id stringlengths 36 36 | document stringlengths 3 3k | metadata stringlengths 23 69 | embeddings listlengths 384 384 |
|---|---|---|---|
5a4e38a1-734d-4141-bbb4-6747a950c11c | description: 'Computes the sum of the numbers, using the same data type for the result
as for the input parameters. If the sum exceeds the maximum value for this data
type, it is calculated with overflow.'
sidebar_position: 200
slug: /sql-reference/aggregate-functions/reference/sumwithoverflow
title: 'sumWithOverfl... | {"source_file": "sumwithoverflow.md"} | [
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-0.006708390545099974,
0.033074911683797836,
-0... |
b498ae1c-1c0e-42be-b8d2-5248dea22bae | description: 'Calculates the sum. Only works for numbers.'
sidebar_position: 195
slug: /sql-reference/aggregate-functions/reference/sum
title: 'sum'
doc_type: 'reference'
sum
Calculates the sum. Only works for numbers.
Syntax
sql
sum(num)
Parameters
-
num
: Column of numeric values.
(U)Int*
,
Float*
,
... | {"source_file": "sum.md"} | [
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a5692b20-e703-4918-ac4a-502be08926fc | description: 'Aggregate function that calculates the slope between the leftmost and
rightmost points across a group of values.'
sidebar_position: 114
slug: /sql-reference/aggregate-functions/reference/boundingRatio
title: 'boundingRatio'
doc_type: 'reference'
Aggregate function that calculates the slope between t... | {"source_file": "boundrat.md"} | [
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0.03300827369093895,
-... |
12cdf172-ba3e-402d-b510-117b1ad6acbf | description: 'Aggregate function that calculates PromQL-like delta over time series data on the specified grid.'
sidebar_position: 221
slug: /sql-reference/aggregate-functions/reference/timeSeriesDeltaToGrid
title: 'timeSeriesDeltaToGrid'
doc_type: 'reference'
Aggregate function that takes time series data as pairs... | {"source_file": "timeSeriesDeltaToGrid.md"} | [
-0.04996413737535477,
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-0.09249354898929596,
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0.004367109853774309,
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-0.00805729627609253,
-0.0... |
40125278-47b2-4efa-b6fd-664ee8c8b3d4 | :::note
This function is experimental, enable it by setting
allow_experimental_ts_to_grid_aggregate_function=true
.
::: | {"source_file": "timeSeriesDeltaToGrid.md"} | [
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-0... |
883e9089-10d4-41c9-b8a1-34bcc5358c9e | description: 'Calculates the exact number of different argument values.'
sidebar_position: 207
slug: /sql-reference/aggregate-functions/reference/uniqexact
title: 'uniqExact'
doc_type: 'reference'
uniqExact
Calculates the exact number of different argument values.
sql
uniqExact(x[, ...])
Use the
uniqExact
f... | {"source_file": "uniqexact.md"} | [
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0.04340681806206703,
-0.081... |
d3efb692-2498-4ec4-a524-6aae5af78ef7 | description: 'Returns the cumulative exponential decay over a time series at the index
t
in time.'
sidebar_position: 134
slug: /sql-reference/aggregate-functions/reference/exponentialTimeDecayedCount
title: 'exponentialTimeDecayedCount'
doc_type: 'reference'
exponentialTimeDecayedCount {#exponentialtimedecayedc... | {"source_file": "exponentialtimedecayedcount.md"} | [
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0.02522929199039936,
0.053115036338567734,
-0.08352230489253998,
0.04032932221889496,
-0.050... |
9c084cff-fcca-4a8a-918d-aa8f682697a7 | response
ββvalueββ¬βtimeββ¬βround(exp_smooth, 3)ββ¬βbarβββββββββββββββββββββββββ
1. β 1 β 0 β 1 β βββ β
2. β 0 β 1 β 1.905 β βββββ β
3. β 0 β 2 β 2.724 β βββββββ β
4. β 0 β 3 ... | {"source_file": "exponentialtimedecayedcount.md"} | [
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0.023402059450745583,
... |
c1e79a70-f266-48ac-a64a-caecdc0c4fbe | 38. β 0 β 37 β 10.273 β ββββββββββββββββββββββββββ β
39. β 0 β 38 β 10.296 β ββββββββββββββββββββββββββ β
40. β 0 β 39 β 10.316 β ββββββββββββββββββββββββββ β
41. β 1 β 40 β 10.334 β ββββββββββββββββββββββββββ β
42. β 0 β 41 β ... | {"source_file": "exponentialtimedecayedcount.md"} | [
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0.05144223943352699,
0.001609... |
67c95dd7-8948-4ce1-b236-f8e5c9254a3d | description: 'Calculates the sum of the numbers and counts the number of rows at the
same time. The function is used by ClickHouse query optimizer: if there are multiple
sum
,
count
or
avg
functions in a query, they can be replaced to single
sumCount
function to reuse the calculations. The function is rare... | {"source_file": "sumcount.md"} | [
0.0023849711287766695,
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0.07448366284370422,
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0.008732608519494534,
-0.021163588389754295,
0.09331854432821274,
-0.... |
6aa6ac55-69b8-48f2-9846-caf652979901 | description: 'Computes quantile of a histogram using linear interpolation.'
sidebar_position: 364
slug: /sql-reference/aggregate-functions/reference/quantilePrometheusHistogram
title: 'quantilePrometheusHistogram'
doc_type: 'reference'
quantilePrometheusHistogram
Computes
quantile
of a histogram using linear in... | {"source_file": "quantileprometheushistogram.md"} | [
-0.021258721128106117,
0.025522960349917412,
-0.014813249930739403,
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-0.0583522729575634,
0.055750180035829544,
-0.... |
a1a79f5e-f8b9-4cf0-9982-af035c15f3d3 | description: 'Calculate the sample variance of a data set. Unlike
varSamp
, this
function uses a numerically stable algorithm. It works slower but provides a lower
computational error.'
