 0.0344...
0975f6f2-af11-4122-882b-90315fc3f41b
When choosing a client library, users should be aware of their respective pros and cons - see Choosing a Client Library. | | Native format | Native protocol | HTTP protocol | Row Orientated API | Column Orientated API | Type flexibility | Compression | Query Placeholders | |:-------------:|:------------...
{"source_file": "index.md"}
[ -0.10247790813446045, 0.07085651904344559, -0.05938427150249481, -0.013575919903814793, -0.009987562894821167, -0.022129632532596588, -0.05854491889476776, 0.007456020452082157, 0.03781191259622574, -0.026927107945084572, -0.037697684019804, 0.019557103514671326, 0.044143516570329666, 0.01...
440955d3-68bc-44b9-b293-c4a8ab64076c
Both interfaces encode data using the native format and native protocol for communication. Additionally, the standard interface supports communication over HTTP. | | Native format | Native protocol | HTTP protocol | Bulk write support | Struct marshaling | Compression | Query Placeholders | |:---...
{"source_file": "index.md"}
[ -0.042043134570121765, -0.011354943737387657, -0.10859565436840057, -0.0008395086624659598, -0.05921675264835358, -0.0740339383482933, -0.017913756892085075, -0.025239737704396248, -0.08937785029411316, -0.08595722168684006, 0.03307635709643364, -0.038917236030101776, 0.06386927515268326, ...
1ab0084e-ed4d-4350-bcf5-fe941f07f829
Note we use the default native port to connect. go conn, err := clickhouse.Open(&clickhouse.Options{ Addr: []string{fmt.Sprintf("%s:%d", env.Host, env.Port)}, Auth: clickhouse.Auth{ Database: env.Database, Username: env.Username, Password: env.Password, }, }) if err != nil { re...
{"source_file": "index.md"}
[ 0.0035053235478699207, -0.01599114015698433, -0.14720945060253143, -0.03573094308376312, -0.08942313492298126, -0.04534660652279854, -0.001539324875921011, 0.021011827513575554, -0.042365144938230515, -0.04737504944205284, 0.06358204036951065, 0.009601124562323093, -0.006338471546769142, 0...
c3aa680c-75f5-4895-8bb4-9f6f101fcf20
go conn, err := clickhouse.Open(&clickhouse.Options{ Addr: []string{fmt.Sprintf("%s:%d", env.Host, env.Port)}, Auth: clickhouse.Auth{ Database: env.Database, Username: env.Username, Password: env.Password, }, DialContext: func(ctx context.Context, addr string) (net.Conn, error) {...
{"source_file": "index.md"}
[ -0.01428529154509306, 0.010371439158916473, -0.09965711086988449, -0.03991790860891342, -0.06641419976949692, -0.0751820057630539, -0.012017474509775639, 0.06859243661165237, -0.012059852480888367, -0.02713671699166298, 0.021495046094059944, -0.032938402146101, -0.045485444366931915, 0.035...
e20eabcf-ce5d-445f-81f8-62b0fbe7be2b
go env, err := GetNativeTestEnvironment() if err != nil { return err } cwd, err := os.Getwd() if err != nil { return err } t := &tls.Config{} caCert, err := ioutil.ReadFile(path.Join(cwd, "../../tests/resources/CAroot.crt")) if err != nil { return err } caCertPool := x509.NewCertPool() successful := caCertP...
{"source_file": "index.md"}
[ 0.010351181961596012, 0.06757372617721558, -0.09809337556362152, 0.009889434091746807, -0.004346109461039305, -0.11016938835382462, 0.03306557610630989, 0.05936867371201515, 0.0010928751435130835, -0.03469455614686012, 0.06197724863886833, -0.15474270284175873, 0.023149680346250534, 0.0757...
06ac1560-f40f-4357-a0a2-8cbe01d0133a
Full Example Two connection strategies are available: ConnOpenInOrder (default) - addresses are consumed in order. Later addresses are only utilized in case of failure to connect using addresses earlier in the list. This is effectively a failure-over strategy. ConnOpenRoundRobin - Load is balanced across the...
{"source_file": "index.md"}
[ 0.012482287362217903, -0.005614349618554115, -0.1134883463382721, 0.021288609132170677, -0.0731198713183403, -0.052505385130643845, 0.008387643843889236, -0.012318192049860954, -0.02345358580350876, 0.0063097248785197735, 0.008310288190841675, 0.05895952507853508, 0.021342959254980087, 0.0...
9a47e13b-2b68-4d37-a1fe-9493397eb49a
batch, err := conn.PrepareBatch(ctx, "INSERT INTO example") if err != nil { return err } defer batch.Close() for i := 0; i < 1000; i++ { err := batch.Append( uint8(42), "ClickHouse", "Inc", uuid.New(), map[string]uint8{"key": 1}, // Map(String, UInt8) ...
{"source_file": "index.md"}
[ -0.026033876463770866, 0.024075128138065338, -0.03481355309486389, 0.027206484228372574, -0.11952167749404907, -0.045376844704151154, 0.10496600717306137, -0.010847741737961769, -0.09798358380794525, -0.03503434360027313, 0.05725761130452156, -0.031914420425891876, 0.061691541224718094, -0...
8e7f63ea-509a-4a77-9f53-8f553c349b94
Full Example Note in both cases, we are required to pass a pointer to the variables we wish to serialize the respective column values into. These must be passed in the order specified in the SELECT statement - by default, the order of column declaration will be used in the event of a SELECT * as shown above. Si...
{"source_file": "index.md"}
[ -0.027195360511541367, 0.02764158882200718, -0.17251110076904297, 0.07790055125951767, -0.07477673888206482, 0.009697736240923405, 0.06035579368472099, 0.03540607541799545, -0.03929069638252258, -0.05668863654136658, 0.02567516826093197, 0.026869257912039757, 0.06592537462711334, -0.008910...
