id stringlengths 36 36 | document stringlengths 3 3k | metadata stringlengths 23 69 | embeddings listlengths 384 384 |
|---|---|---|---|
1860dc78-e572-447f-9fd4-e303cfc16173 | ββpart_keyββ¬βvalueββ¬βorderββ¬βframe_valuesββ
β 1 β 1 β 1 β [1] β
β 1 β 2 β 2 β [1,2] β
β 1 β 3 β 3 β [1,2,3] β
β 1 β 4 β 4 β [1,2,3,4] β
β 1 β 5 β 5 β [1,2,3,4,5] β
ββββββββββββ΄ββββββββ΄ββββββββ΄βββββββββββββββ
```
``sql
... | {"source_file": "index.md"} | [
0.012349079363048077,
-0.0446493998169899,
0.040256600826978683,
-0.01382570993155241,
0.0019102233927696943,
0.01975097879767418,
0.0708380788564682,
-0.037435486912727356,
-0.019014203920960426,
-0.002866913564503193,
-0.01949196495115757,
0.0709318220615387,
-0.05005841329693794,
-0.025... |
d9058381-72c9-4192-bc47-aa5ab5bc2c1a | ββpart_keyββ¬βvalueββ¬βorderββ¬βframe_valuesββ
β 1 β 1 β 1 β [1,2,3,4,5] β
β 1 β 2 β 2 β [1,2,3,4,5] β
β 1 β 3 β 3 β [2,3,4,5] β
β 1 β 4 β 4 β [3,4,5] β
β 1 β 5 β 5 β [4,5] β
ββββββββββββ΄ββββββββ΄ββββββββ΄βββββββββββββββ
```
```sql... | {"source_file": "index.md"} | [
0.016282519325613976,
-0.08551058173179626,
0.017352726310491562,
-0.0051254876889288425,
0.014854195527732372,
0.01949893683195114,
0.09510215371847153,
-0.05508635565638542,
-0.032722752541303635,
-0.03089872933924198,
-0.05828210711479187,
0.04006544500589371,
-0.059375494718551636,
-0.... |
360943be-7019-4c5d-9651-2e4b48caf2d4 | ββframe_values_1ββ¬βsecond_valueββ
β [1] β 0 β
β [1,2] β 2 β
β [1,2,3] β 2 β
β [1,2,3,4] β 2 β
β [2,3,4,5] β 3 β
ββββββββββββββββββ΄βββββββββββββββ
```
```sql
-- second value within the frame + Null for missing values
SELECT
... | {"source_file": "index.md"} | [
-0.010763827711343765,
-0.031320855021476746,
-0.035279154777526855,
0.02220837213099003,
-0.017308516427874565,
-0.024483080953359604,
0.048685550689697266,
-0.07929205894470215,
-0.053136199712753296,
-0.003054676577448845,
0.036088861525058746,
-0.03730335831642151,
-0.03312431648373604,
... |
f95870b8-2e3c-41b9-84b9-df59eb47c0ab | Cumulative sum {#cumulative-sum}
``sql
CREATE TABLE warehouse
(
item
String,
ts
DateTime,
value` Float
)
ENGINE = Memory
INSERT INTO warehouse VALUES
('sku38', '2020-01-01', 9),
('sku38', '2020-02-01', 1),
('sku38', '2020-03-01', -4),
('sku1', '2020-01-01', 1),
('sku1', '2020-02-01', 1),
('s... | {"source_file": "index.md"} | [
-0.013832993805408478,
0.005976438522338867,
-0.00478363549336791,
0.04995444416999817,
-0.09881352633237839,
0.03664303943514824,
0.04177113249897957,
0.0020085040014237165,
0.017429064959287643,
0.049956005066633224,
0.06460760533809662,
-0.07806475460529327,
0.01485387422144413,
-0.0135... |
91f683d6-4bd4-4b07-8aff-fcaf66cfe3ba | ββmetricββββ¬ββββββββββββββββββtsββ¬βvalueββ¬βmoving_avg_10_seconds_tempββ
β cpu_temp β 2020-01-01 00:00:00 β 87 β 87 β
β cpu_temp β 2020-01-01 00:01:10 β 77 β 77 β
β cpu_temp β 2020-01-01 00:02:20 β 93 β 93 β
β cpu_temp β 2020-01-01 00:03:30... | {"source_file": "index.md"} | [
-0.025427548214793205,
-0.04846914857625961,
-0.003163822228088975,
0.0718066394329071,
-0.02259908616542816,
-0.027835531160235405,
0.055639129132032394,
0.013055290095508099,
-0.020274575799703598,
0.019693640992045403,
0.018731215968728065,
-0.0796278566122055,
0.0038821145426481962,
0.... |
275ca35d-9b66-4cc5-94b7-2a9ff044cd91 | ββmetricββββββββ¬ββββββββββββββββββtsββ¬βvalueββ¬βmoving_avg_10_days_tempββ
β ambient_temp β 2020-01-01 00:00:00 β 16 β 16 β
β ambient_temp β 2020-01-01 12:00:00 β 16 β 16 β
β ambient_temp β 2020-01-02 11:00:00 β 9 β 12.5 β
β ambient_temp β 2020-01-02 ... | {"source_file": "index.md"} | [
-0.004341804422438145,
0.01721995323896408,
0.012105722911655903,
0.07331844419240952,
0.05071019381284714,
-0.07615388184785843,
0.08058800548315048,
-0.0732923224568367,
-0.01361676212400198,
0.04970552772283554,
0.07325533777475357,
-0.06511416286230087,
0.041638221591711044,
-0.0010036... |
6daf3eac-b155-4b20-8d8d-d790bfd7ff29 | description: 'Documentation for the dense_rank window function'
sidebar_label: 'dense_rank'
sidebar_position: 7
slug: /sql-reference/window-functions/dense_rank
title: 'dense_rank'
doc_type: 'reference'
dense_rank
Ranks the current row within its partition without gaps. In other words, if the value of any new row... | {"source_file": "dense_rank.md"} | [
-0.05243071913719177,
-0.0897602066397667,
-0.0051957955583930016,
0.0050953649915754795,
-0.02136785164475441,
0.0363246351480484,
0.027378074824810028,
0.018861569464206696,
0.010826138779520988,
-0.023209411650896072,
-0.015241231769323349,
-0.0003787070163525641,
0.02794739231467247,
-... |
509e244d-e8de-4a82-98e3-1da62e2b16dc | description: 'Documentation for the row_number window function'
sidebar_label: 'row_number'
sidebar_position: 2
slug: /sql-reference/window-functions/row_number
title: 'row_number'
doc_type: 'reference'
row_number
Numbers the current row within its partition starting from 1.
Syntax
sql
row_number (column_name... | {"source_file": "row_number.md"} | [
-0.01916847564280033,
0.044608913362026215,
-0.05975934863090515,
-0.018879586830735207,
-0.09625446051359177,
0.0571003183722496,
0.036231402307748795,
0.056070055812597275,
-0.017153291031718254,
-0.02425803802907467,
-0.03294530510902405,
0.03139081597328186,
0.026768159121274948,
-0.05... |
d56f3b90-182c-4726-b6cf-6b70d5cace83 | description: 'Documentation for the cume_dist window function'
sidebar_label: 'cume_dist'
sidebar_position: 11
slug: /sql-reference/window-functions/cume_dist
title: 'cume_dist'
doc_type: 'reference'
cume_dist
Computes the cumulative distribution of a value within a group of values, i.e., the percentage of rows w... | {"source_file": "cume_dist.md"} | [
-0.06851772218942642,
-0.01463402807712555,
-0.015693424269557,
-0.009091964922845364,
-0.08952480554580688,
0.03187347576022148,
0.05636092647910118,
0.09452922642230988,
0.003532717702910304,
-0.009264333173632622,
-0.03389905020594597,
-0.05719925835728645,
0.0021180466283112764,
-0.028... |
ed98a5a1-36a1-4405-abd8-23d1d28e2047 | description: 'Documentation for the nth_value window function'
sidebar_label: 'nth_value'
sidebar_position: 5
slug: /sql-reference/window-functions/nth_value
title: 'nth_value'
doc_type: 'reference'
nth_value
Returns the first non-NULL value evaluated against the nth row (offset) in its ordered frame.
Syntax
... | {"source_file": "nth_value.md"} | [
-0.03357956185936928,
0.027750549837946892,
-0.07031392306089401,
-0.005302912089973688,
-0.07501791417598724,
0.05053706839680672,
0.06817003339529037,
0.03538312390446663,
0.023373009636998177,
-0.03495379909873009,
-0.007525269873440266,
-0.025051603093743324,
-0.02989855408668518,
-0.0... |
36d9eee5-a2ce-4932-8ecf-0891f6dec750 | description: 'Enables simultaneous processing of files matching a specified path across
multiple nodes within a cluster. The initiator establishes connections to worker
nodes, expands globs in the file path, and delegates file-reading tasks to worker
nodes. Each worker node is querying the initiator for the next ... | {"source_file": "fileCluster.md"} | [
-0.06657062470912933,
-0.0239312332123518,
-0.02766396850347519,
0.05324166640639305,
0.03847113251686096,
-0.07854574173688889,
0.02696068398654461,
0.031622081995010376,
0.020290229469537735,
0.016088636592030525,
0.032038044184446335,
0.002287826035171747,
0.06156422197818756,
-0.057325... |
3e67b1a5-7ddd-4948-a42b-cd63e041d427 | Example
Given a cluster named
my_cluster
and given the following value of setting
user_files_path
:
bash
$ grep user_files_path /etc/clickhouse-server/config.xml
<user_files_path>/var/lib/clickhouse/user_files/</user_files_path>
Also, given there are files
test1.csv
and
test2.csv
inside
user_files_path... | {"source_file": "fileCluster.md"} | [
0.012360526248812675,
-0.03346109390258789,
-0.09512187540531158,
0.04724754020571709,
-0.01724797673523426,
-0.03794398158788681,
0.08505331724882126,
0.01649010367691517,
0.032704394310712814,
-0.014361398294568062,
0.06558898836374283,
-0.04866113141179085,
0.09150639921426773,
-0.07904... |
29bc9f4b-792a-4bb7-b6de-22a24e8741f1 | description: 'Table function that allows effectively converting and inserting data
sent to the server with a given structure to a table with another structure.'