sidebar_position: 213
slug: /sql-reference/aggregate-functions/reference/varsampstable
title: 'varSampStable'
doc_type: 'referen... | {"source_file": "varsampstable.md"} | [
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0.028349503874778748,
0.0996118113398552,
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0.03693120554089546,
-0.012219822965562344,
0.04798821359872818,
0.03244689479470253,
-0.05741... |
44a3afb6-9b85-4a0b-80af-519e3e1d3896 | description: 'Returns an array of the approximately most frequent values in the specified
column. The resulting array is sorted in descending order of approximate frequency
of values (not by the values themselves).'
sidebar_position: 202
slug: /sql-reference/aggregate-functions/reference/topk
title: 'topK'
doc_type... | {"source_file": "topk.md"} | [
0.020301032811403275,
0.0076744891703128815,
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0.009395717643201351,
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0.03367584943771362,
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0.05522505193948746,
0.06543464958667755,
-0.13... |
a07e3e89-3cb6-499b-8921-196a61cb15a9 | description: 'Aggregate function that calculates the positions of the occurrences
of the maxIntersections function.'
sidebar_position: 164
slug: /sql-reference/aggregate-functions/reference/maxintersectionsposition
title: 'maxIntersectionsPosition'
doc_type: 'reference'
maxIntersectionsPosition
Aggregate functi... | {"source_file": "maxintersectionsposition.md"} | [
0.030591463670134544,
-0.044753581285476685,
0.04945719614624977,
-0.03891758620738983,
-0.10085207223892212,
0.001251472276635468,
0.004574815277010202,
0.06635361164808273,
0.00670063029974699,
-0.01707855612039566,
0.0214480459690094,
-0.010569947771728039,
0.01812306046485901,
-0.07574... |
4421af9a-7d95-4450-a618-7470b317d3b9 | description: 'The result is equal to the square root of varSamp. Unlike this function
uses a numerically stable algorithm.'
sidebar_position: 191
slug: /sql-reference/aggregate-functions/reference/stddevsampstable
title: 'stddevSampStable'
doc_type: 'reference'
stddevSampStable
The result is equal to the square... | {"source_file": "stddevsampstable.md"} | [
0.0006219953647814691,
-0.0056455498561263084,
0.008973226882517338,
0.008364505134522915,
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0.01201719418168068,
0.09090496599674225,
0.005566076375544071,
0.007354688830673695,
0.04705105721950531,
0.021823061630129814,
0.06065724417567253,
-0.1... |
bda7ea22-db27-42cf-b676-d02809808665 | description: 'Calculates the population variance.'
sidebar_position: 210
slug: /sql-reference/aggregate-functions/reference/varPop
title: 'varPop'
doc_type: 'reference'
varPop {#varpop}
Calculates the population variance:
$$
\frac{\Sigma{(x - \bar{x})^2}}{n}
$$
Syntax
sql
varPop(x)
Alias:
VAR_POP
.
Par... | {"source_file": "varpop.md"} | [
0.01441159751266241,
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0.03168749064207077,
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0.004355562385171652,
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-0.0512017086148262,
0.05412653088569641,
-0.12747351... |
e79a0054-4460-4732-959d-ebaf28e1bc24 | description: 'Exactly computes the quantile of a numeric data sequence, taking into
account the weight of each element.'
sidebar_position: 174
slug: /sql-reference/aggregate-functions/reference/quantileexactweighted
title: 'quantileExactWeighted'
doc_type: 'reference'
quantileExactWeighted
Exactly computes the ... | {"source_file": "quantileexactweighted.md"} | [
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0.011839677579700947,
0.027364088222384453,
0.02320001646876335,
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0.04338052496314049,
0.07052642852067947,
0.008163739927113056,
0.0028900306206196547,
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-0.03844388946890831,
0.03750813379883766,
-0.06... |
1698871d-1821-4a4b-bb44-019aa9712cd2 | description: 'Returns the population covariance matrix over N variables.'
sidebar_position: 122
slug: /sql-reference/aggregate-functions/reference/covarpopmatrix
title: 'covarPopMatrix'
doc_type: 'reference'
covarPopMatrix
Returns the population covariance matrix over N variables.
Syntax
sql
covarPopMatrix(x[... | {"source_file": "covarpopmatrix.md"} | [
0.048841264098882675,
-0.008885180577635765,
-0.07834908366203308,
0.04722127318382263,
-0.06126659736037254,
-0.02794906497001648,
0.030040768906474113,
-0.05244719609618187,
-0.0613013356924057,
0.022329004481434822,
0.10194358229637146,
-0.0630585253238678,
0.025064686313271523,
-0.0858... |
2099e10b-638a-40c2-97c4-d0f9dc79d4da | description: 'The function plots a frequency histogram for values
x
and the repetition
rate
y
of these values over the interval
[min_x, max_x]
.'
sidebar_label: 'sparkbar'
sidebar_position: 187
slug: /sql-reference/aggregate-functions/reference/sparkbar
title: 'sparkbar'
doc_type: 'reference'
sparkbar
The ... | {"source_file": "sparkbar.md"} | [
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0.029800422489643097,
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0.040146324783563614,
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-0.06143094226717949,
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-0.03322219103574753,
0.07187943160533905,
-0.... |
a8c6a5bf-2e9e-43c1-8fee-12c6a8283d61 | description: 'The
contingency
function calculates the contingency coefficient, a
value that measures the association between two columns in a table. The computation
is similar to the
cramersV
function but with a different denominator in the square
root.'
sidebar_position: 116
slug: /sql-reference/aggregate-fu... | {"source_file": "contingency.md"} | [
-0.03282719850540161,
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0.013951854780316353,
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0.05069805309176445,
0.08309207111597061,
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0.002070343354716897,
0.00815511867403984,
-0.02217782847583294,
0.04475617781281471,
-0.0... |
0b7edeca-999d-4f62-936d-de2ea75ce2b2 | description: 'This function implements stochastic linear regression. It supports custom
parameters for learning rate, L2 regularization coefficient, mini-batch size, and
has a few methods for updating weights (Adam, simple SGD, Momentum, Nesterov.)'
sidebar_position: 192
slug: /sql-reference/aggregate-functions/ref... | {"source_file": "stochasticlinearregression.md"} | [
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0.02868536114692688,
0.0003018066636286676,
0.008218887262046337,
-0.02873709797859192,
-0.04357236996293068,
0.03567155450582504,
0.041374996304512024,
-0.052998218685388565,
-0.1... |
b78ec9aa-e919-4d04-9fd6-c2074670afb6 | 2.