46e21dbc-d47b-4639-93d5-33b3bfce7c5b
return batch.Send() ``` Full Example Using structs {#using-structs} For users, Golang structs provide a logical representation of a row of data in ClickHouse. To assist with this, the native interface provides several convenient functions. Select with serialize {#select-with-serialize} The Select method allow...
{"source_file": "index.md"}
[ 0.021433202549815178, 0.016752948984503746, -0.10973105579614639, 0.043815214186906815, -0.05109797418117523, -0.0911555215716362, 0.0954541489481926, 0.0652245357632637, -0.10215144604444504, -0.07247000187635422, 0.04475915804505348, -0.007034833077341318, -0.01499274093657732, 0.0336517...
92909d04-bebf-4923-957c-26acb14c826f
The type conversions currently supported for primitive types are captured here . This effort is ongoing and can be separated into insertion ( Append / AppendRow ) and read time (via a Scan ). Should you need support for a specific conversion, please raise an issue. Complex types {#complex-types} Date/DateTime t...
{"source_file": "index.md"}
[ 0.05447590723633766, 0.005944777745753527, -0.09706360101699829, 0.01763804256916046, -0.05051379278302193, 0.011362305842339993, 0.01914202608168125, 0.03954727202653885, -0.07642097026109695, -0.028916098177433014, -0.03057924285531044, -0.05782131105661392, 0.01650054007768631, 0.019538...
3c771201-da96-4e4a-85c7-7e1f0f9441b6
Full Example Map {#map} Maps should be inserted as Golang maps with keys and values conforming to the type rules defined earlier . ```go batch, err := conn.PrepareBatch(ctx, "INSERT INTO example") if err != nil { return err } defer batch.Close() var i int64 for i = 0; i < 10; i++ { err := batch.Append(...
{"source_file": "index.md"}
[ 0.07012470066547394, 0.051135748624801636, -0.017094753682613373, -0.029130740091204643, -0.13518498837947845, 0.008825501427054405, 0.028255226090550423, 0.044811833649873734, -0.10640321671962738, -0.049873825162649155, 0.07072976231575012, -0.015825975686311722, -0.019294319674372673, -...
e2f94e3d-4e49-47cf-a274-8c5b362d2579
Full Example Note: typed slices and maps are supported, provide the sub-columns in the named tuple are all of the same types. Nested {#nested} A Nested field is equivalent to an Array of named Tuples. Usage depends on whether the user has set flatten_nested to 1 or 0. By setting flatten_nested to 0, Nested co...
{"source_file": "index.md"}
[ 0.02945834770798683, 0.014781526289880276, -0.056001823395490646, 0.0019394056871533394, -0.020590685307979584, -0.04634776711463928, 0.03282848373055458, 0.027473313733935356, -0.12005428969860077, -0.017985733225941658, 0.024525802582502365, -0.0722922682762146, -0.01235067006200552, 0.0...
823e1f81-3e89-46e9-a0e9-f6d7f3069d3b
Full Example - flatten_tested=0 If the default value of 1 is used for flatten_nested , nested columns are flattened to separate arrays. This requires using nested slices for insertion and retrieval. While arbitrary levels of nesting may work, this is not officially supported. ``go conn, err := GetNativeConnection...
{"source_file": "index.md"}
[ 0.015324954874813557, -0.06344723701477051, -0.06856007128953934, 0.06246855854988098, -0.015864934772253036, -0.09391729533672333, 0.02372748777270317, 0.07182369381189346, -0.11440416425466537, -0.02491012029349804, 0.03119581565260887, -0.05614802613854408, -0.018226031213998795, 0.0069...
0bad8ac4-b2f7-4d5a-89b1-45553ebbeafd
batch, err := conn.PrepareBatch(ctx, "INSERT INTO example") if err != nil { return err } defer batch.Close() if err = batch.Append( orb.Point{11, 22}, orb.Ring{ orb.Point{1, 2}, orb.Point{1, 2}, }, orb.Polygon{ orb.Ring{ orb.Point{1, 2}, orb.Point{12...
{"source_file": "index.md"}
[ 0.023549439385533333, 0.016673492267727852, -0.04227771610021591, -0.02127949893474579, -0.034248512238264084, -0.08577936142683029, 0.10728122293949127, -0.02346721477806568, -0.03089054301381111, -0.044536370784044266, 0.029122713953256607, -0.01135391928255558, 0.04669102653861046, -0.0...
cce55273-a791-4f1a-bce7-c91d6c0bb812
if err = batch.Send(); err != nil { return err } var ( col1 decimal.Decimal col2 decimal.Decimal col3 decimal.Decimal col4 decimal.Decimal col5 decimal.Decimal ) if err = conn.QueryRow(ctx, "SELECT * FROM example").Scan(&col1, &col2, &col3, &col4, &col5); err != nil { return err } fmt.Pr...
{"source_file": "index.md"}
[ 0.0033194595016539097, 0.015889709815382957, -0.12640489637851715, 0.08134742081165314, -0.06568832695484161, -0.05177063122391701, 0.052054956555366516, 0.05106634646654129, -0.09174322336912155, -0.03336142748594284, 0.018789179623126984, -0.06009935587644577, -0.024705585092306137, -0.0...
81c799d9-834f-462d-bf40-18e0371caa4c
batch, err := conn.PrepareBatch(ctx, "INSERT INTO example") if err != nil { return err } defer batch.Close() col1Data, _ := new(big.Int).SetString("170141183460469231731687303715884105727", 10) col2Data := big.NewInt(128) col3Data := [] big.Int{ big.NewInt(-128), big.NewInt(128128), big.NewInt(1281281...