sidebar_label: 'input'
sidebar_position: 95
slug: /sql-reference/table-functions/input
title: 'input'
doc_type: 'reference'
input Table Function
input(... | {"source_file": "input.md"} | [
-0.03147922456264496,
-0.013853289186954498,
-0.07487823069095612,
0.05588337406516075,
-0.09518466889858246,
-0.047282807528972626,
0.04010646790266037,
0.057783614844083786,
0.011524813249707222,
0.006877307780086994,
0.052180882543325424,
-0.013473987579345703,
0.1093912199139595,
-0.07... |
2a5441ee-0131-48fa-96d0-3c80bed0ab78 | description: 'Provides a read-only table-like interface to Apache Iceberg tables in
Amazon S3, Azure, HDFS or locally stored.'
sidebar_label: 'iceberg'
sidebar_position: 90
slug: /sql-reference/table-functions/iceberg
title: 'iceberg'
doc_type: 'reference'
iceberg Table Function {#iceberg-table-function}
Provid... | {"source_file": "iceberg.md"} | [
-0.012690648436546326,
-0.016467751935124397,
-0.14149783551692963,
0.06926766037940979,
0.014285367913544178,
-0.006995185744017363,
-0.016246207058429718,
0.031326670199632645,
-0.010888038203120232,
0.0501769557595253,
0.013390609063208103,
0.0033476664684712887,
0.11500526964664459,
-0... |
4c17422a-399d-4b3c-adfa-2a36fc02d248 | int -> long
float -> double
decimal(P, S) -> decimal(P', S) where P' > P.
Currently, it is not possible to change nested structures or the types of elements within arrays and maps.
Partition Pruning {#partition-pruning}
ClickHouse supports partition pruning during SELECT queries for Iceberg tables, which he... | {"source_file": "iceberg.md"} | [
-0.021178212016820908,
0.0275813527405262,
-0.03706058859825134,
0.0010537075577303767,
0.017069343477487564,
-0.04461333528161049,
-0.02881893701851368,
0.007657716516405344,
-0.04183351993560791,
-0.015122178941965103,
-0.002029771450906992,
0.03543801233172417,
-0.008615626022219658,
0.... |
65055a82-bb09-4500-a207-47d6797553db | +------------+------------+
|order_number|product_code|
+------------+------------+
| 1| Mars|
+------------+------------+
SELECT * FROM spark_catalog.db.time_travel_example TIMESTAMP AS OF ts3;
+------------+------------+-----+
|order_number|product_code|price|
+------------+------------+-----+
| ... | {"source_file": "iceberg.md"} | [
-0.011371978558599949,
-0.03249680995941162,
0.007838263176381588,
0.05723050236701965,
-0.0215463750064373,
-0.014949816279113293,
0.014142016880214214,
0.015334793366491795,
0.005681650713086128,
0.003165967995300889,
0.07797451317310333,
-0.06216679513454437,
-0.035162072628736496,
-0.0... |
7f7df97c-3ee9-49b4-8ee5-14578e167870 | Candidate Search (in Priority Order) {#candidate-search}
Direct Path Specification
:
*If you set
iceberg_metadata_file_path
, the system will use this exact path by combining it with the Iceberg table directory path.
When this setting is provided, all other resolution settings are ignored.
Table UUID Mat... | {"source_file": "iceberg.md"} | [
-0.0044968924485147,
0.028077874332666397,
-0.03888966888189316,
-0.033401377499103546,
0.11688360571861267,
-0.009018178097903728,
-0.0527680404484272,
0.09627314656972885,
-0.008515452966094017,
0.0201619490981102,
0.029772348701953888,
0.06922295689582825,
-0.007392675615847111,
0.00311... |
9fb2163c-69ea-44d1-81a5-cf962488c79e | Currently, this is an experimental feature, so you first need to enable it:
sql
SET allow_experimental_insert_into_iceberg = 1;
Creating table {#create-iceberg-table}
To create your own empty Iceberg table, use the same commands as for reading, but specify the schema explicitly.
Writes supports all data formats f... | {"source_file": "iceberg.md"} | [
-0.0299517959356308,
-0.029978185892105103,
-0.08975595235824585,
0.0663943812251091,
0.0016696210950613022,
-0.029865875840187073,
-0.07547922432422638,
0.11470421403646469,
-0.06575683504343033,
0.05155317485332489,
0.00291540683247149,
-0.011793662793934345,
0.017887696623802185,
-0.070... |
a4009697-2673-41fa-abbb-895d625f8fee | ALTER TABLE iceberg_writes_example ADD COLUMN z Nullable(Int32);
SHOW CREATE TABLE iceberg_writes_example;
ββstatementββββββββββββββββββββββββββββββββββββββββββββββββββ
1. β CREATE TABLE default.iceberg_writes_example β΄β
ββ³( β΄β
ββ³
x
Nullab... | {"source_file": "iceberg.md"} | [
-0.011654221452772617,
0.004916760604828596,
-0.07663170248270035,
0.052495189011096954,
0.010663998313248158,
-0.005617707502096891,
-0.019373221322894096,
0.08771006017923355,
-0.05188111588358879,
0.028842009603977203,
-0.009362217038869858,
0.010453457944095135,
0.027245191857218742,
-... |
210e9c99-eb10-4b7b-a6a3-18254b11106b | description: 'The
executable
table function creates a table based on the output
of a user-defined function (UDF) that you define in a script that outputs rows to
stdout
.'
keywords: ['udf', 'user defined function', 'clickhouse', 'executable', 'table', 'function']
sidebar_label: 'executable'
sidebar_position: 50
... | {"source_file": "executable.md"} | [
0.024635473266243935,
-0.098733089864254,
-0.10450389236211777,
-0.028202751651406288,
-0.029013298451900482,
-0.09946094453334808,
-0.009184313006699085,
0.05169264227151871,
-0.03794446215033531,
0.03735097870230675,
0.047402385622262955,
-0.03181023895740509,
0.03909768909215927,
-0.057... |
b5a71bae-8ca4-4b9b-a7ab-7bcecd26fcba | # Flush results to stdout
sys.stdout.flush()
if
name
== "
main
":
main()
```
Let's invoke the script and have it generate 10 random strings:
sql
SELECT * FROM executable('generate_random.py', TabSeparated, 'id UInt32, random String', (SELECT 10))
The response looks like:
response
ββidββ¬βrandomβββββ... | {"source_file": "executable.md"} | [
-0.029161518439650536,
-0.014711327850818634,
-0.0434257872402668,
0.06832964718341827,
-0.04854104667901993,
-0.08469676226377487,
0.07826319336891174,
-0.02346963621675968,
-0.03685396537184715,
0.03492943197488785,
0.005445234011858702,
-0.025376221165060997,
0.06742870807647705,
-0.109... |
4beeba93-1be6-405e-b0b2-14e8319a4e43 | description: 'timeSeriesMetrics returns the metrics table used by table
db_name.time_series_table
whose table engine is the TimeSeries engine.'
sidebar_label: 'timeSeriesMetrics'
sidebar_position: 145
slug: /sql-reference/table-functions/timeSeriesMetrics
title: 'timeSeriesMetrics'
doc_type: 'reference'
timeSer... | {"source_file": "timeSeriesMetrics.md"} | [
-0.05707875266671181,
-0.050546228885650635,
-0.06674615293741226,
0.01149621233344078,
-0.06155172735452652,
-0.08263611048460007,
0.054513752460479736,
0.06326215714216232,
0.025248682126402855,
-0.03810080140829086,
-0.007739221677184105,
-0.11106224358081818,
0.014987689442932606,
-0.0... |
0ab8f4b5-de22-4655-97f3-60198f41d559 | description: 'The loop table function in ClickHouse is used to return query results
in an infinite loop.'
slug: /sql-reference/table-functions/loop
title: 'loop'
doc_type: 'reference'
loop Table Function
Syntax {#syntax}
sql
SELECT ... FROM loop(database, table);
SELECT ... FROM loop(database.table);
SELECT .... | {"source_file": "loop.md"} | [
0.050893768668174744,
-0.006742043420672417,
-0.03824424743652344,
0.04015393555164337,
-0.06181687116622925,
-0.019828181713819504,
0.05026868358254433,
0.019325608387589455,
-0.0036828021984547377,
-0.0458475761115551,
0.03210269287228584,
-0.021719856187701225,
0.025996072217822075,
-0.... |
0c412f31-3e9b-44d9-9dba-544bfaae6902 | description: 'Creates a table from the
URL
with given
format
and
structure
'
sidebar_label: 'url'
sidebar_position: 200
slug: /sql-reference/table-functions/url
title: 'url'
doc_type: 'reference'
import ExperimentalBadge from '@theme/badges/ExperimentalBadge';
import CloudNotSupportedBadge from '@theme/badges/... | {"source_file": "url.md"} | [
-0.0057968869805336,
0.017699090763926506,
-0.028187034651637077,
0.0795660987496376,
-0.059941306710243225,
0.029511790722608566,
0.030017845332622528,
0.013903062790632248,
-0.005589196924120188,
0.04128839075565338,
-0.00047872858704067767,
-0.050344713032245636,
0.14109204709529877,
-0... |
0c08323d-e9f2-43fb-81a5-37f6811896d4 | Virtual Columns {#virtual-columns}
_path
β Path to the
URL
. Type:
LowCardinality(String)
.