Predicting
After saving a state into the table, we may use it multiple times for prediction or even merge with other states and create new, even better models.
sql
WITH (SELECT state FROM your_model) AS model SELECT
evalMLMethod(model, param1, param2) FROM test_data
The query will return a column of predicted... | {"source_file": "stochasticlinearregression.md"} | [
-0.08581724762916565,
-0.06367165595293045,
-0.06363050639629364,
0.13091273605823517,
0.0318668931722641,
0.0033726077526807785,
0.06034671515226364,
0.05786766856908798,
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-0.0590912401676178,
0.03540068492293358,
-0.05090764909982681,
0.05331723019480705,
-0.0630561... |
2fa6df3f-7e90-4ba4-8442-e8ea4b578d92 | description: 'Provides a statistical test for one-way analysis of variance (ANOVA
test). It is a test over several groups of normally distributed observations to
find out whether all groups have the same mean or not.'
sidebar_position: 101
slug: /sql-reference/aggregate-functions/reference/analysis_of_variance
titl... | {"source_file": "analysis_of_variance.md"} | [
0.028773048892617226,
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0.03252045065164566,
0.00647842837497592,
-0.05693143233656883,
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0.05444081500172615,
0.03470967337489128,
0.030358390882611275,
0.017726799473166466,
0.020084723830223083,
-0.021485844627022743,
0.004641978535801172,
-0.015... |
6278725c-93cd-4ae2-bb2b-c7ede03b0c17 | description: 'Aggregate function that calculates PromQL-like resets over time series data on the specified grid.'
sidebar_position: 230
slug: /sql-reference/aggregate-functions/reference/timeSeriesResetsToGrid
title: 'timeSeriesResetsToGrid'
doc_type: 'reference'
Aggregate function that takes time series data as pa... | {"source_file": "timeSeriesResetsToGrid.md"} | [
-0.12168758362531662,
-0.006407720968127251,
-0.08571506291627884,
0.08752690255641937,
-0.06638512015342712,
-0.0035526244901120663,
0.0008013423648662865,
0.05492984130978584,
0.034373145550489426,
-0.006875900086015463,
-0.05007757991552353,
-0.02687799744307995,
-0.022512245923280716,
... |
93af4381-ce27-4e6d-a55c-f301013099ec | :::note
This function is experimental, enable it by setting
allow_experimental_ts_to_grid_aggregate_function=true
.
::: | {"source_file": "timeSeriesResetsToGrid.md"} | [
-0.04617350548505783,
-0.037194281816482544,
-0.013469654135406017,
0.09186480939388275,
0.022367699071764946,
0.004247533623129129,
0.002288512885570526,
-0.07123781740665436,
0.0007586118299514055,
0.07126599550247192,
-0.006106517277657986,
-0.012565995566546917,
-0.00505802920088172,
-... |
93122194-ff39-4cd5-b25b-742d66f94303 | description: 'Calculates a concatenated string from a group of strings, optionally
separated by a delimiter, and optionally limited by a maximum number of elements.'
sidebar_label: 'groupConcat'
sidebar_position: 363
slug: /sql-reference/aggregate-functions/reference/groupconcat
title: 'groupConcat'
doc_type: 'refere... | {"source_file": "groupconcat.md"} | [
0.02452375739812851,
0.014115409925580025,
-0.03517678752541542,
0.0429806262254715,
-0.05935696139931679,
0.024213887751102448,
0.08726494014263153,
0.05176921188831329,
-0.027824338525533676,
-0.042496562004089355,
0.051443979144096375,
-0.0346212200820446,
0.05917811021208763,
-0.135179... |
9bed5354-add2-452a-8040-7e5c66f6adc7 | description: 'Returns the maximum of the computed exponentially smoothed moving average
at index
t
in time with that at
t-1
. '
sidebar_position: 135
slug: /sql-reference/aggregate-functions/reference/exponentialTimeDecayedMax
title: 'exponentialTimeDecayedMax'
doc_type: 'reference'
exponentialTimeDecayedMax {... | {"source_file": "exponentialtimedecayedmax.md"} | [
-0.07823941111564636,
-0.059251975268125534,
0.010187679901719093,
-0.0018608906539157033,
-0.05627407878637314,
-0.10420355200767517,
0.07351403683423996,
0.07090736925601959,
0.015245992690324783,
0.015106003731489182,
0.022353006526827812,
-0.07012749463319778,
0.059211935847997665,
-0.... |
9324c5c6-e1b3-49e2-b4ea-327532fd0356 | Result:
response
ββvalueββ¬βtimeββ¬βround(exp_smooth, 3)ββ¬βbarβββββββββ
1. β 1 β 0 β 1 β ββββββββββ β
2. β 0 β 1 β 0.905 β βββββββββ β
3. β 0 β 2 β 0.819 β βββββββββ β
4. β 0 β 3 β 0.741 β ββββββββ β
5. β 0 β ... | {"source_file": "exponentialtimedecayedmax.md"} | [
-0.07088932394981384,
-0.004207790829241276,
-0.01858203113079071,
0.007326469291001558,
-0.015286010690033436,
-0.13404949009418488,
0.04915459826588631,
-0.026068631559610367,
-0.011233176104724407,
0.03507913649082184,
0.061965376138687134,
-0.06657350808382034,
0.01880638487637043,
-0.... |
d7533588-1d59-4d92-a562-554a00063fb8 | description: 'Selects the first encountered value of a column.'
sidebar_position: 102
slug: /sql-reference/aggregate-functions/reference/any
title: 'any'
doc_type: 'reference'
any
Selects the first encountered value of a column.