{"source_file": "index.md"}
[ 0.022855505347251892, -0.021618790924549103, -0.04279362037777901, -0.003643104573711753, -0.0962074026465416, -0.08235635608434677, -0.03219741955399513, 0.031040582805871964, -0.12010084092617035, 0.004326505120843649, -0.0016071520512923598, -0.039485443383455276, 0.0012269065482541919, ...
19104ff4-a6dc-46b7-bc18-9a48d196ac73
go var count uint64 // positional bind if err = conn.QueryRow(ctx, "SELECT count() FROM example WHERE Col1 >= ? AND Col3 < ?", 500, now.Add(time.Duration(750)*time.Second)).Scan(&count); err != nil { return err } // 250 fmt.Printf("Positional bind count: %d\n", count) // numeric bind if err = conn.QueryRow(ctx, "SE...
{"source_file": "index.md"}
[ 0.06351649761199951, -0.038680631667375565, -0.06859367340803146, 0.03331071138381958, -0.09938305616378784, -0.01181596890091896, 0.04316822066903114, 0.05601617321372032, 0.013871475122869015, -0.03398120403289795, 0.025354323908686638, -0.032985687255859375, 0.061499692499637604, -0.048...
a66db880-a057-40d4-82c6-8742b485a333
Full Example Using context {#using-context} Go contexts provide a means of passing deadlines, cancellation signals, and other request-scoped values across API boundaries. All methods on a connection accept a context as their first variable. While previous examples used context.Background(), users can use this capab...
{"source_file": "index.md"}
[ -0.07447312772274017, 0.053038280457258224, -0.09445880353450775, 0.0011893005575984716, -0.10645310580730438, -0.01145562157034874, 0.11256017535924911, 0.007795796263962984, 0.010263302363455296, -0.02567017823457718, -0.000204453244805336, -0.03900031000375748, 0.05643922835588455, -0.0...
95175900-40bc-480b-b5dd-aef91c6802ab
// set a deadline for a query - this will cancel the query after the absolute time is reached. // queries will continue to completion in ClickHouse ctx, cancel = context.WithDeadline(context.Background(), time.Now().Add(-time.Second)) defer cancel() if err := conn.Ping(ctx); err == nil { return fmt.Errorf("expected...
{"source_file": "index.md"}
[ -0.019716624170541763, 0.022941388189792633, -0.017239956185221672, 0.05916881561279297, -0.02019413746893406, -0.0988713949918747, 0.060401059687137604, -0.02699941396713257, -0.006485366728156805, -0.008610839024186134, -0.0018992341356351972, -0.04463280364871025, -0.017245711758732796, ...
ef25dfaf-d6ca-4a7e-a7ff-21e66e2a0f79
fmt.Printf("Total Rows: %d\n", totalRows) rows.Close() ``` Full Example Dynamic scanning {#dynamic-scanning} Users may need to read tables for which they do not know the schema or type of the fields being returned. This is common in cases where ad-hoc data analysis is performed or generic tooling is written. To a...
{"source_file": "index.md"}
[ 0.04659042879939079, 0.06082179769873619, -0.09602165967226028, 0.12619540095329285, -0.03290199488401413, -0.07608916610479355, 0.09968782216310501, 0.07577106356620789, -0.08686578273773193, -0.05839169770479202, -0.0064473142847418785, 0.007447259500622749, -0.03199922293424606, 0.00436...
0872eec0-e485-4769-bd62-f7dc6b8cd7f7
var count uint64 if err := conn.QueryRow(ctx, "SELECT COUNT( ) FROM external_table_1").Scan(&count); err != nil { return err } fmt.Printf("external_table_1: %d\n", count) if err := conn.QueryRow(ctx, "SELECT COUNT( ) FROM external_table_2").Scan(&count); err != nil { return err } fmt.Printf("external_table_2: %...
{"source_file": "index.md"}
[ 0.038089554756879807, -0.02472592331469059, -0.07472044974565506, 0.06062643602490425, -0.007999022491276264, -0.09972554445266724, 0.09605559706687927, 0.09076593816280365, -0.048997074365615845, -0.02567649818956852, 0.06426502019166946, -0.06355327367782593, 0.06485534459352493, -0.0585...
eb48fbea-e41d-4ab4-a4aa-de105e050047
```go func Connect() error { env, err := GetStdTestEnvironment() if err != nil { return err } conn := clickhouse.OpenDB(&clickhouse.Options{ Addr: []string{fmt.Sprintf("%s:%d", env.Host, env.Port)}, Auth: clickhouse.Auth{ ...
{"source_file": "index.md"}
[ 0.03280875086784363, -0.052622389048337936, -0.11085986346006393, -0.014051140286028385, -0.06049586832523346, -0.03749197721481323, 0.015992091968655586, 0.03717736899852753, -0.05492662265896797, -0.018330244347453117, 0.016871510073542595, -0.035793159157037735, -0.021083056926727295, 0...
d6fb7607-4534-4ffe-9797-cf9905fac97f
skip_verify - skip certificate verification (default is false ) block_buffer_size - allows users to control the block buffer size. See BlockBufferSize . (default is 2 ) go func ConnectSettings() error { env, err := GetStdTestEnvironment() if err != nil { return err } ...
{"source_file": "index.md"}
[ 0.025048233568668365, 0.061572857201099396, -0.11743662506341934, -0.00870101060718298, -0.008334146812558174, -0.08529640734195709, 0.07009485363960266, 0.020910998806357384, -0.061027493327856064, -0.020494403317570686, 0.023733731359243393, -0.024415744468569756, -0.005877216812223196, ...