_file
β Resource name of the
URL
. Type:
LowCardinality(String)
.
_size
β Size of the resource in bytes. Type:
Nullable(UInt64)
. If the size is unknown, the value is
NULL
.
_time
β Last modified time of the ... | {"source_file": "url.md"} | [
0.04856688529253006,
0.0387871079146862,
-0.041082579642534256,
0.020384622737765312,
-0.015151585452258587,
-0.03954877331852913,
-0.004834293853491545,
0.02151532657444477,
-0.053537577390670776,
0.0530683659017086,
0.011011097580194473,
-0.06181224808096886,
-0.04481985419988632,
-0.013... |
138aacfa-1468-415e-ab8d-8fd187fb6afd | description: 'Provides a read-only table-like interface to Apache Hudi tables in Amazon
S3.'
sidebar_label: 'hudi'
sidebar_position: 85
slug: /sql-reference/table-functions/hudi
title: 'hudi'
doc_type: 'reference'
hudi Table Function
Provides a read-only table-like interface to Apache
Hudi
tables in Amazon S3... | {"source_file": "hudi.md"} | [
-0.029360095039010048,
0.0031873455736786127,
-0.14018794894218445,
0.026636401191353798,
0.04225470498204231,
-0.019614798948168755,
0.00893205963075161,
-0.05153238773345947,
-0.023584824055433273,
0.02366076223552227,
0.05620235949754715,
0.04293862730264664,
0.11238616704940796,
-0.140... |
18dac643-101f-4b10-8546-de7648fbd080 | Syntax {#syntax}
sql
hudi(url [,aws_access_key_id, aws_secret_access_key] [,format] [,structure] [,compression])
Arguments {#arguments}
| Argument | Description ... | {"source_file": "hudi.md"} | [
-0.01547252107411623,
0.08261675387620926,
-0.1277632862329483,
0.03868080675601959,
-0.023105183616280556,
-0.05102929100394249,
0.04470669850707054,
-0.029838182032108307,
-0.0035001784563064575,
0.01035996899008751,
0.037577301263809204,
-0.022458957508206367,
0.10584427416324615,
-0.12... |
2b585e79-3629-43cb-965a-46a894cdc88e | Returned value {#returned_value}
A table with the specified structure for reading data in the specified Hudi table in S3.
Virtual Columns {#virtual-columns}
_path
β Path to the file. Type:
LowCardinality(String)
.
_file
β Name of the file. Type:
LowCardinality(String)
.
_size
β Size of the file in byte... | {"source_file": "hudi.md"} | [
0.0013941816287115216,
0.03251335397362709,
-0.14833927154541016,
0.052695561200380325,
0.08512714505195618,
-0.0306391604244709,
-0.008708957582712173,
0.024364333599805832,
-0.009964879602193832,
-0.016781289130449295,
0.11223675310611725,
0.000035484186810208485,
0.0009380385745316744,
... |
fc448837-d9d1-48d1-9f75-56cae98ac7e3 | description: 'Perturbs the given query string with random variations.'
sidebar_label: 'fuzzQuery'
sidebar_position: 75
slug: /sql-reference/table-functions/fuzzQuery
title: 'fuzzQuery'
doc_type: 'reference'
fuzzQuery Table Function
Perturbs the given query string with random variations.
Syntax {#syntax}
sql
f... | {"source_file": "fuzzQuery.md"} | [
0.016791941598057747,
0.062240567058324814,
-0.0502944178879261,
0.014486190862953663,
-0.05366228520870209,
-0.02298007346689701,
0.1070527583360672,
0.049558304250240326,
-0.04590874910354614,
-0.028913985937833786,
-0.000792493752669543,
-0.04258622229099274,
0.10830886662006378,
-0.110... |
ca284c74-7d7c-41de-a643-a76a5390cf0d | description: 'Allows accessing all shards (configured in the
remote_servers
section)
of a cluster without creating a Distributed table.'
sidebar_label: 'cluster'
sidebar_position: 30
slug: /sql-reference/table-functions/cluster
title: 'clusterAllReplicas'
doc_type: 'reference'
clusterAllReplicas Table Function
... | {"source_file": "cluster.md"} | [
0.07210429012775421,
-0.05968311056494713,
-0.023958874866366386,
0.04998166114091873,
-0.001926916535012424,
-0.0063305688090622425,
-0.044696174561977386,
-0.05761769041419029,
0.05101506784558296,
0.039956916123628616,
0.029715800657868385,
0.0069182561710476875,
0.06719114631414413,
-0... |
af305c61-e97b-4804-a243-5c9e433cbcd9 | Queries to various ClickHouse clusters and replicas for research purposes.
Infrequent distributed requests that are made manually.
Connection settings like
host
,
port
,
user
,
password
,
compression
,
secure
are taken from
<remote_servers>
config section. See details in
Distributed engine
.
Related {... | {"source_file": "cluster.md"} | [
0.004969716537743807,
-0.029993025586009026,
-0.03997179865837097,
0.03441182151436806,
-0.022001443430781364,
-0.08031415939331055,
-0.07833220809698105,
-0.05390922352671623,
0.0062488229013979435,
0.0220296960324049,
-0.02101055346429348,
0.047467272728681564,
0.028258970007300377,
-0.0... |
b69e96b2-9a4c-4cb9-842e-eefa37ec6bac | description: 'Allows processing files from URL in parallel from many nodes in a specified
cluster.'
sidebar_label: 'urlCluster'
sidebar_position: 201
slug: /sql-reference/table-functions/urlCluster
title: 'urlCluster'
doc_type: 'reference'
urlCluster Table Function
Allows processing files from URL in parallel f... | {"source_file": "urlCluster.md"} | [
-0.05420665815472603,
-0.03187050670385361,
-0.09904330968856812,
0.08632002025842667,
-0.092234767973423,
-0.06372369825839996,
-0.01620331220328808,
0.008959961123764515,
-0.020072126761078835,
0.029082773253321648,
-0.017190633341670036,
-0.01456025056540966,
0.033718932420015335,
-0.09... |
5d1e145f-cc48-4e50-9adb-49ba07f760b1 | Related {#related}
HDFS engine
URL table function | {"source_file": "urlCluster.md"} | [
0.009525408037006855,
-0.04839875176548958,
-0.029927508905529976,
-0.015475749969482422,
0.012817359529435635,
0.025493064895272255,
-0.06833542138338089,
-0.01666877605021,
-0.04709484800696373,
-0.05031917989253998,
-0.0018095048144459724,
-0.006148979999125004,
0.07559599727392197,
-0.... |
758e98a4-fc02-4e4a-973a-75abd7bc0137 | description: 'This table function allows integrating ClickHouse with Redis.'
sidebar_label: 'redis'
sidebar_position: 170
slug: /sql-reference/table-functions/redis
title: 'redis'
doc_type: 'reference'
redis Table Function
This table function allows integrating ClickHouse with
Redis
.
Syntax {#syntax}
sql
re... | {"source_file": "redis.md"} | [
0.04102666303515434,
-0.04989808425307274,
-0.12823797762393951,
0.023082716390490532,
-0.07576345652341843,
-0.03863900527358055,
0.04440296068787575,
-0.006828997749835253,
-0.03658704832196236,
0.008676175959408283,
0.024865148589015007,
-0.03576233983039856,
0.0799943283200264,
-0.0684... |
958e0d85-edd1-4f79-9245-29c6403c930b | description: 'An extension to the iceberg table function which allows processing files
from Apache Iceberg in parallel from many nodes in a specified cluster.'
sidebar_label: 'icebergCluster'
sidebar_position: 91
slug: /sql-reference/table-functions/icebergCluster
title: 'icebergCluster'
doc_type: 'reference'
ice... | {"source_file": "icebergCluster.md"} | [
-0.08024230599403381,
-0.04225502535700798,
-0.10302162915468216,
0.07824359089136124,
0.02497975341975689,
-0.07460856437683105,
-0.01633690670132637,
0.05525987595319748,
-0.038718461990356445,
0.01129123754799366,
0.007927494123578072,
-0.0005107562174089253,
0.03624868392944336,
-0.113... |
a95b7d30-0c91-4431-ba72-c9101477d43d | description: 'Turns a subquery into a table. The function implements views.'
sidebar_label: 'view'
sidebar_position: 210
slug: /sql-reference/table-functions/view
title: 'view'
doc_type: 'reference'
view Table Function
Turns a subquery into a table. The function implements views (see
CREATE VIEW
). The resulting... | {"source_file": "view.md"} | [
0.02310967817902565,
-0.07863199710845947,
-0.056003257632255554,
0.10374192893505096,
-0.014743873849511147,
-0.012940242886543274,
-0.018179984763264656,
0.013464435003697872,
-0.016176633536815643,
0.010471933521330357,
0.029475798830389977,
-0.02656206488609314,
0.06999225914478302,
-0... |
1f9409f7-44b8-41c9-9be2-b7efadf717fa | description: 'A table engine which provides a table-like interface to SELECT from
and INSERT into files, similar to the s3 table function. Use
file()
when working
with local files, and
s3()
when working with buckets in object storage such as
S3, GCS, or MinIO.'