:::warning
As a query can be executed in arbitrary order, the result of this functi... | {"source_file": "any.md"} | [
-0.00964006781578064,
-0.0035943251568824053,
-0.02271316945552826,
0.031792402267456055,
-0.04503073915839195,
0.0009679798968136311,
0.0423256941139698,
0.04810962826013565,
0.02124776504933834,
0.03324991464614868,
0.06732238829135895,
-0.04184512048959732,
0.0279457475990057,
-0.091403... |
1380e6b4-351e-4c09-8f57-6c5d4a0fe24d | description: 'Returns the sample covariance matrix over N variables.'
sidebar_position: 125
slug: /sql-reference/aggregate-functions/reference/covarsampmatrix
title: 'covarSampMatrix'
doc_type: 'reference'
covarSampMatrix
Returns the sample covariance matrix over N variables.
Syntax
sql
covarSampMatrix(x[, ..... | {"source_file": "covarsampmatrix.md"} | [
0.021804623305797577,
-0.00886972714215517,
-0.08329237252473831,
0.025271914899349213,
-0.04889749363064766,
-0.028407590463757515,
0.0570426769554615,
-0.01879201829433441,
-0.04672694951295853,
0.021160097792744637,
0.048391684889793396,
-0.03078167326748371,
0.01445781160145998,
-0.083... |
f9edf6ea-359c-4f15-81c1-02d13c962297 | description: 'Aggregate function that calculates PromQL-like irate over time series data on the specified grid.'
sidebar_position: 223
slug: /sql-reference/aggregate-functions/reference/timeSeriesInstantRateToGrid
title: 'timeSeriesInstantRateToGrid'
doc_type: 'reference'
Aggregate function that takes time series d... | {"source_file": "timeSeriesInstantRateToGrid.md"} | [
-0.06053175404667854,
0.019316812977194786,
-0.13510777056217194,
0.048816680908203125,
-0.006379064172506332,
-0.04618095979094505,
0.043286241590976715,
0.06883393228054047,
0.05217159911990166,
0.0052466364577412605,
-0.02594233863055706,
-0.039088621735572815,
0.003449457697570324,
-0.... |
a72d8ddb-3f95-4fd0-94bd-9698cd5738de | :::note
This function is experimental, enable it by setting
allow_experimental_ts_to_grid_aggregate_function=true
.
::: | {"source_file": "timeSeriesInstantRateToGrid.md"} | [
-0.04617350548505783,
-0.037194281816482544,
-0.013469654135406017,
0.09186480939388275,
0.022367699071764946,
0.004247533623129129,
0.002288512885570526,
-0.07123781740665436,
0.0007586118299514055,
0.07126599550247192,
-0.006106517277657986,
-0.012565995566546917,
-0.00505802920088172,
-... |
4350d593-540d-4966-ac7e-4a754db5b3ee | description: 'Creates an array of the last argument values.'
sidebar_position: 142
slug: /sql-reference/aggregate-functions/reference/grouparraylast
title: 'groupArrayLast'
doc_type: 'reference'
groupArrayLast
Syntax:
groupArrayLast(max_size)(x)
Creates an array of the last argument values.
For example,
group... | {"source_file": "grouparraylast.md"} | [
0.008255413733422756,
0.031250301748514175,
0.031296443194150925,
-0.000969285611063242,
-0.05785829573869705,
-0.02867140807211399,
0.007680272683501244,
0.0373331643640995,
0.05897735059261322,
-0.02105502039194107,
-0.033465851098299026,
0.14988075196743011,
0.00647264439612627,
-0.0736... |
37e235bf-7bcd-47f9-a214-510c4189bad3 | description: 'The aggregate function
singleValueOrNull
is used to implement subquery
operators, such as
x = ALL (SELECT ...)
. It checks if there is only one unique
non-NULL value in the data.'
sidebar_position: 184
slug: /sql-reference/aggregate-functions/reference/singlevalueornull
title: 'singleValueOrNull'
d... | {"source_file": "singlevalueornull.md"} | [
0.01358381099998951,
0.009724230505526066,
0.020755602046847343,
-0.005870559718459845,
-0.08209377527236938,
0.003172901924699545,
0.047264281660318375,
0.03883053734898567,
0.014983909204602242,
-0.02787274867296219,
0.047644004225730896,
-0.0747571736574173,
0.08801870793104172,
-0.1325... |
a2f0d27d-ee72-42ad-81ee-b629a86ace0e | description: 'The
theilsU
function calculates Theils'' U uncertainty coefficient,
a value that measures the association between two columns in a table.'
sidebar_position: 201
slug: /sql-reference/aggregate-functions/reference/theilsu
title: 'theilsU'
doc_type: 'reference'
theilsU
The
theilsU
function calcul... | {"source_file": "theilsu.md"} | [
-0.020878814160823822,
-0.0013982170494273305,
-0.08803881704807281,
0.02040642872452736,
-0.07903474569320679,
-0.053505171090364456,
0.007591625209897757,
0.052386123687028885,
-0.004136613104492426,
-0.0436803475022316,
0.07824808359146118,
-0.09644225239753723,
0.10168316215276718,
-0.... |
c9fa58bf-42be-4fbd-83ab-72166ec5a147 | description: 'The result of the
cramersV
function ranges from 0 (corresponding to
no association between the variables) to 1 and can reach 1 only when each value
is completely determined by the other. It may be viewed as the association between
two variables as a percentage of their maximum possible variation.'... | {"source_file": "cramersv.md"} | [
0.014992996118962765,
-0.0598301887512207,
-0.12568341195583344,
0.019290927797555923,
0.005821262951940298,
0.0534680150449276,
0.001782165956683457,
0.04661202430725098,
-0.04243621975183487,
0.008016841486096382,
-0.023984218016266823,
-0.008113726042211056,
0.029152482748031616,
0.0169... |
18ec9d11-46e0-429f-878c-bd524036a123 | description: 'Selects the last encountered value, similar to
anyLast
, but could
accept NULL.'