3398cefb-f497-432c-98e5-dfb58f2e915f
For DSN-based connections, the string accepts multiple hosts and a connection_open_strategy parameter for which the value round_robin or in_order can be set. ```go func MultiStdHost() error { env, err := GetStdTestEnvironment() if err != nil { return err } conn, e...
{"source_file": "index.md"}
[ 0.02618490718305111, -0.023439079523086548, -0.14019536972045898, -0.010950186289846897, -0.08456610888242722, -0.06327734887599945, 0.00012777688971254975, 0.029434440657496452, -0.04607071354985237, -0.032949671149253845, -0.00918519962579012, -0.0038725584745407104, -0.026763824746012688,...
dbbe5178-19f7-4c9c-bdb2-95f58aaa6509
} func ConnectDSNSSL() error { env, err := GetStdTestEnvironment() if err != nil { return err } conn, err := sql.Open("clickhouse", fmt.Sprintf("https://%s:%d?secure=true&skip_verify=true&username=%s&password=%s", env.Host, env.HttpsPort, env.Username, env.Password)) ...
{"source_file": "index.md"}
[ -0.04417688399553299, -0.01685931347310543, -0.13119155168533325, -0.000826966657768935, -0.049510207027196884, -0.06655293703079224, 0.03235604986548424, 0.06388821452856064, -0.021273503080010414, -0.03750044107437134, -0.01147119514644146, -0.009144757874310017, 0.024763982743024826, 0....
c89a2f70-5943-4baa-86ce-36f70538648e
go batch, err := scope.Prepare("INSERT INTO example") if err != nil { return err } for i := 0; i < 1000; i++ { _, err := batch.Exec( uint8(42), "ClickHouse", "Inc", uuid.New(), map[string]uint8{"key": 1}, // Map(String, UInt8) []string{"Q", "W", "E", "R", "T",...
{"source_file": "index.md"}
[ 0.003971728961914778, 0.03707234561443329, -0.026000095531344414, 0.015745069831609726, -0.1090526357293129, -0.024838274344801903, 0.09136952459812164, -0.01993914507329464, -0.10384131222963333, -0.01242354791611433, 0.05925694853067398, -0.029770782217383385, 0.013055162504315376, -0.00...
e67b17c3-0598-4e64-81d1-591fa602a603
go const ddl = ` CREATE TABLE example ( Col1 UInt64 , Col2 String , Col3 Array(UInt8) , Col4 DateTime ) ENGINE = Memory ` if _, err := conn.Exec(ddl); err != nil { return err } ctx := clickhouse.Context(context.Background(), clickhouse.WithStdAsync(false)) { for i...
{"source_file": "index.md"}
[ 0.02989455871284008, -0.02396346814930439, -0.11974504590034485, 0.03606473281979561, -0.0657220110297203, -0.046331290155649185, 0.045557718724012375, 0.07690586894750595, -0.07218274474143982, -0.01811189390718937, 0.05474970489740372, -0.032121866941452026, 0.002234425861388445, -0.0200...
5c662182-2dd8-4f17-9e98-a3937f3889b8
Full Example Insert behavior is the same as the ClickHouse API. Compression {#compression-1} The standard API supports the same compression algorithms as native ClickHouse API i.e. lz4 and zstd compression at a block level. In addition, gzip, deflate and br compression are supported for HTTP connections. If...
{"source_file": "index.md"}
[ -0.0743727907538414, 0.00485199736431241, -0.11024242639541626, 0.06649938225746155, -0.009795483201742172, -0.07377006858587265, -0.028587084263563156, -0.004101582802832127, -0.005764069501310587, -0.03700092434883118, -0.057529184967279434, 0.08003205060958862, 0.038591522723436356, -0....
0baf358e-add3-4cb6-94ba-bea2661a6b46
go var count uint64 // positional bind if err = conn.QueryRow(ctx, "SELECT count() FROM example WHERE Col1 >= ? AND Col3 < ?", 500, now.Add(time.Duration(750)*time.Second)).Scan(&count); err != nil { return err } // 250 fmt.Printf("Positional bind count: %d\n", count) // numeric bind if err = conn.QueryRow(ctx, "SE...
{"source_file": "index.md"}
[ 0.06351649761199951, -0.038680631667375565, -0.06859367340803146, 0.03331071138381958, -0.09938305616378784, -0.01181596890091896, 0.04316822066903114, 0.05601617321372032, 0.013871475122869015, -0.03398120403289795, 0.025354323908686638, -0.032985687255859375, 0.061499692499637604, -0.048...
efa4fc4e-0e98-48a2-84d6-03f00933b0a3
// set a query id to assist tracing queries in logs e.g. see system.query_log var one uint8 ctx = clickhouse.Context(context.Background(), clickhouse.WithQueryID(uuid.NewString())) if err = conn.QueryRowContext(ctx, "SELECT 1").Scan(&one); err != nil { return err } conn.ExecContext(context.Background(), "DROP QUO...
{"source_file": "index.md"}
[ -0.07554128021001816, -0.011798392049968243, -0.06567132472991943, 0.06040661409497261, -0.08185736835002899, -0.056343924254179, 0.14927950501441956, 0.008057528175413609, 0.03409494459629059, -0.003939390182495117, -0.02070096880197525, -0.0970120057463646, 0.05744178593158722, -0.029521...
78e83bb4-a366-40fc-9037-3e904934a30e
Full Example Dynamic scanning {#dynamic-scanning-1} Similar to the ClickHouse API , column type information is available to allow users to create runtime instances of correctly typed variables which can be passed to Scan. This allows columns to be read where the type is not known. go const query = ` SELECT ...