sidebar_label: 'file'
sidebar_position: 60
slug:... | {"source_file": "file.md"} | [
-0.037283334881067276,
0.0013774350518360734,
-0.08767087012529373,
0.06253436952829361,
0.06290590763092041,
0.012398377992212772,
0.053694628179073334,
0.060482610017061234,
0.007864998653531075,
0.09060854464769363,
0.0234269630163908,
0.03467770293354988,
0.09101200103759766,
-0.069350... |
486de785-062f-476a-b6e3-6a908859dc9c | Syntax {#syntax}
sql
file([path_to_archive ::] path [,format] [,structure] [,compression])
Arguments {#arguments}
| Parameter | Description ... | {"source_file": "file.md"} | [
0.010162239894270897,
0.055552151054143906,
-0.12164152413606644,
0.05587872490286827,
-0.038644157350063324,
-0.006671028211712837,
0.04785730689764023,
0.06522426009178162,
-0.06465504318475723,
0.05772525072097778,
-0.044386062771081924,
-0.0037546944804489613,
0.058528680354356766,
-0.... |
2f03739f-84fc-48f5-ae74-8a0b4f569fb9 | ```bash
cat /var/lib/clickhouse/user_files/test.tsv
1 2 3
3 2 1
1 3 2
```
Partitioned write to multiple TSV files {#partitioned-write-to-multiple-tsv-files}
If you specify a
PARTITION BY
expression when inserting data into a table function of type
file()
, then a separate file is created fo... | {"source_file": "file.md"} | [
-0.010162611491978168,
-0.07765756547451019,
-0.030446475371718407,
0.015111533924937248,
-0.02446524240076542,
-0.05953551456332207,
0.08784044533967972,
0.07892598956823349,
-0.023096442222595215,
0.08335868269205093,
0.005806826055049896,
0.030367881059646606,
0.01223512552678585,
0.003... |
8fafe7b7-0f4d-47d5-af34-480f07d21eb1 | {N..M}
β Represents any number
>= N
and
<= M
.
**
- Represents all files inside a folder recursively.
Constructions with
{}
are similar to the
remote
and
hdfs
table functions.
Examples {#examples}
Example
Suppose there are these files with the following relative paths:
some_dir/some_file_1
... | {"source_file": "file.md"} | [
-0.01488120760768652,
-0.03848673775792122,
-0.03891875967383385,
0.08838586509227753,
-0.036940425634384155,
-0.006256040185689926,
0.06514086574316025,
0.08740272372961044,
0.05789850279688835,
0.029839513823390007,
0.039545100182294846,
-0.002162511460483074,
0.09831070154905319,
-0.023... |
a70589ee-3dc9-46d1-a017-5eb6ee44f4e4 | sql
SELECT * FROM file('data/path/date=*/country=*/code=*/*.parquet') WHERE _date > '2020-01-01' AND _country = 'Netherlands' AND _code = 42;
Settings {#settings}
| Setting | Description ... | {"source_file": "file.md"} | [
0.03859790414571762,
0.05679038166999817,
-0.00619762297719717,
0.0037379709538072348,
-0.08757887035608292,
0.0349949486553669,
0.026377307251095772,
0.019567690789699554,
-0.05246192589402199,
0.040450114756822586,
0.07581073045730591,
-0.06924538314342499,
-0.011922313831746578,
-0.1085... |
7e3987ec-0576-4daf-b3c1-cafb4caa465e | description: 'Allows to perform queries on data exposed via an Apache Arrow Flight server.'
sidebar_label: 'arrowFlight'
sidebar_position: 186
slug: /sql-reference/table-functions/arrowflight
title: 'arrowFlight'
doc_type: 'reference'
arrowFlight Table Function
Allows to perform queries on data exposed via an
Ap... | {"source_file": "arrowflight.md"} | [
0.062304913997650146,
-0.09884875267744064,
-0.03924540430307388,
0.0528295673429966,
-0.10634391754865646,
-0.03715517371892929,
0.07192412763834,
-0.02193339169025421,
-0.016176749020814896,
0.0006969566456973553,
0.049722470343112946,
0.028395451605319977,
0.028261782601475716,
-0.04617... |
14ebb1c8-fa2a-4941-981c-512f75fa1061 | description: 'Reads time series from a TimeSeries table filtered by a selector and with timestamps in a specified interval.'
sidebar_label: 'timeSeriesSelector'
sidebar_position: 145
slug: /sql-reference/table-functions/timeSeriesSelector
title: 'timeSeriesSelector'
doc_type: 'reference'
timeSeriesSelector Table Fu... | {"source_file": "timeSeriesSelector.md"} | [
-0.04112020134925842,
-0.016675099730491638,
-0.058260466903448105,
0.05969627574086189,
-0.04968385770916939,
-0.0046942573972046375,
0.08181898295879364,
0.05179428309202194,
-0.011277923360466957,
-0.040531888604164124,
0.0028492137789726257,
-0.09059730172157288,
-0.04033739119768143,
... |
03ff4c4d-1f02-4b2e-aa5d-1ac9e4ce0d0e | description: 'timeSeriesTags table function returns the tags table use by table
db_name.time_series_table
whose table engine is the TimeSeries engine.'
sidebar_label: 'timeSeriesTags'
sidebar_position: 145
slug: /sql-reference/table-functions/timeSeriesTags
title: 'timeSeriesTags'
doc_type: 'reference'
timeSeri... | {"source_file": "timeSeriesTags.md"} | [
-0.027034427970647812,
-0.03947415575385094,
-0.07097432017326355,
0.0045110564678907394,
-0.01526168454438448,
-0.09808902442455292,
0.07149920612573624,
0.07903170585632324,
0.019929001107811928,
-0.03021034225821495,
0.0008692654082551599,
-0.08321170508861542,
0.02561386302113533,
-0.0... |
7aac415b-3f81-4b3c-9fc5-e81b01922067 | description: 'An extension to the paimon table function which allows processing files
from Apache Paimon in parallel from many nodes in a specified cluster.'
sidebar_label: 'paimonCluster'
sidebar_position: 91
slug: /sql-reference/table-functions/paimonCluster
title: 'paimonCluster'
doc_type: 'reference'
paimonCl... | {"source_file": "paimonCluster.md"} | [
-0.07727815955877304,
-0.05342334508895874,
-0.08218885958194733,
0.005909301806241274,
-0.034724630415439606,
-0.036170925945043564,
-0.020281778648495674,
-0.008958895690739155,
-0.031298719346523285,
0.0353979617357254,
0.043367549777030945,
-0.06429588049650192,
-0.015279291197657585,
... |
8f73af34-5969-4d21-94a8-46a316b4008d | description: 'Allows
SELECT
and
INSERT
queries to be performed on data that are
stored on a remote MySQL server.'
sidebar_label: 'mysql'
sidebar_position: 137
slug: /sql-reference/table-functions/mysql
title: 'mysql'
doc_type: 'reference'
mysql Table Function
Allows
SELECT
and
INSERT
queries to be perfo... | {"source_file": "mysql.md"} | [
0.0005998939159326255,
0.029807619750499725,
-0.06865763664245605,
0.07270150631666183,
-0.10433061420917511,
-0.03946026787161827,
0.049293939024209976,
0.04203907400369644,
-0.005108899902552366,
0.021120745688676834,
0.05483070760965347,
-0.0025293200742453337,
0.13370786607265472,
-0.0... |
f45f18aa-481d-4bb3-8223-2a3ed6a82956 | sql
mysql({host:port, database, table, user, password[, replace_query, on_duplicate_clause] | named_collection[, option=value [,..]]})
Arguments {#arguments}
| Argument | Description ... | {"source_file": "mysql.md"} | [
0.01830783300101757,
0.06329363584518433,
-0.10131257772445679,
0.00997648760676384,
-0.14613482356071472,
-0.04071923717856407,
0.07325247675180435,
0.006310421973466873,
0.017674772068858147,
0.006464946549385786,
0.028157074004411697,
-0.0935085192322731,
0.07588137686252594,
-0.0584779... |
033a70e5-6788-466a-b7fc-6d59ebfe91eb | Arguments also can be passed using
named collections
. In this case
host
and
port
should be specified separately. This approach is recommended for production environment.
Simple
WHERE
clauses such as
=, !=, >, >=, <, <=
are currently executed on the MySQL server.
The rest of the conditions and the
LIMIT
... | {"source_file": "mysql.md"} | [
-0.020076066255569458,
-0.01092404406517744,
-0.09295227378606796,
-0.04076560586690903,
-0.09874500334262848,
-0.06468939781188965,
0.08060584962368011,
-0.012089862488210201,
-0.0292504895478487,
0.011293027549982071,
0.0008682692423462868,
-0.060643941164016724,
0.18310676515102386,
-0.... |
9df341c5-debf-4e07-9f4b-b13705ed331e | sql
INSERT INTO mysql_copy
SELECT * FROM mysql('host:port', 'database', 'table', 'user', 'password')
WHERE id > (SELECT max(id) FROM mysql_copy);
Related {#related}
The 'MySQL' table engine
Using MySQL as a dictionary source
mysql_datatypes_support_level
mysql_map_fixed_string_to_text_in_show_columns
mysq... | {"source_file": "mysql.md"} | [
0.035644952207803726,
-0.043934416025877,
-0.04054504632949829,
-0.031005412340164185,
-0.08813300728797913,
-0.0161028690636158,
-0.00035985963768325746,
0.050054844468832016,
-0.10087543725967407,
-0.00021563358313869685,
0.09452063590288162,
0.036309078335762024,
0.17298837006092072,
-0... |
1c7a3aa3-85cd-4306-b638-53466c2ff3a4 | description: 'Evaluates a prometheus query using data from a TimeSeries table.'
sidebar_label: 'prometheusQueryRange'
sidebar_position: 145
slug: /sql-reference/table-functions/prometheusQueryRange
title: 'prometheusQueryRange'
doc_type: 'reference'
prometheusQuery Table Function
Evaluates a prometheus query usin... | {"source_file": "prometheusQueryRange.md"} | [
-0.02338244765996933,
0.03711630031466484,
-0.05017189309000969,
0.04755428433418274,
-0.06452813744544983,
-0.05790035054087639,
0.03564761206507683,
0.07282676547765732,
-0.04040215536952019,
-0.009542102925479412,
0.009362133219838142,
-0.07930000871419907,
0.03543577343225479,
-0.04854... |
dc998e71-99f2-4b56-9fde-4d37668f4701 | description: 'The table function allows to read data from the YTsaurus cluster.'
sidebar_label: 'ytsaurus'
sidebar_position: 85
slug: /sql-reference/table-functions/ytsaurus
title: 'ytsaurus'
doc_type: 'reference'
import ExperimentalBadge from '@theme/badges/ExperimentalBadge';
ytsaurus Table Function
The tab... | {"source_file": "ytsaurus.md"} | [
0.000572215998545289,
0.0014745036605745554,
-0.08897293359041214,
0.03311624005436897,
0.025657229125499725,
-0.09723122417926788,
0.040383126586675644,
0.04462648183107376,
-0.07401590794324875,
0.013046981766819954,
0.040467433631420135,
0.051519155502319336,
0.0443057082593441,
-0.0222... |
abeafeae-667b-4b57-baf1-ed66794e2f62 | description: 'Represents the contents of some projection in MergeTree tables.