sidebar_position: 160
slug: /sql-reference/aggregate-functions/reference/last_value
title: 'last_value'
doc_type: 'reference'
last_value
Selects the last encountered value, similar to
anyLast
, but could accept NULL... | {"source_file": "last_value.md"} | [
-0.018264170736074448,
0.040359016507864,
0.013237888924777508,
0.026895929127931595,
-0.021418364718556404,
0.038726478815078735,
0.014242758974432945,
0.018881358206272125,
0.006185146514326334,
0.028515566140413284,
0.02137397602200508,
-0.035825591534376144,
0.029704829677939415,
-0.10... |
87279782-0484-404f-98e6-83b5b2ba03c8 | description: 'With the determined precision computes the quantile of a numeric data
sequence.'
sidebar_position: 180
slug: /sql-reference/aggregate-functions/reference/quantiletiming
title: 'quantileTiming'
doc_type: 'reference'
quantileTiming
With the determined precision computes the
quantile
of a numeric d... | {"source_file": "quantiletiming.md"} | [
-0.05667293816804886,
-0.0026105011347681284,
0.01837890036404133,
0.017377063632011414,
-0.11019139736890793,
-0.07460471987724304,
0.0013701367424800992,
0.07866253703832626,
0.0028651102911680937,
0.00821702741086483,
-0.0006566020892933011,
-0.0888800173997879,
0.021485362201929092,
-0... |
159d5b82-7df7-438c-a0e7-05701561928b | description: 'Bitmap or Aggregate calculations from a unsigned integer column, return
cardinality of type UInt64, if add suffix -State, then return a bitmap object'
sidebar_position: 148
slug: /sql-reference/aggregate-functions/reference/groupbitmap
title: 'groupBitmap'
doc_type: 'reference'
groupBitmap
Bitmap ... | {"source_file": "groupbitmap.md"} | [
0.035628657788038254,
0.10637380182743073,
-0.01938793435692787,
0.04958935081958771,
-0.12214002758264542,
0.015148957259953022,
0.04465058445930481,
0.014688168652355671,
-0.06170973181724548,
-0.03527972474694252,
0.02265886403620243,
-0.08913332968950272,
0.061562880873680115,
-0.05782... |
3135e8f9-ea9a-4da9-81d7-00f24317801e | description: 'Calculates the minimum from
value
array according to the keys specified
in the
key
array.'
sidebar_position: 169
slug: /sql-reference/aggregate-functions/reference/minmap
title: 'minMap'
doc_type: 'reference'
minMap
Calculates the minimum from
value
array according to the keys specified in t... | {"source_file": "minmap.md"} | [
0.07127900421619415,
0.06953177601099014,
-0.014546315185725689,
-0.022006725892424583,
-0.09212352335453033,
0.0031081160996109247,
0.0708337277173996,
0.07195337116718292,
-0.034124620258808136,
-0.0037202653475105762,
0.012573196552693844,
-0.052080899477005005,
0.11634216457605362,
-0.... |
5576ca2d-9c74-46de-b7a2-1a9537574f49 | description: 'Returns the exponentially smoothed weighted moving average of values
of a time series at point
t
in time.'
sidebar_position: 133
slug: /sql-reference/aggregate-functions/reference/exponentialTimeDecayedAvg
title: 'exponentialTimeDecayedAvg'
doc_type: 'reference'
exponentialTimeDecayedAvg {#exponen... | {"source_file": "exponentialtimedecayedavg.md"} | [
-0.10797903686761856,
-0.04691558703780174,
-0.01697118580341339,
0.061787236481904984,
-0.05396736413240433,
-0.10006655007600784,
0.09778919816017151,
0.03697466105222702,
0.03626035898923874,
-0.004059751518070698,
0.03989621624350548,
-0.10031181573867798,
0.04383737966418266,
-0.03941... |
787c48e7-24d1-42cc-b18c-c7494471c1d8 | Response:
sql
ββvalueββ¬βtimeββ¬βround(exp_smooth, 3)ββ¬βbarβββββββββ
1. β 1 β 0 β 1 β ββββββββββ β
2. β 0 β 1 β 0.475 β βββββ β
3. β 0 β 2 β 0.301 β βββ β
4. β 0 β 3 β 0.214 β βββ β
5. β 0 β 4 β ... | {"source_file": "exponentialtimedecayedavg.md"} | [
-0.030177047476172447,
-0.05252765864133835,
-0.02834406867623329,
0.04259036108851433,
-0.046888478100299835,
-0.10587906837463379,
0.08679560571908951,
-0.028901811689138412,
-0.061887551099061966,
0.07137588411569595,
0.07147925347089767,
-0.08400993794202805,
0.0042009237222373486,
-0.... |
8d4014ad-7558-486f-9270-073f1856934b | description: 'Aggregate function that calculates PromQL-like idelta over time series data on the specified grid.'
sidebar_position: 222
slug: /sql-reference/aggregate-functions/reference/timeSeriesInstantDeltaToGrid
title: 'timeSeriesInstantDeltaToGrid'
doc_type: 'reference'
Aggregate function that takes time serie... | {"source_file": "timeSeriesInstantDeltaToGrid.md"} | [
-0.08710699528455734,
-0.014406213536858559,
-0.09601826965808868,
0.05012832209467888,
-0.04949557036161423,
-0.03963586688041687,
0.017825495451688766,
0.0840180367231369,
0.04921916127204895,
0.020779622718691826,
-0.013484800234436989,
-0.05350353941321373,
0.0010546682169660926,
-0.01... |
5af55d7b-ee02-49f3-b0c4-33a238ddf516 | :::note
This function is experimental, enable it by setting
allow_experimental_ts_to_grid_aggregate_function=true
.