{"source_file": "index.md"}
[ 0.020243195816874504, 0.01417178101837635, -0.10330481827259064, 0.09404585510492325, -0.03488845005631447, -0.04794951155781746, 0.08412451297044754, 0.039159249514341354, -0.10803943127393723, -0.09106161445379257, -0.010881495662033558, 0.018230395391583443, 0.004671749658882618, 0.0375...
893bbe64-b082-4329-8098-d1c01f58648b
Full Example Open telemetry {#open-telemetry-1} ClickHouse allows a trace context to be passed as part of the native protocol. The client allows a Span to be created via the function clickhouse.withSpan and passed via the Context to achieve this. This is not supported when HTTP is used as transport. go var co...
{"source_file": "index.md"}
[ 0.02855968475341797, -0.040726691484451294, -0.0913168415427208, 0.04164661094546318, -0.03433360531926155, -0.07976523041725159, 0.12203458696603775, 0.005645619705319405, 0.0016672107158228755, -0.03705984726548195, 0.027598228305578232, 0.013461645692586899, 0.01766490936279297, -0.0128...
28afcb16-2887-4d61-852a-064cef47a318
sidebar_label: 'Advanced Inserting' sidebar_position: 5 keywords: ['clickhouse', 'python', 'insert', 'advanced'] description: 'Advanced Inserting with ClickHouse Connect' slug: /integrations/language-clients/python/advanced-inserting title: 'Advanced Inserting' doc_type: 'reference' Inserting data with ClickHouse C...
{"source_file": "advanced-inserting.md"}
[ -0.025435741990804672, -0.022029587998986244, -0.04109521210193634, 0.0724455937743187, -0.09740090370178223, -0.018320027738809586, 0.023171190172433853, 0.02975141815841198, -0.0626935139298439, -0.011199683882296085, 0.06944604218006134, 0.0023938820231705904, 0.11033493280410767, -0.06...
e9494216-837d-4d3a-89ef-529f7d0d0155
| ClickHouse Type | Native Python Type | Write Formats | Comments | |-----------------------|-------------------------|-------------------|-------------------------------------------------------------------...
{"source_file": "advanced-inserting.md"}
[ -0.023651115596294403, 0.0011578816920518875, -0.13633474707603455, -0.008949181996285915, -0.05894972011446953, -0.10561346262693405, 0.013333704322576523, 0.04760371148586273, -0.06549476832151413, -0.054204218089580536, 0.010586608201265335, -0.08680595457553864, 0.025954168289899826, 0...
66980582-e6e0-4087-b19c-c8098ec71d6a
| DateTime64 | datetime.datetime | int | Python datetime.datetime is limited to microsecond precision. The raw 64 bit int value is available | | Time | datetime.timedelta | int, string, time | ClickHouse stores DateTime in epoch seconds. int types will be ass...
{"source_file": "advanced-inserting.md"}
[ -0.02253599837422371, 0.02101954258978367, -0.03616553917527199, -0.018679574131965637, -0.09128992259502411, -0.06673648208379745, -0.10405107587575912, -0.01128420140594244, -0.03306521847844124, -0.041469208896160126, 0.005107345059514046, -0.044400617480278015, -0.048720259219408035, -...
3658c952-95dd-401b-9a1f-1e7b2aaff922
Specialized insert methods {#specialized-insert-methods} ClickHouse Connect provides specialized insert methods for common data formats: insert_df -- Insert a Pandas DataFrame. Instead of a Python Sequence of Sequences data argument, the second parameter of this method requires a df argument that must be a P...
{"source_file": "advanced-inserting.md"}
[ -0.02721036970615387, -0.14681392908096313, -0.12725314497947693, 0.006647138856351376, -0.07895257323980331, -0.07791635394096375, -0.05322285741567612, -0.03508380427956581, -0.0642232745885849, 0.0013184247072786093, 0.04784364625811577, 0.06768833845853806, -0.03738163039088249, 0.0083...
c64bc98b-de91-4b91-ad7f-06d948bbcc33
Timezone-aware datetime objects {#timezone-aware-datetime-objects} If you insert a timezone-aware Python datetime.datetime object, ClickHouse Connect will automatically call .timestamp() to convert it to a Unix timestamp, which correctly accounts for the timezone offset. This means you can insert datetime objects...
{"source_file": "advanced-inserting.md"}
[ 0.04864205792546272, -0.04216340556740761, -0.03774641454219818, 0.018343614414334297, 0.012840560637414455, -0.08649180084466934, -0.008075088262557983, -0.03175313025712967, 0.018469762057065964, 0.0025973618030548096, -0.038413140922784805, -0.05742170289158821, -0.08186522126197815, 0....
91af8dd2-5923-4c42-af2c-650d0c452c72
DateTime columns with timezone metadata {#datetime-columns-with-timezone-metadata} ClickHouse columns can be defined with timezone metadata (e.g., DateTime('America/Denver') or DateTime64(3, 'Asia/Tokyo') ). This metadata doesn't affect how data is stored (still as UTC timestamps), but it controls the timezone use...
{"source_file": "advanced-inserting.md"}
[ 0.10242974758148193, -0.04610525071620941, -0.07141166180372238, 0.008131883107125759, 0.0016085626557469368, -0.10208522528409958, -0.00995299220085144, -0.027424132451415062, 0.022461656481027603, 0.008207297883927822, 0.014313954859972, -0.03216699883341789, -0.041811518371105194, 0.028...
bf813995-d6b4-4421-9211-fbedc4e081c9
| Parameter | Type | Default | Description | |--------------|-----------------|-------------------|---------------------------------------------------------------------------------------...