It can be used for introspection.'
sidebar_label: 'mergeTreeProjection'
sidebar_position: 77
slug: /sql-reference/table-functions/mergeTreeProjection
title: 'mergeTreeProjection'
doc_type: 'reference'
mergeTreeProjection Table Function
... | {"source_file": "mergeTreeProjection.md"} | [
0.04834588244557381,
0.00685629528015852,
-0.05688540264964104,
0.04530526325106621,
-0.013431860134005547,
-0.00281611573882401,
0.05851364508271217,
0.09604036062955856,
-0.05740031972527504,
0.02788163349032402,
-0.004929517861455679,
-0.053459156304597855,
0.039730172604322433,
-0.0770... |
6ca474a0-d9fc-469f-bc72-59d2cf3f75c8 | description: 'Provides a table-like interface to select/insert files in Amazon S3
and Google Cloud Storage. This table function is similar to the hdfs function, but
provides S3-specific features.'
keywords: ['s3', 'gcs', 'bucket']
sidebar_label: 's3'
sidebar_position: 180
slug: /sql-reference/table-functions/s3
tit... | {"source_file": "s3.md"} | [
-0.031171215698122978,
-0.09977466613054276,
-0.05782623961567879,
0.02200458012521267,
0.08154185861349106,
0.004037154372781515,
-0.02457355707883835,
-0.033408816903829575,
0.038114096969366074,
0.07018894702196121,
0.007780506741255522,
0.011586697772145271,
0.1253204196691513,
-0.0787... |
8a47e82c-bb49-48c7-bb12-08e1f71a63a0 | | Parameter | Description ... | {"source_file": "s3.md"} | [
0.010136748664081097,
0.07613538205623627,
-0.043113913387060165,
-0.007272630929946899,
-0.09032130241394043,
0.024296408519148827,
0.02009110525250435,
0.04225422441959381,
-0.00288283359259367,
-0.06826462596654892,
0.04134080186486244,
-0.04884437844157219,
0.0006245627882890403,
-0.07... |
5950278f-e8bc-4a20-ba46-b94df179e769 | |
structure
| Structure of the table. Format
'column1_name column1_type, column2_name column2_type, ...'
. ... | {"source_file": "s3.md"} | [
-0.03587625175714493,
0.019887445494532585,
-0.09463503956794739,
-0.03281304985284805,
0.0635378509759903,
-0.0035064807161688805,
0.027650410309433937,
0.025457914918661118,
-0.06557786464691162,
0.03611557558178902,
-0.05482719838619232,
-0.015224042348563671,
0.04002634435892105,
-0.02... |
46bfe148-1d26-4ef5-94bd-5fd3b44bd82c | :::note GCS
The GCS url is in this format as the endpoint for the Google XML API is different than the JSON API:
text
https://storage.googleapis.com/<bucket>/<folder>/<filename(s)>
and not ~~https://storage.cloud.google.com~~.
:::
Arguments can also be passed using
named collections
. In this case
url
,
acce... | {"source_file": "s3.md"} | [
-0.10435760021209717,
0.05619758367538452,
-0.02795345149934292,
-0.010464427061378956,
-0.03292199969291687,
-0.03447563573718071,
-0.01029317919164896,
-0.0139003312215209,
0.05367877334356308,
0.014947894960641861,
0.015406698919832706,
-0.02438465692102909,
0.0648055151104927,
-0.04634... |
5ac68c79-08b4-4c61-ab38-67331b13c782 | :::note
ClickHouse uses filename extensions to determine the format of the data. For example, we could have run the previous command without the
CSVWithNames
:
sql
SELECT *
FROM s3(
'https://datasets-documentation.s3.eu-west-3.amazonaws.com/aapl_stock.csv'
)
LIMIT 5;
ClickHouse also can determine the compressio... | {"source_file": "s3.md"} | [
-0.0866062268614769,
0.01475498080253601,
-0.10060052573680878,
-0.07171210646629333,
0.017494438216090202,
-0.10597243905067444,
-0.020974060520529747,
-0.013782021589577198,
0.015301892533898354,
0.013039746321737766,
0.011254331097006798,
0.03380909562110901,
-0.0184528436511755,
-0.073... |
b52e2ce4-f601-464d-9828-88e1611ba1fc | Count the total amount of rows in files named
file-000.csv
,
file-001.csv
, ... ,
file-999.csv
:
sql
SELECT count(*)
FROM s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/my-test-bucket-768/big_prefix/file-{000..999}.csv', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32');
text
ββcount()ββ
β ... | {"source_file": "s3.md"} | [
0.00828046165406704,
-0.034487344324588776,
-0.1312963366508484,
0.03376973420381546,
-0.0038559078238904476,
-0.010386361740529537,
0.02019055187702179,
0.032708968967199326,
0.027358800172805786,
0.08814410865306854,
0.04869018867611885,
-0.07885506004095078,
0.09362653642892838,
-0.1223... |
b35cfefa-6c6d-47d8-8f66-e4e2b659754e | Example of
HIVE
partition strategy
sql
INSERT INTO FUNCTION s3(s3_conn, filename='t_03363_function', format=Parquet, partition_strategy='hive') PARTITION BY (year, country) SELECT 2020 as year, 'Russia' as country, 1 as id;
```result
SELECT _path, * FROM s3(s3_conn, filename='t_03363_function/**.parquet');
ββ_p... | {"source_file": "s3.md"} | [
-0.012128000147640705,
-0.045588377863168716,
-0.05850740894675255,
-0.046729397028684616,
0.01765337400138378,
-0.033051781356334686,
0.024647587910294533,
-0.0014387810369953513,
0.0051508680917322636,
0.038003042340278625,
0.009022665210068226,
-0.04499349743127823,
0.029188739135861397,
... |
7810067b-d665-48ff-ae72-ccd852202e98 | Role-based access for S3 in ClickHouse Cloud is documented
here
.
Once configured, a
roleARN
can be passed to the s3 function via an
extra_credentials
parameter. For example:
sql
SELECT count() FROM s3('https://datasets-documentation.s3.eu-west-3.amazonaws.com/mta/*.tsv','CSVWithNames',extra_credentials(role_a... | {"source_file": "s3.md"} | [
-0.057201940566301346,
0.0180471520870924,
-0.1163536012172699,
0.008985576219856739,
-0.003400590503588319,
-0.012389757670462132,
-0.012036853469908237,
-0.09767065942287445,
0.044332876801490784,
-0.00843570102006197,
-0.011191647499799728,
-0.03414757177233696,
0.08389448374509811,
-0.... |
67972e27-da9d-4675-a9fd-698368f4c9b9 | Accessing requester-pays buckets {#accessing-requester-pays-buckets}
To access a requester-pays bucket, a header
x-amz-request-payer = requester
must be passed in any requests. This is achieved by passing the parameter
headers('x-amz-request-payer' = 'requester')
to the s3 function. For example:
```sql
SELECT
... | {"source_file": "s3.md"} | [
-0.08904864639043808,
0.04002683237195015,
-0.1001150980591774,
-0.01800677552819252,
0.007316283881664276,
-0.06978461146354675,
0.054252512753009796,
-0.038778916001319885,
0.0536138117313385,
0.07030262798070908,
-0.020160812884569168,
-0.0646200180053711,
0.07499583065509796,
-0.091232... |
fff4c86c-afec-4106-8f59-3dd835e3e258 | description: 'Displays the dictionary data as a ClickHouse table. Works the same way
as the Dictionary engine.'
sidebar_label: 'dictionary'
sidebar_position: 47
slug: /sql-reference/table-functions/dictionary
title: 'dictionary'
doc_type: 'reference'
dictionary Table Function
Displays the
dictionary
data as a... | {"source_file": "dictionary.md"} | [
-0.0009567920351400971,
-0.022202080115675926,
-0.07555323094129562,
0.022946080192923546,
-0.08395254611968994,
-0.08831015974283218,
0.0656113550066948,
-0.013893100433051586,
-0.051712773740291595,
-0.0060119773261249065,
0.057396143674850464,
-0.014384145848453045,
0.09705939888954163,
... |
9024c8b4-6b94-4c49-8bb6-7d7e928f5ac9 | description: 'Creates a table from files in HDFS. This table function is similar to
the url and file table functions.'