::: | {"source_file": "timeSeriesInstantDeltaToGrid.md"} | [
-0.04617350548505783,
-0.037194281816482544,
-0.013469654135406017,
0.09186480939388275,
0.022367699071764946,
0.004247533623129129,
0.002288512885570526,
-0.07123781740665436,
0.0007586118299514055,
0.07126599550247192,
-0.006106517277657986,
-0.012565995566546917,
-0.00505802920088172,
-... |
d8ea1acc-8a99-4f9e-8b11-8416c1c3ce6c | description: 'Computes the skewness of a sequence.'
sidebar_position: 185
slug: /sql-reference/aggregate-functions/reference/skewpop
title: 'skewPop'
doc_type: 'reference'
skewPop
Computes the
skewness
of a sequence.
sql
skewPop(expr)
Arguments
expr
β
Expression
returning a number.
Returned value
T... | {"source_file": "skewpop.md"} | [
-0.09742235392332077,
0.011957000941038132,
-0.047984641045331955,
0.006786075886338949,
-0.03981994464993477,
-0.013179996982216835,
0.009067421779036522,
0.051077667623758316,
0.04804566502571106,
-0.04379099979996681,
0.07552586495876312,
-0.00250240508466959,
-0.007751955650746822,
-0.... |
06e66c9e-b82e-4c27-adc7-c032c2ad082d | description: 'Applies the Mann-Whitney rank test to samples from two populations.'
sidebar_label: 'mannWhitneyUTest'
sidebar_position: 161
slug: /sql-reference/aggregate-functions/reference/mannwhitneyutest
title: 'mannWhitneyUTest'
doc_type: 'reference'
mannWhitneyUTest
Applies the Mann-Whitney rank test to samp... | {"source_file": "mannwhitneyutest.md"} | [
0.052364494651556015,
0.019673040136694908,
0.010414870455861092,
0.04787549376487732,
-0.0059816245920956135,
0.017966710031032562,
-0.013941575773060322,
0.029635854065418243,
-0.10080848634243011,
0.021098028868436813,
0.056691113859415054,
-0.11376750469207764,
0.0772872120141983,
-0.0... |
65f9be11-6ef1-4265-9858-f20996e5a6f3 | description: 'Computes the quantile of a numeric data sequence using the Greenwald-Khanna
algorithm.'
sidebar_position: 175
slug: /sql-reference/aggregate-functions/reference/quantileGK
title: 'quantileGK'
doc_type: 'reference'
quantileGK
Computes the
quantile
of a numeric data sequence using the
Greenwald-K... | {"source_file": "quantileGK.md"} | [
-0.1084093227982521,
0.04076549410820007,
-0.0572059266269207,
-0.04715891554951668,
-0.09443962574005127,
-0.11292005330324173,
0.025854505598545074,
0.04293840751051903,
0.02672533690929413,
-0.049133799970149994,
-0.03176618739962578,
-0.00559206260368228,
0.0012259940849617124,
-0.0418... |
5f083021-cfe2-48cc-96a4-e58d2e109af9 | ββquantileGK(100, 0.25)(plus(number, 1))ββ
β 251 β
ββββββββββββββββββββββββββββββββββββββββββ
SELECT quantileGK(1000, 0.25)(number + 1)
FROM numbers(1000)
ββquantileGK(1000, 0.25)(plus(number, 1))ββ
β 249 β
ββββββββββββββββββββββββββββββββββββββ... | {"source_file": "quantileGK.md"} | [
-0.0019856838043779135,
0.019457798451185226,
0.025586076080799103,
-0.04976389557123184,
-0.038182370364665985,
-0.0423649437725544,
0.08222802728414536,
0.04794514551758766,
0.0034725407604128122,
0.03759560361504555,
0.029070887714624405,
-0.08270762860774994,
0.053823042660951614,
-0.0... |
6fba06d7-68b3-48ed-9a8f-a066b6559b73 | description: 'Return an intersection of given arrays (Return all items of arrays,
that are in all given arrays).'
sidebar_position: 141
slug: /sql-reference/aggregate-functions/reference/grouparrayintersect
title: 'groupArrayIntersect'
doc_type: 'reference'
groupArrayIntersect
Return an intersection of given ar... | {"source_file": "grouparrayintersect.md"} | [
0.061398670077323914,
-0.009873652830719948,
-0.013833082281053066,
0.04149113595485687,
-0.004295438062399626,
-0.025697018951177597,
0.13022778928279877,
-0.0592762753367424,
-0.06796469539403915,
-0.03543096408247948,
-0.03636499121785164,
0.02301528863608837,
0.021533114835619926,
-0.0... |
998c6ca0-56ab-425f-af1c-426b7430e7c1 | description: 'Estimates the compression ratio of a given column without compressing
it.'
sidebar_position: 132
slug: /sql-reference/aggregate-functions/reference/estimateCompressionRatio
title: 'estimateCompressionRatio'
doc_type: 'reference'
estimateCompressionRatio {#estimatecompressionration}
Estimates the c... | {"source_file": "estimateCompressionRatio.md"} | [
-0.054772667586803436,
0.03732019290328026,
-0.1108098104596138,
0.05379989743232727,
-0.023301642388105392,
-0.03743823245167732,
-0.039860595017671585,
0.09818064421415329,
-0.05915483832359314,
0.009469196200370789,
-0.03901473805308342,
-0.07491567730903625,
0.05759343132376671,
-0.080... |
9cefc005-0760-4fd1-9348-0c3d2fc55713 | description: 'Creates an array of sample argument values. The size of the resulting
array is limited to
max_size
elements. Argument values are selected and added
to the array randomly.'
sidebar_position: 145
slug: /sql-reference/aggregate-functions/reference/grouparraysample
title: 'groupArraySample'
doc_type: 'r... | {"source_file": "grouparraysample.md"} | [
0.023385541513562202,
-0.0016196968499571085,
-0.03656516969203949,
0.06916739791631699,
0.0024041556753218174,
-0.008866490796208382,
0.1016763299703598,
-0.07437092810869217,
-0.008948670700192451,
-0.02324550971388817,
-0.028470028191804886,
0.025250732898712158,
0.04864881560206413,
-0... |
00d3021a-1d10-41d9-8f5a-eeb86a3fab63 | description: 'The result is equal to the square root of varSamp'
sidebar_position: 190
slug: /sql-reference/aggregate-functions/reference/stddevsamp
title: 'stddevSamp'
doc_type: 'reference'
stddevSamp
The result is equal to the square root of
varSamp
.