{"source_file": "advanced-inserting.md"}
[ -0.0005824867403134704, -0.03332158923149109, -0.12375921756029129, 0.02682046964764595, -0.1035052090883255, 0.019171463325619698, 0.030128998681902885, 0.025187982246279716, -0.03856927901506424, 0.02255917340517044, 0.06785313785076141, -0.09197982400655746, 0.12386184185743332, -0.0508...
dc566e53-3dc9-44a0-8c01-dad39587da91
sidebar_label: 'SQLAlchemy' sidebar_position: 7 keywords: ['clickhouse', 'python', 'sqlalchemy', 'integrate'] description: 'ClickHouse SQLAlchemy Support' slug: /integrations/language-clients/python/sqlalchemy title: 'SQLAlchemy Support' doc_type: 'reference' ClickHouse Connect includes a SQLAlchemy dialect ( click...
{"source_file": "sqlalchemy.md"}
[ -0.013024838641285896, -0.06132502108812332, -0.08103258162736893, 0.04322221875190735, -0.08707565069198608, -0.06188341602683067, 0.03920846804976463, 0.02364172600209713, -0.1149633526802063, -0.06598424166440964, -0.038753122091293335, 0.022519521415233612, 0.11845008283853531, -0.0158...
4c95d483-e0ce-4825-a4ca-45bb2bfdb39f
with engine.begin() as conn: # Databases conn.execute(CreateDatabase("example_db", exists_ok=True)) # Tables metadata = MetaData(schema="example_db") table = db.Table( "events", metadata, db.Column("id", UInt32, primary_key=True), db.Column("user", String), db.Column("created_at", DateTime...
{"source_file": "sqlalchemy.md"}
[ -0.0038758227601647377, -0.07588138431310654, -0.05607587844133377, 0.04574494808912277, -0.0762137696146965, -0.08883555978536606, -0.0019061649218201637, 0.012090845964848995, -0.06587543338537216, 0.011500939726829529, 0.027319058775901794, -0.03283055126667023, 0.06634580343961716, -0....
272c5847-3a0a-47dd-97c2-bfba9e58b3a4
Transactions and server features: Two-phase transactions, sequences, RETURNING , and advanced isolation levels are not supported. engine.begin() provides a Python context manager for grouping statements but performs no actual transaction control (commit/rollback are no-ops).
{"source_file": "sqlalchemy.md"}
[ -0.08006508648395538, -0.03859934210777283, -0.06372334063053131, 0.06168222799897194, -0.05575733259320259, -0.04303085431456566, 0.0013605505228042603, -0.051404569298028946, 0.02671508863568306, -0.04066172614693642, 0.08044490963220596, 0.05247000977396965, -0.026461811736226082, -0.02...
e1a2f355-2f42-457c-8b8d-b838e431f79a
sidebar_label: 'Driver API' sidebar_position: 2 keywords: ['clickhouse', 'python', 'driver', 'api', 'client'] description: 'ClickHouse Connect Driver API' slug: /integrations/language-clients/python/driver-api title: 'ClickHouse Connect Driver API' doc_type: 'reference' ClickHouse Connect driver API {#clickhouse-co...
{"source_file": "driver-api.md"}
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1f288010-d839-4f49-b196-409283ed4e59
| Parameter | Type | Default | Description ...
{"source_file": "driver-api.md"}
[ 0.03499232977628708, 0.05151437595486641, -0.03347549960017204, 0.01007634587585926, -0.08359705656766891, 0.042122550308704376, 0.027290377765893936, 0.04243069514632225, 0.0028166708070784807, -0.0498807393014431, 0.020550336688756943, -0.054090991616249084, -0.012340902350842953, -0.062...
cff95196-7fd9-497b-8042-6f2d2adbf4a9
| dsn | str | None | A string in standard DSN (Data Source Name) format. Other connection values (such as host or user) will be extracted from this string if not set otherwise. ...
{"source_file": "driver-api.md"}
[ -0.06050261855125427, -0.013577330857515335, -0.10453357547521591, 0.0710795670747757, -0.08160685747861862, -0.07360489666461945, -0.051160238683223724, 0.009344304911792278, -0.026363367214798927, -0.019071128219366074, -0.021394414827227592, 0.034676533192396164, 0.034311361610889435, -...
b15f52de-0164-4663-b9a1-5fa00a16d9ec
| https_proxy | str | None | HTTPS proxy address (equivalent to setting the HTTPS_PROXY environment variable). ...
{"source_file": "driver-api.md"}
[ -0.024272486567497253, 0.01524997316300869, -0.07438433915376663, -0.012548856437206268, -0.09832897782325745, -0.06110097095370293, -0.0499795638024807, -0.04645860940217972, -0.07455770671367645, -0.015191031619906425, -0.027524644508957863, -0.02901727706193924, 0.030231818556785583, -0...
72fed02a-fff8-4051-b324-1003a774ce43
HTTPS/TLS arguments {#httpstls-arguments} | Parameter | Type | Default | Description ...
{"source_file": "driver-api.md"}
[ -0.019003765657544136, 0.08503501862287521, 0.005065098404884338, -0.012156755663454533, -0.09321760386228561, -0.09741544723510742, -0.03376298025250435, -0.03584050014615059, 0.08466028422117233, -0.0679180771112442, -0.02089720219373703, -0.06855718046426773, 0.03869045525789261, -0.004...
6ea15df4-6b99-4d3d-ba5e-2bef7d9829f3
Settings argument {#settings-argument} Finally, the settings argument to get_client is used to pass additional ClickHouse settings to the server for each client request. Note that in most cases, users with readonly = 1 access cannot alter settings sent with a query, so ClickHouse Connect will drop such settings...