sidebar_label: 'hdfs'
sidebar_position: 80
slug: /sql-reference/table-functions/hdfs
title: 'hdfs'
doc_type: 'reference'
import ExperimentalBadge from '@theme/badges/ExperimentalBadge';
import Cl... | {"source_file": "hdfs.md"} | [
0.020528698340058327,
-0.0435086153447628,
-0.06333281099796295,
0.04262195900082588,
0.026040758937597275,
0.007725460920482874,
-0.005246351007372141,
0.04918534681200981,
-0.027663862332701683,
0.05478089675307274,
-0.020225854590535164,
-0.01620287075638771,
0.10001025348901749,
-0.046... |
8e0a451e-a9d9-4050-b49a-84c648f5910d | 'hdfs://hdfs1:9000/some_dir/some_file_3'
'hdfs://hdfs1:9000/another_dir/some_file_1'
'hdfs://hdfs1:9000/another_dir/some_file_2'
'hdfs://hdfs1:9000/another_dir/some_file_3'
Query the amount of rows in these files:
sql
SELECT count(*)
FROM hdfs('hdfs://hdfs1:9000/{some,another}_dir/some_file_{1..3}... | {"source_file": "hdfs.md"} | [
-0.02839353121817112,
-0.038145873695611954,
-0.04102623090147972,
0.0005527015891857445,
-0.021073659881949425,
0.04495612531900406,
0.11142746359109879,
0.08804447203874588,
0.004559393972158432,
-0.01852494478225708,
0.027884528040885925,
-0.04678674787282944,
0.08246809989213943,
0.005... |
2d49468f-7065-4442-b8a4-6eb2f85a884e | description: 'Perturbs a JSON string with random variations.'
sidebar_label: 'fuzzJSON'
sidebar_position: 75
slug: /sql-reference/table-functions/fuzzJSON
title: 'fuzzJSON'
doc_type: 'reference'
fuzzJSON Table Function
Perturbs a JSON string with random variations.
Syntax {#syntax}
sql
fuzzJSON({ named_collec... | {"source_file": "fuzzJSON.md"} | [
-0.03228607401251793,
0.07872070372104645,
-0.041842930018901825,
0.018652712926268578,
-0.07519319653511047,
-0.027024077251553535,
0.09671563655138016,
0.041293494403362274,
-0.000642744533251971,
-0.05537118390202522,
0.0344608873128891,
-0.057555295526981354,
0.010404971428215504,
-0.0... |
e2f66d0a-c467-4cf3-9e8d-d4dd8a78e607 | text
{"52Xz2Zd4vKNcuP2":true}
{"UPbOhOQAdPKIg91":3405264103600403024}
{"X0QUWu8yT":[]}
sql
SELECT * FROM fuzzJSON(json_fuzzer, json_str='{"name" : "value"}', random_seed=1234) LIMIT 3;
text
{"key":"value", "mxPG0h1R5":"L-YQLv@9hcZbOIGrAn10%GA"}
{"BRE3":true}
{"key":"value", "SWzJdEJZ04nrpSfy":[{"3Q23y":[]}]}
sql
... | {"source_file": "fuzzJSON.md"} | [
-0.032111626118421555,
0.06031133234500885,
-0.0034916207659989595,
0.00968247465789318,
-0.060620084404945374,
-0.028976747766137123,
0.09885743260383606,
-0.005084422882646322,
-0.019755113869905472,
-0.056300703436136246,
0.05899298936128616,
0.0010421925690025091,
0.06107638031244278,
... |
2d96685b-a409-4b62-8822-9a7450f9cda7 | description: 'Allows processing files from HDFS in parallel from many nodes in a specified
cluster.'
sidebar_label: 'hdfsCluster'
sidebar_position: 81
slug: /sql-reference/table-functions/hdfsCluster
title: 'hdfsCluster'
doc_type: 'reference'
hdfsCluster Table Function
Allows processing files from HDFS in paral... | {"source_file": "hdfsCluster.md"} | [
-0.01898869499564171,
-0.0651874840259552,
-0.062499504536390305,
0.06934669613838196,
-0.0036003084387630224,
-0.05061771348118782,
-0.02831520140171051,
0.02269860729575157,
-0.04770014435052872,
0.023259557783603668,
-0.04103253409266472,
-0.01904298923909664,
0.04349504038691521,
-0.06... |
cd32bb55-f850-4957-b923-6527cd042423 | 'hdfs://hdfs1:9000/some_dir/some_file_2'
'hdfs://hdfs1:9000/some_dir/some_file_3'
'hdfs://hdfs1:9000/another_dir/some_file_1'
'hdfs://hdfs1:9000/another_dir/some_file_2'
'hdfs://hdfs1:9000/another_dir/some_file_3'
Query the amount of rows in these files:
sql
SELECT count(*)
FROM hdfsCluster('clust... | {"source_file": "hdfsCluster.md"} | [
0.031158436089754105,
-0.056739021092653275,
-0.036703161895275116,
0.051172200590372086,
0.001750816940329969,
0.005465193651616573,
0.05300562083721161,
0.06565703451633453,
-0.020395513623952866,
-0.018545519560575485,
0.0586661696434021,
-0.09658115357160568,
0.07954602688550949,
-0.02... |
df35a949-a0b3-4527-8897-2ae8fec86401 | description: 'Used for test purposes as the fastest method to generate many rows.
Similar to the
system.zeros
and
system.zeros_mt
system tables.'
sidebar_label: 'zeros'
sidebar_position: 145
slug: /sql-reference/table-functions/zeros
title: 'zeros'
doc_type: 'reference'
zeros Table Function
zeros(N)
β Re... | {"source_file": "zeros.md"} | [
-0.0845351368188858,
0.022339176386594772,
-0.11862407624721527,
0.019669929519295692,
-0.047088608145713806,
-0.11974701285362244,
-0.009774450212717056,
0.01863638125360012,
0.03640279173851013,
0.04905564710497856,
0.06404855102300644,
-0.0341356061398983,
0.06845305114984512,
-0.093152... |
bf29e697-ebc8-42d1-a6f1-ea11773b9241 | description: 'creates a temporary storage which fills columns with values.'
keywords: ['values', 'table function']
sidebar_label: 'values'
sidebar_position: 210
slug: /sql-reference/table-functions/values
title: 'values'
doc_type: 'reference'
Values Table Function {#values-table-function}
The
Values
table funct... | {"source_file": "values.md"} | [
-0.01577918417751789,
0.010484347119927406,
-0.10121419280767441,
0.05024749040603638,
-0.07056540995836258,
0.0033653834834694862,
0.08491100370883942,
0.0804188922047615,
-0.026719558984041214,
0.06246238946914673,
0.0750705674290657,
-0.015552887693047523,
0.09318169206380844,
-0.057272... |
65c5bb87-a021-4dc6-b6d3-7ae1035965ff | Or without providing a row specification (
'column1_name Type1, column2_name Type2, ...'
in the
syntax
), in which case the columns are automatically named.
For example:
sql title="Query"
-- tuples as values
SELECT *
FROM VALUES(
('Noah', 'Paris'),
('Emma', 'Tokyo'),
('Liam', 'Sydney'),
('Olivia'... | {"source_file": "values.md"} | [
0.03993217274546623,
-0.045250337570905685,
-0.012205684557557106,
0.03985348343849182,
-0.047716304659843445,
-0.043347131460905075,
0.060377705842256546,
-0.03587982431054115,
-0.04115172475576401,
0.0014545508893206716,
0.028719710186123848,
-0.0620182640850544,
0.023117875680327415,
-0... |
dc3f9c07-b57d-4679-9dcb-72d50762743a | description: 'Generates random data with a given schema. Allows populating test tables
with that data. Not all types are supported.'
sidebar_label: 'generateRandom'
sidebar_position: 75
slug: /sql-reference/table-functions/generate
title: 'generateRandom'
doc_type: 'reference'
generateRandom Table Function
Gene... | {"source_file": "generate.md"} | [
0.01796828769147396,
0.02295740135014057,
-0.06757520139217377,
0.040398091077804565,
-0.050310105085372925,
-0.03172079473733902,
0.07002638280391693,
0.012620791792869568,
-0.07464119791984558,
0.023295700550079346,
0.03277202695608139,
-0.07393835484981537,
0.08299539983272552,
-0.08074... |
e75f071b-a00a-46f7-a9ea-ad8b8952c180 | In combination with
generateRandomStructure
:
sql
SELECT * FROM generateRandom(generateRandomStructure(4, 101), 101) LIMIT 3;
text
βββββββββββββββββββc1ββ¬ββββββββββββββββββc2ββ¬βc3ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ... | {"source_file": "generate.md"} | [
0.03560108691453934,
0.009462954476475716,
-0.058482248336076736,
-0.0056351725943386555,
-0.020938098430633545,
-0.06717800348997116,
0.07135052978992462,
-0.05646427348256111,
-0.007894164882600307,
0.06808340549468994,
-0.0022043937351554632,
-0.09375287592411041,
0.04832286387681961,
-... |
5ba16d6e-d347-40eb-b139-24c0cc54ec2c | text
ββββββββββββββββββββββββββββββββββββββββc1ββ¬βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββc2ββ¬βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββc3ββ¬βββββββββc4ββ¬βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββc5ββ¬βββββββββββββββ... | {"source_file": "generate.md"} | [
0.012594763189554214,
-0.005912866909056902,
-0.01981927827000618,
-0.019227182492613792,
-0.0033692317083477974,
-0.04588698968291283,
-0.017997730523347855,
0.012795434333384037,
0.049605146050453186,
0.022431261837482452,
0.058570411056280136,
-0.01068704854696989,
0.018988430500030518,
... |
c579a745-aec7-4502-92f5-cfb64860cf5a | ββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββββββ΄βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄ββββββββββββββββββββ... | {"source_file": "generate.md"} | [
-0.04159650206565857,
-0.024681830778717995,
0.07789310067892075,
-0.006149471737444401,
0.017001427710056305,
0.0012621216010302305,
0.12373971194028854,
-0.001971512334421277,
0.05898108333349228,
-0.04216562211513519,
0.059197306632995605,
-0.07129892706871033,
0.12670376896858215,
0.02... |
8dd5e4f8-d351-47d5-9f74-105f7b0f2430 | :::note
generateRandom(generateRandomStructure(), [random seed], max_string_length, max_array_length)
with a large enough
max_array_length
can generate a really huge output due to possible big nesting depth (up to 16) of complex types (
Array
,
Tuple
,
Map
,
Nested
).