Alias:
STDDEV_SAMP
.
:::note
This function uses a nume... | {"source_file": "stddevsamp.md"} | [
-0.009841266088187695,
0.004789599683135748,
0.02090964838862419,
0.019633445888757706,
-0.06539098173379898,
-0.015230325050652027,
0.0436522476375103,
0.12785163521766663,
0.02421584352850914,
-0.003941020462661982,
0.04625684767961502,
-0.0019208879675716162,
0.034389182925224304,
-0.10... |
992cc128-47ca-44d4-bb4e-3538e7d6882a | description: 'Landing page for aggregate functions with complete list of aggregate
functions'
sidebar_position: 36
slug: /sql-reference/aggregate-functions/reference/
title: 'Aggregate Functions'
toc_folder_title: 'Reference'
toc_hidden: true
doc_type: 'landing-page'
Aggregate functions
ClickHouse supports all ... | {"source_file": "index.md"} | [
0.00044325541239231825,
-0.11637332290410995,
-0.01449220534414053,
0.049585770815610886,
-0.0440010167658329,
0.049642760306596756,
-0.01276326458901167,
0.04722421243786812,
-0.033840131014585495,
0.015317766927182674,
-0.007159699220210314,
-0.006110537331551313,
0.0365159809589386,
-0.... |
1dd1a687-1588-4b72-819b-482d1a78b57c | description: 'Computes an approximate quantile of a numeric data sequence.'
sidebar_position: 170
slug: /sql-reference/aggregate-functions/reference/quantile
title: 'quantile'
doc_type: 'reference'
quantile
Computes an approximate
quantile
of a numeric data sequence.
This function applies
reservoir sampling
... | {"source_file": "quantile.md"} | [
-0.06025293841958046,
-0.014578370377421379,
0.024190014228224754,
-0.0018599762115627527,
-0.060115084052085876,
-0.1038094088435173,
0.05484123155474663,
0.07549737393856049,
0.01144056860357523,
-0.021187826991081238,
-0.05515257269144058,
-0.11481669545173645,
0.01337695773690939,
-0.0... |
0bd69d70-4d70-4e5f-8cfd-9018035b1aa8 | description: 'Creates an array of argument values. Values can be added to the array
in any (indeterminate) order.'
sidebar_position: 139
slug: /sql-reference/aggregate-functions/reference/grouparray
title: 'groupArray'
doc_type: 'reference'
groupArray
Syntax:
groupArray(x)
or
groupArray(max_size)(x)
Create... | {"source_file": "grouparray.md"} | [
0.006038210820406675,
0.021637720987200737,
-0.014486867003142834,
0.03267877548933029,
-0.04919998720288277,
-0.007091797422617674,
0.004749896936118603,
0.017719054594635963,
0.043360255658626556,
-0.030583489686250687,
-0.011460074223577976,
0.09620892256498337,
0.029872415587306023,
-0... |
49c2a7bb-4f0c-4bd1-8dd2-0f68832f563d | description: 'Returns the sum of exponentially smoothed moving average values of a
time series at the index
t
in time.'
sidebar_position: 136
slug: /sql-reference/aggregate-functions/reference/exponentialTimeDecayedSum
title: 'exponentialTimeDecayedSum'
doc_type: 'reference'
exponentialTimeDecayedSum {#exponent... | {"source_file": "exponentialtimedecayedsum.md"} | [
-0.10303454101085663,
-0.04049541801214218,
-0.004072993062436581,
0.04721788689494133,
-0.03074544109404087,
-0.07659495621919632,
0.12378331273794174,
0.02379786968231201,
0.03419151529669762,
0.0020095992367714643,
0.047009341418743134,
-0.11448642611503601,
0.04756614938378334,
-0.0571... |
13c7e25c-847a-4aeb-86c2-410aefd9616a | response
ββvalueββ¬βtimeββ¬βround(exp_smooth, 3)ββ¬βbarββββββββββββββββββββββββββββββββββββββββββββββββ
1. β 1 β 0 β 1 β βββββ β
2. β 0 β 1 β 0.905 β βββββ β
3. β 0 β 2 β ... | {"source_file": "exponentialtimedecayedsum.md"} | [
-0.08743393421173096,
-0.0042401524260640144,
-0.013094599358737469,
0.007450675591826439,
-0.013715323060750961,
-0.12748801708221436,
0.057339176535606384,
-0.044873565435409546,
-0.028813380748033524,
0.034526728093624115,
0.05758565664291382,
-0.05693399906158447,
0.020420949906110764,
... |
78f5ca42-42d7-4b47-9941-f5e609f1a6dc | 29. β 1 β 28 β 3.525 β ββββββββββββββββββ β
30. β 1 β 29 β 4.19 β βββββββββββββββββββββ β
31. β 1 β 30 β 4.791 β ββββββββββββββββββββββββ β
32. β 1 β 31 β ... | {"source_file": "exponentialtimedecayedsum.md"} | [
0.006419220007956028,
-0.0013311897637322545,
-0.03073887713253498,
-0.03607700765132904,
0.004249317571520805,
-0.05549175664782524,
0.047881923615932465,
-0.03243021294474602,
-0.0590481236577034,
0.1128634512424469,
0.034665729850530624,
-0.018558310344815254,
0.0769602432847023,
-0.014... |
ede20473-96b4-4760-aa52-d88e93832b21 | description: 'Calculates the value of
(P(tag = 1) - P(tag = 0))(log(P(tag = 1)) -
log(P(tag = 0)))
for each category.'