{"source_file": "driver-api.md"}
[ 0.005230261478573084, 0.024288715794682503, -0.07449445873498917, 0.05389169603586197, -0.09597151726484299, -0.03344239667057991, 0.03998967260122299, -0.019466714933514595, -0.029390016570687294, -0.03886514902114868, 0.0012738548684865236, -0.006422265432775021, 0.0635770633816719, -0.0...
f2506cd7-ca61-4eb9-b22f-8aefac0fe45f
```python import clickhouse_connect client = clickhouse_connect.get_client() print(client.server_version) Output: '22.10.1.98' ``` Connecting to a secure (HTTPS) external ClickHouse server ```python import clickhouse_connect client = clickhouse_connect.get_client(host='play.clickhouse.com', secure=True,...
{"source_file": "driver-api.md"}
[ 0.0475650392472744, -0.024417245760560036, -0.09339822828769684, -0.06091658025979996, -0.10048727691173553, -0.041703350841999054, -0.00846768356859684, -0.03840749338269234, 0.00411501619964838, -0.024132460355758667, -0.019632427021861076, 0.0001991791359614581, 0.007762175519019365, -0...
d991cb31-dd57-4015-8a34-6d1626367b23
To share a client across threads safely: ```python import clickhouse_connect import threading Option 1: Disable sessions (recommended for shared clients) client = clickhouse_connect.get_client( host='my-host', username='default', password='password', autogenerate_session_id=False # Required for t...
{"source_file": "driver-api.md"}
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9eeb71df-bdf0-473a-acbd-1a35c0cef83f
Several client methods use one or both of the common parameters and settings arguments. These keyword arguments are described below. Parameters argument {#parameters-argument} ClickHouse Connect Client query* and command methods accept an optional parameters keyword argument used for binding Python expres...
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Example with Python Sequence (Tuple), Float64, and IPv4Address ```python import ipaddress parameters = (35200.44, ipaddress.IPv4Address(0x443d04fe)) client.query('SELECT * FROM some_table WHERE metric >= %s AND ip_address = %s', parameters=parameters) ``` This generates the following query on the server: sql ...
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| Parameter | Type | Default | Description | |---------------|------------------|------------|-------------------------------------------------------------...
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Using client-side parameters table_name = "system" result = client.command( "SELECT count() FROM system.tables WHERE database = %(db)s", parameters={"db": table_name} ) Using server-side parameters result = client.command( "SELECT count() FROM system.tables WHERE database = {db:String}", parameter...
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| Parameter | Type | Default | Description | |---------------------|------------------|------------|----------------------------...
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| use_extended_dtypes | bool | True | Use Pandas extended dtypes (like StringArray), and pandas.NA and pandas.NaT for ClickHouse NULL values. Applies only to query_df and query_df_stream methods. | | external_data | ExternalData | None | An ExternalData object cont...
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Query examples {#query-examples} Basic query {#basic-query} ```python import clickhouse_connect client = clickhouse_connect.get_client() Simple SELECT query result = client.query("SELECT name, database FROM system.tables LIMIT 3") Access results as rows for row in result.result_rows: print(row) Outp...
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The QueryResult object {#the-queryresult-object} The base query method returns a QueryResult object with the following public properties: result_rows -- A matrix of the data returned in the form of a Sequence of rows, with each row element being a sequence of column values. result_columns -- A matrix of...
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| Parameter | Type | Default | Description | |--------------------|----------------------------------...
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Advanced Inserts (InsertContexts) | | transport_settings | dict | None | Optional dictionary of transport-level settings (HTTP headers, etc.) ...
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This method returns a "query summary" dictionary as described under the "command" method. An exception will be raised if the insert fails for any reason. For specialized insert methods that work with Pandas DataFrames, PyArrow Tables, and Arrow-backed DataFrames, see Advanced Inserting (Specialized Insert Methods) ....
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Exceptions {#exceptions} All custom exceptions (including those defined in the DB API 2.0 specification) are defined in the clickhouse_connect.driver.exceptions module. Exceptions actually detected by the driver will use one of these types. ClickHouse SQL utilities {#clickhouse-sql-utilities} The functions and ...
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keywords: ['clickhouse', 'python', 'client', 'connect', 'integrate'] slug: /integrations/python description: 'The ClickHouse Connect project suite for connecting Python to ClickHouse' title: 'Python Integration with ClickHouse Connect' doc_type: 'guide' integration: - support_level: 'core' - category: 'language_cli...
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This documentation is current as of the clickhouse-connect release 0.9.2. :::note The official ClickHouse Connect Python driver uses the HTTP protocol for communication with the ClickHouse server. This enables HTTP load balancer support and works well in enterprise environments with firewalls and proxies, but has sli...
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Support policy {#support-policy} Please update to the latest version of ClickHouse Connect before reporting any issues. Issues should be filed in the GitHub project . Future releases of ClickHouse Connect are intended be compatible with actively supported ClickHouse versions at the time of release. Actively supporte...
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sidebar_label: 'Advanced Usage' sidebar_position: 6 keywords: ['clickhouse', 'python', 'advanced', 'raw', 'async', 'threading'] description: 'Advanced Usage with ClickHouse Connect' slug: /integrations/language-clients/python/advanced-usage title: 'Advanced Usage' doc_type: 'reference' Advanced Usage {#advanced-usa...
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Client raw_insert method {#client-rawinsert-method} The Client.raw_insert method allows direct inserts of bytes objects or bytes object generators using the client connection. Because it does no processing of the insert payload, it is highly performant. The method provides options to specify settings and inse...
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Multithreaded, multiprocess, and async/event driven use cases {#multithreaded-multiprocess-and-asyncevent-driven-use-cases} ClickHouse Connect works well in multithreaded, multiprocess, and event-loop-driven/asynchronous applications. All query and insert processing occurs within a single thread, so operations are ge...