:::
Related content {#related-content}
... | {"source_file": "generate.md"} | [
-0.04397840425372124,
0.003130580997094512,
-0.0473274402320385,
0.020517561584711075,
0.022196251899003983,
-0.037791069597005844,
-0.017316168174147606,
-0.09395114332437515,
-0.0317719466984272,
-0.0014284767676144838,
0.03865645453333855,
-0.001102900831028819,
0.0921550989151001,
-0.0... |
7ee8a6d2-ffb7-403a-938a-1b3ec9b72478 | description: 'Provides a read-only table-like interface to the Delta Lake tables in
Amazon S3.'
sidebar_label: 'deltaLake'
sidebar_position: 45
slug: /sql-reference/table-functions/deltalake
title: 'deltaLake'
doc_type: 'reference'
deltaLake Table Function
Provides a read-only table-like interface to
Delta Lak... | {"source_file": "deltalake.md"} | [
-0.03862440958619118,
-0.016309883445501328,
-0.08325008302927017,
-0.02785583958029747,
-0.020081447437405586,
-0.017748326063156128,
0.01884043589234352,
-0.00782245583832264,
-0.01004562247544527,
0.04495839774608612,
0.01642436534166336,
-0.03115645982325077,
0.10823221504688263,
-0.08... |
7a749869-500d-4a57-9fbf-afb332f5206a | description: 'Provides a table-like interface to
SELECT
and
INSERT
data from Google
Cloud Storage. Requires the
Storage Object User
IAM role.'
keywords: ['gcs', 'bucket']
sidebar_label: 'gcs'
sidebar_position: 70
slug: /sql-reference/table-functions/gcs
title: 'gcs'
doc_type: 'reference'
gcs Table Function
... | {"source_file": "gcs.md"} | [
-0.07099271565675735,
-0.10989756882190704,
-0.05336460843682289,
-0.007182334084063768,
-0.010847803205251694,
-0.007971464656293392,
0.008190223947167397,
-0.05502517893910408,
0.010364591144025326,
0.05539701133966446,
0.04824502766132355,
-0.04981907829642296,
0.11576139181852341,
-0.0... |
404e77b3-9c2b-418f-9452-0497108ee300 | :::note GCS
The GCS path is in this format as the endpoint for the Google XML API is different than the JSON API:
text
https://storage.googleapis.com/<bucket>/<folder>/<filename(s)>
and not ~~https://storage.cloud.google.com~~.
:::
Arguments can also be passed using
named collections
. In this case
url
,
for... | {"source_file": "gcs.md"} | [
-0.10815610736608505,
0.06279028952121735,
-0.004833877086639404,
-0.008898594416677952,
-0.025645067915320396,
-0.030973907560110092,
-0.03808381035923958,
-0.0060768136754632,
0.051533956080675125,
0.028856799006462097,
0.009289856068789959,
-0.02976503036916256,
0.04619845002889633,
-0.... |
626c3440-f3b3-422a-a8aa-68fa0b43941f | sql
SELECT *
FROM gcs('https://storage.googleapis.com/clickhouse_public_datasets/my-test-bucket-768/data.csv.gz', 'CSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
LIMIT 2;
text
ββcolumn1ββ¬βcolumn2ββ¬βcolumn3ββ
β 1 β 2 β 3 β
β 3 β 2 β 1 β
βββββββββββ΄ββββββββββ΄ββββββββββ
The... | {"source_file": "gcs.md"} | [
-0.09278754144906998,
0.03153903782367706,
-0.0590943843126297,
0.04524048790335655,
0.0168253593146801,
-0.10990726947784424,
0.0500897541642189,
-0.050501398742198944,
0.014315624721348286,
0.06947798281908035,
0.010433819144964218,
-0.02951432392001152,
0.06249329820275307,
-0.052129477... |
d71fb09e-d92c-45ad-8508-659375f9d6d0 | Insert data into file
test-data.csv.gz
from existing table:
sql
INSERT INTO FUNCTION gcs('https://storage.googleapis.com/my-test-bucket-768/test-data.csv.gz', 'CSV', 'name String, value UInt32', 'gzip')
SELECT name, value FROM existing_table;
Glob ** can be used for recursive directory traversal. Consider the bel... | {"source_file": "gcs.md"} | [
-0.03453502058982849,
-0.03160443529486656,
-0.06264597177505493,
0.058518342673778534,
-0.039571452885866165,
-0.105046346783638,
0.05215577036142349,
0.030645085498690605,
-0.009225426241755486,
0.07876023650169373,
0.04701933637261391,
-0.049470022320747375,
0.09269583970308304,
-0.0445... |
0bf8d06f-76b8-4746-8edd-5414f2f45997 | description: 'Provides a read-only table-like interface to Apache Paimon tables in
Amazon S3, Azure, HDFS or locally stored.'
sidebar_label: 'paimon'
sidebar_position: 90
slug: /sql-reference/table-functions/paimon
title: 'paimon'
doc_type: 'reference'
paimon Table Function {#paimon-table-function}
Provides a r... | {"source_file": "paimon.md"} | [
-0.016577916219830513,
-0.03715655952692032,
-0.09358440339565277,
-0.028444653376936913,
-0.05069594085216522,
0.02116895280778408,
-0.007042743731290102,
-0.030071338638663292,
-0.029971200972795486,
0.07013168931007385,
0.057811345905065536,
-0.042082302272319794,
0.05743289366364479,
-... |
fc81a3d6-54ee-4527-81fb-203fc0aa8b28 | _etag
β The etag of the file. Type:
LowCardinality(String)
. If the etag is unknown, the value is
NULL
.
Data Types supported {#data-types-supported}
| Paimon Data Type | Clickhouse Data Type
|-------|--------|
|BOOLEAN |Int8 |
|TINYINT |Int8 |
|SMALLINT |Int16 |
|INTEGER |Int32... | {"source_file": "paimon.md"} | [
-0.010866773314774036,
0.011979728937149048,
-0.011521156877279282,
-0.002692799549549818,
-0.022120226174592972,
-0.029227333143353462,
-0.010614313185214996,
0.05301329866051674,
-0.009538715705275536,
-0.003666680073365569,
0.0519375205039978,
-0.06244392693042755,
-0.02808733470737934,
... |
afd87427-8e15-435f-ae79-c5673bcb9b20 | description: 'Documentation for Table Functions'
sidebar_label: 'Table Functions'
sidebar_position: 1
slug: /sql-reference/table-functions/
title: 'Table Functions'
doc_type: 'reference'
Table Functions
Table functions are methods for constructing tables.
Usage {#usage}
Table functions can be used in the ... | {"source_file": "index.md"} | [
-0.04354554042220116,
0.00040608076960779727,
-0.08741261810064316,
0.07514346390962601,
-0.03838012367486954,
-0.0311025008559227,
0.011901285499334335,
0.055114906281232834,
0.0037224176339805126,
0.055694229900836945,
0.015428178012371063,
-0.014096392318606377,
0.08913572877645493,
-0.... |
96b70a4e-d5de-4181-95bc-d0d48a00979f | description: 'Represents the contents of index and marks files of MergeTree tables.
It can be used for introspection.'
sidebar_label: 'mergeTreeIndex'
sidebar_position: 77
slug: /sql-reference/table-functions/mergeTreeIndex
title: 'mergeTreeIndex'
doc_type: 'reference'
mergeTreeIndex Table Function
Represents t... | {"source_file": "mergeTreeIndex.md"} | [
0.0638343021273613,
0.013201471418142319,
-0.023099126294255257,
0.06032360717654228,
-0.004196310881525278,
-0.0014117737300693989,
0.06146860122680664,
0.09546219557523727,
-0.06708204746246338,
0.008665204979479313,
0.02181699313223362,
-0.006699533201754093,
0.055108774453401566,
-0.09... |
f2b41180-79da-4434-90ac-c2fa6f275d30 | INSERT INTO test_table SELECT number, number, range(number % 5) FROM numbers(10, 10);
```
sql
SELECT * FROM mergeTreeIndex(currentDatabase(), test_table, with_marks = true);
text
ββpart_nameββ¬βmark_numberββ¬βrows_in_granuleββ¬βidββ¬βid.markββ¬βn.markβββ¬βarr.size0.markββ¬βarr.markββ
β all_1_1_0 β 0 β ... | {"source_file": "mergeTreeIndex.md"} | [
0.09460369497537613,
-0.037243783473968506,
0.03662462532520294,
-0.021677395328879356,
-0.020320508629083633,
-0.012868126854300499,
0.05725186690688133,
0.00909410510212183,
-0.10658953338861465,
0.06605548411607742,
0.05785574018955231,
-0.03690408170223236,
0.029372666031122208,
-0.064... |
567c1168-c0e2-4531-a3e8-3544368ebd23 | description: 'Allows
SELECT
and
INSERT
queries to be performed on data that is
stored on a remote PostgreSQL server.'
sidebar_label: 'postgresql'
sidebar_position: 160
slug: /sql-reference/table-functions/postgresql
title: 'postgresql'
doc_type: 'reference'
postgresql Table Function
Allows
SELECT
and
INS... | {"source_file": "postgresql.md"} | [
0.007274061441421509,
0.023423470556735992,
-0.06572927534580231,
0.046158164739608765,
-0.1225670725107193,
-0.011828129179775715,
0.029215263202786446,
0.032594721764326096,
0.012892396189272404,
0.014774140901863575,
-0.00964734610170126,
-0.013482660986483097,
0.015585771761834621,
-0.... |
9df19ece-add8-4b68-bd35-0ed01f8d34f2 | Supports multiple replicas that must be listed by
|
. For example:
sql
SELECT name FROM postgresql(`postgres{1|2|3}:5432`, 'postgres_database', 'postgres_table', 'user', 'password');
or
sql
SELECT name FROM postgresql(`postgres1:5431|postgres2:5432`, 'postgres_database', 'postgres_table', 'user', 'password');
... | {"source_file": "postgresql.md"} | [
-0.002112702000886202,
-0.043879732489585876,
-0.07515139132738113,
-0.0672297477722168,
-0.09694914519786835,
-0.030019039288163185,
0.00017004272376652807,
-0.010647867806255817,
-0.0250515379011631,
0.029735727235674858,
0.017575137317180634,
0.04301287606358528,
0.03391149640083313,
-0... |
46ed1d24-37a9-402f-8691-11b74601ba31 | The PostgreSQL table engine
Using PostgreSQL as a dictionary source
Replicating or migrating Postgres data with with PeerDB {#replicating-or-migrating-postgres-data-with-with-peerdb}
In addition to table functions, you can always use
PeerDB
by ClickHouse to set up a continuous data pipeline from Postgres to... | {"source_file": "postgresql.md"} | [
-0.04882749915122986,
-0.06472461670637131,
-0.07180555909872055,
-0.006173542235046625,
-0.08201754838228226,
-0.03755742311477661,
-0.024153733626008034,
-0.050199273973703384,
-0.05937158316373825,
0.055820778012275696,
-0.003948505502194166,
0.053187817335128784,
0.008124076761305332,
... |
9a79f48e-17cc-431f-b231-52eb051fc725 | description: 'timeSeriesData returns the data table used by table
db_name.time_series_table
whose table engine is TimeSeries.'
sidebar_label: 'timeSeriesData'
sidebar_position: 145
slug: /sql-reference/table-functions/timeSeriesData
title: 'timeSeriesData'
doc_type: 'reference'
timeSeriesData Table Function
t... | {"source_file": "timeSeriesData.md"} | [
-0.034002650529146194,
-0.041977133601903915,
-0.05150340497493744,
-0.007475280202925205,
-0.06518638879060745,
-0.09204256534576416,
0.04988039284944534,
0.08370408415794373,
0.0062776366248726845,
-0.03716328367590904,
0.006358925253152847,
-0.0797187015414238,
0.0023347935639321804,
-0... |
92d13306-73f0-4809-b8c8-b01957fb9e12 | description: 'Provides a table-like interface to select/insert files in Azure Blob
Storage. Similar to the s3 function.'
keywords: ['azure blob storage']
sidebar_label: 'azureBlobStorage'
sidebar_position: 10
slug: /sql-reference/table-functions/azureBlobStorage
title: 'azureBlobStorage'
doc_type: 'reference'
imp... | {"source_file": "azureBlobStorage.md"} | [
0.01154843345284462,
-0.046559955924749374,
-0.11976932734251022,
0.0787351056933403,
-0.022957902401685715,
0.055872734636068344,
0.06597360223531723,
-0.0033267394173890352,
0.0244993194937706,
0.10767493396997452,
0.02172393538057804,
0.009066970087587833,
0.13159339129924774,
0.0126971... |
c48b508b-72c5-4a4a-b653-adb8d07be6f4 | | Argument | Description ... | {"source_file": "azureBlobStorage.md"} | [
0.027820559218525887,
0.09321624785661697,
-0.03668836131691933,
-0.034107331186532974,
-0.05860394611954689,
0.01916765607893467,
0.03267664462327957,
0.04797063022851944,
0.04604816436767578,
-0.05763087421655655,
0.011640780605375767,
-0.04407937824726105,
0.0003477597492747009,
-0.0341... |
971d2535-fe59-457d-beda-2770b0bb84df | |
account_key
| if storage_account_url is used, then account key can be specified here ... | {"source_file": "azureBlobStorage.md"} | [
0.0036375741474330425,
0.03577835485339165,
-0.07121344655752182,
-0.0029543121345341206,
0.024327201768755913,
-0.0032272222451865673,
0.045984119176864624,
0.06727232784032822,
-0.08232422918081284,
0.023077569901943207,
-0.05282527580857277,
-0.010364746674895287,
0.04255812615156174,
-... |
5189a700-a9c6-4bcc-9614-f12eb48450ac | | Parameter is optional. Only used with
HIVE
partition strategy. Tells ClickHouse whether to expect partition columns to be written in the data file. Defaults
false
. ... | {"source_file": "azureBlobStorage.md"} | [
0.03761804476380348,
-0.01712910085916519,
-0.09348780661821365,
-0.04400063678622246,
-0.023963037878274918,
0.01585768721997738,
0.04758989438414574,
0.0035538123920559883,
-0.08072663098573685,
-0.008187140338122845,
0.06656084954738617,
-0.03649608790874481,
0.050171997398138046,
-0.04... |
a367bb8b-3f82-4eab-9fbd-0bb52696d967 | Returned value {#returned_value}
A table with the specified structure for reading or writing data in the specified file.
Examples {#examples}
Similar to the
AzureBlobStorage
table engine, users can use Azurite emulator for local Azure Storage development. Further details
here
. Below we assume Azurite is avail... | {"source_file": "azureBlobStorage.md"} | [
0.03950485587120056,
0.005952620878815651,
-0.14138466119766235,
0.10319695621728897,
-0.09744692593812943,
0.013688959181308746,
0.0804021954536438,
0.06467755138874054,
0.027529466897249222,
0.11565994471311569,
0.03196525201201439,
-0.0715760663151741,
0.1311332732439041,
-0.01477031037... |
cc50a9ad-9915-46fe-9ba8-1cf602955056 | ```result
select _path, * from azureBlobStorage(azure_conf2, storage_account_url = 'http://localhost:30000/devstoreaccount1', container='cont', blob_path='azure_table_root/**.csvwithnames')
ββ_pathββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ¬βidββ¬βyearββ¬βcountryββ
1. β cont/azure_table_... | {"source_file": "azureBlobStorage.md"} | [
0.045821670442819595,
-0.010476968251168728,
-0.020270690321922302,
0.03158612176775932,
-0.006200660020112991,
-0.0021516212727874517,
0.062265556305646896,
-0.018206773325800896,
-0.012103104032576084,
0.10131514072418213,
-0.006867108400911093,
-0.08312325924634933,
0.014152994379401207,
... |
fe4dc294-9af0-4d8a-b87e-7edfddd08be2 | ββcount()ββ
β 10 β
βββββββββββ
1 row in set. Elapsed: 0.153 sec.
```
Related {#related}
AzureBlobStorage Table Engine | {"source_file": "azureBlobStorage.md"} | [
-0.0004219755355734378,
0.002540457295253873,
-0.0221859123557806,
0.03191665560007095,
-0.024068079888820648,
0.07753472775220871,
0.05163882300257683,
-0.06703159213066101,
0.04306508228182793,
0.0442541167140007,
0.12556631863117218,
-0.047358568757772446,
0.06904257088899612,
-0.017882... |
13597851-f6d7-4cb4-a9cf-b44b6440bb24 | description: 'Returns the table that is connected via ODBC.'
sidebar_label: 'odbc'
sidebar_position: 150
slug: /sql-reference/table-functions/odbc
title: 'odbc'
doc_type: 'reference'
odbc Table Function
Returns table that is connected via
ODBC
.
Syntax {#syntax}
sql
odbc(datasource, external_database, extern... | {"source_file": "odbc.md"} | [
-0.023056840524077415,
-0.027631521224975586,
-0.09147054702043533,
0.08817968517541885,
-0.03357270732522011,
-0.05245263874530792,
0.04023145139217377,
0.06711048632860184,
0.015971947461366653,
-0.03050752356648445,
0.0028201851528137922,
-0.054949142038822174,
0.02422383800148964,
-0.0... |
c0d602fc-b05b-4682-9f50-5bb2e5f461d2 | mysql> insert into test (
int_id
,
float
) VALUES (1,2);
Query OK, 1 row affected (0,00 sec)
mysql> select * from test;
+------+----------+-----+----------+
| int_id | int_nullable | float | float_nullable |
+------+----------+-----+----------+
| 1 | NULL | 2 | NULL |
+------+----------+--... | {"source_file": "odbc.md"} | [
-0.016149191185832024,
-0.0077901300974190235,
-0.047429852187633514,
0.08582255244255066,
-0.03395487368106842,
-0.0681992620229721,
0.08214083313941956,
0.0000966121515375562,
-0.017954736948013306,
-0.04969991371035576,
0.10397258400917053,
-0.08153335005044937,
0.059850700199604034,
-0... |
c44f922e-068f-41d9-a173-7549a85cb6a7 | description: 'Creates a temporary Merge table. The structure will be derived from underlying tables by using a union of their columns and by deriving common types.'
sidebar_label: 'merge'
sidebar_position: 130
slug: /sql-reference/table-functions/merge
title: 'merge'
doc_type: 'reference'
merge Table Function
Cre... | {"source_file": "merge.md"} | [
0.006969159934669733,
-0.012841575779020786,
-0.011233414523303509,
0.03842092305421829,
-0.018785834312438965,
0.0020731741096824408,
0.01102438848465681,
0.04465383291244507,
-0.02009563520550728,
0.0269001517444849,
0.02797260507941246,
-0.03784584626555443,
0.010279906913638115,
-0.050... |
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