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By default, each query executed with a ClickHouse Connect Client instance uses that client's session ID. SET statements and temporary tables work as expected when using a single client. However, the ClickHouse server does not allow concurrent queries within the same session (the client will raise a ProgrammingErro...
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sidebar_label: 'Additional Options' sidebar_position: 3 keywords: ['clickhouse', 'python', 'options', 'settings'] description: 'Additional Options for ClickHouse Connect' slug: /integrations/language-clients/python/additional-options title: 'Additional Options' doc_type: 'reference' Additional options {#additional-...
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| Setting Name | Default | Options | Description ...
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| send_integration_tags | True | True, False | Include the used integration libraries/version (e.g. Pandas/SQLAlchemy/etc.) in client information sent to ClickHouse (HTTP User-Agent string). ...
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Compression {#compression} ClickHouse Connect supports lz4, zstd, brotli, and gzip compression for both query results and inserts. Always keep in mind that using compression usually involves a tradeoff between network bandwidth/transfer speed against CPU usage (both on the client and the server.) To receive compres...
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"Old" JSON data type {#old-json-data-type} The experimental Object (or Object('json') ) data type is deprecated and should be avoided in a production environment. ClickHouse Connect continues to provide limited support for the data type for backward compatibility. Note that this support does not include queries th...
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sidebar_label: 'Advanced Querying' sidebar_position: 4 keywords: ['clickhouse', 'python', 'query', 'advanced'] description: 'Advanced Querying with ClickHouse Connect' slug: /integrations/language-clients/python/advanced-querying title: 'Advanced Querying' doc_type: 'reference' Querying data with ClickHouse Connect...
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query_df_stream -- Returns each ClickHouse Block of query data as a Pandas DataFrame query_arrow_stream -- Returns query data in PyArrow RecordBlocks query_df_arrow_stream -- Returns each ClickHouse Block of query data as an arrow-backed Pandas DataFrame or a Polars DataFrame depending on the kwarg dataframe_li...
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StreamContexts {#streamcontexts} Each of the query_*_stream methods (like query_row_block_stream ) returns a ClickHouse StreamContext object, which is a combined Python context/generator. This is the basic usage: python with client.query_row_block_stream('SELECT pickup, dropoff, pickup_longitude, pickup_latitu...
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The query_df_stream method returns each ClickHouse Block as a two-dimensional Pandas DataFrame. Here's an example which shows that the StreamContext object can be used as a context in a deferred fashion (but only once). python df_stream = client.query_df_stream('SELECT * FROM hits') column_names = df_stream.sourc...
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Stream Arrow batches {#stream-arrow-batches} ```python import clickhouse_connect client = clickhouse_connect.get_client() Stream query results as Arrow record batches with client.query_arrow_stream("SELECT * FROM large_table") as stream: for arrow_batch in stream: # Process each Arrow batch ...
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query_df_arrow : Executes the query using the ClickHouse Arrow output format and returns a DataFrame. For dataframe_library='pandas' , returns a pandas 2.x DataFrame using Arrow‑backed dtypes ( pd.ArrowDtype ). This requires pandas 2.x and leverages zero‑copy buffers where possible for excellent performance and lo...
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Pandas requirement: Arrow‑backed dtypes require pandas 2.x. For older pandas versions, use query_df (non‑Arrow) instead. Strings vs binary: The use_strings option (when supported by the server setting output_format_arrow_string_as_string ) controls whether ClickHouse String columns are returned as Arrow string...
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The "data type" argument for any formatting function can include wildcards. The format is a single lower case string. Read formats can be set at several levels: Globally, using the methods defined in the clickhouse_connect.datatypes.format package. This will control the format of the configured datatype for all...
{"source_file": "advanced-querying.md"}
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ebc7df3d-30dc-4317-a0d6-9faef889b2ba
| ClickHouse Type | Native Python Type | Read Formats | Comments | |-----------------------|-------------------------|-------------------|-------------------------------------------------------------...
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e9db6adf-6710-46f7-b9f1-1c0526e53f31
| DateTime | datetime.datetime | int | ClickHouse stores DateTime in epoch seconds. This value is available as an int | | DateTime64 | datetime.datetime | int | Python datetime.datetime is limited to microsecond precision...
{"source_file": "advanced-querying.md"}
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e3d8dd83-5e30-4996-950c-73ab845d4946
External data {#external-data} ClickHouse queries can accept external data in any ClickHouse format. This binary data is sent along with the query string to be used to process the data. Details of the External Data feature are here . The client query* methods accept an optional external_data parameter to take ad...
{"source_file": "advanced-querying.md"}
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47383d93-50e3-4d57-98e9-20ce93dba87e
Additional external data files can be added to the initial ExternalData object using the add_file method, which takes the same parameters as the constructor. For HTTP, all external data is transmitted as part of a multi-part/form-data file upload. Time zones {#time-zones} There are multiple mechanisms for app...
{"source_file": "advanced-querying.md"}
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629bd7ee-c06f-4ab3-8345-02f822ee4e7b
title: 'Java' keywords: ['clickhouse', 'java', 'jdbc', 'client', 'integrate', 'r2dbc'] description: 'Options for connecting to ClickHouse from Java' slug: /integrations/java doc_type: 'reference' import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; import CodeBlock from '@theme/CodeBlock'; Java c...
{"source_file": "index.md"}
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21d14326-962b-4394-83e0-c33dadc4ebb3
| Data Type | Client V2 Support | Client V1 Support | |-----------------------|---------------------|---------------------| |Int8 |✔ |✔ | |Int16 |✔ |✔ | |Int32 |✔ ...
{"source_file": "index.md"}
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