sidebar_position: 115
slug: /sql-reference/aggregate-functions/reference/categoricalinformationvalue
title: 'categoricalInformationValue'
doc_type: 'reference'
Calculates the value of
(P(tag =... | {"source_file": "categoricalinformationvalue.md"} | [
0.03774235025048256,
0.024295270442962646,
-0.01492798700928688,
0.0410105399787426,
-0.01297577004879713,
-0.0028623463585972786,
0.06222856789827347,
0.05390365794301033,
0.03597138822078705,
-0.022197507321834564,
0.011195894330739975,
-0.08572209626436234,
0.0028500379994511604,
-0.043... |
05ac6bed-72c3-4d36-879d-c161674b0572 | description: 'Calculates the Pearson correlation coefficient.'
sidebar_position: 117
slug: /sql-reference/aggregate-functions/reference/corr
title: 'corr'
doc_type: 'reference'
corr
Calculates the
Pearson correlation coefficient
:
$$
\frac{\Sigma{(x - \bar{x})(y - \bar{y})}}{\sqrt{\Sigma{(x - \bar{x})^2} * \Si... | {"source_file": "corr.md"} | [
-0.020083293318748474,
-0.095804862678051,
-0.0129557428881526,
0.026442112401127815,
-0.07500258088111877,
-0.022801171988248825,
0.01390058733522892,
0.03564770519733429,
-0.009039437398314476,
0.027896542102098465,
0.02475225180387497,
-0.013715649954974651,
0.02357875183224678,
-0.0518... |
93fb83c2-12f8-449c-b375-fde9223f69ed | description: 'Returns an array of the approximately most frequent values and their
counts in the specified column.'
sidebar_position: 107
slug: /sql-reference/aggregate-functions/reference/approxtopk
title: 'approx_top_k'
doc_type: 'reference'
approx_top_k
Returns an array of the approximately most frequent val... | {"source_file": "approxtopk.md"} | [
0.028492962941527367,
0.007934893481433392,
-0.07430361956357956,
0.032636817544698715,
-0.08321544528007507,
-0.014312513172626495,
0.0440170094370842,
0.08677205443382263,
0.003046203637495637,
-0.005191211588680744,
0.014035661704838276,
0.012828212231397629,
0.08676479011774063,
-0.115... |
c3f7ebb0-2e20-4775-ba71-c666cb5e26d0 | description: 'Computes the correlation matrix over N variables.'
sidebar_position: 118
slug: /sql-reference/aggregate-functions/reference/corrmatrix
title: 'corrMatrix'
doc_type: 'reference'
corrMatrix
Computes the correlation matrix over N variables.
Syntax
sql
corrMatrix(x[, ...])
Arguments
x
β a var... | {"source_file": "corrmatrix.md"} | [
0.006173374596983194,
-0.030527165159583092,
-0.10094638168811798,
0.04924479126930237,
-0.08989378809928894,
-0.015153445303440094,
-0.017777668312191963,
-0.04961032420396805,
-0.038603950291872025,
0.020920943468809128,
0.04860888794064522,
-0.009155279025435448,
0.033517688512802124,
-... |
8d881261-9fd5-49e4-840b-f9a11436fe36 | description: 'Computes an approximate quantile of a sample with relative-error guarantees.'
sidebar_position: 171
slug: /sql-reference/aggregate-functions/reference/quantileddsketch
title: 'quantileDD'
doc_type: 'reference'
Computes an approximate
quantile
of a sample with relative-error guarantees. It works by b... | {"source_file": "quantileddsketch.md"} | [
-0.016947651281952858,
-0.013619715347886086,
-0.04669088497757912,
-0.02664467692375183,
-0.0550876148045063,
-0.08590181916952133,
-0.006631446070969105,
0.08983885496854782,
-0.040659110993146896,
-0.016562316566705704,
-0.012540343217551708,
-0.054415348917245865,
0.0540078729391098,
-... |
1bd6967d-af9a-43ee-b31d-8e8a9f8b6df3 | description: 'Sorts time series by timestamp in ascending order.'
sidebar_position: 146
slug: /sql-reference/aggregate-functions/reference/timeSeriesGroupArray
title: 'timeSeriesGroupArray'
doc_type: 'reference'
timeSeriesGroupArray
Sorts time series by timestamp in ascending order.
Syntax
sql
timeSeriesGroup... | {"source_file": "timeSeriesGroupArray.md"} | [
-0.06375601887702942,
-0.01981058157980442,
0.03909418731927872,
-0.04085761308670044,
-0.059491582214832306,
-0.026549579575657845,
0.033977873623371124,
0.0226153451949358,
0.0008906075963750482,
0.02628250978887081,
-0.05067726969718933,
0.01289262156933546,
-0.039713628590106964,
0.016... |
d66a89b3-00ed-492f-ac8b-39746ef84103 | description: 'Selects a frequently occurring value using the heavy hitters algorithm.
If there is a value that occurs more than in half the cases in each of the query
execution threads, this value is returned. Normally, the result is nondeterministic.'
sidebar_position: 104
slug: /sql-reference/aggregate-functions/... | {"source_file": "anyheavy.md"} | [
0.05716777592897415,
0.0018218717304989696,
-0.016273029148578644,
0.11966165155172348,
-0.004298589192330837,
-0.04024434834718704,
0.004487235564738512,
-0.008138642646372318,
0.06534328311681747,
0.009295839816331863,
0.03844776377081871,
-0.023899080231785774,
-0.007323036901652813,
-0... |
3cfbc994-40ba-4e65-97e7-66fa1367f195 | description: 'Computes an approximate quantile of a sample consisting of bfloat16
numbers.'
sidebar_position: 171
slug: /sql-reference/aggregate-functions/reference/quantilebfloat16
title: 'quantileBFloat16'
doc_type: 'reference'
quantileBFloat16Weighted
Like
quantileBFloat16
but takes into account the weight... | {"source_file": "quantilebfloat16.md"} | [
-0.040612224489450455,
0.041230209171772,
-0.07102710008621216,
-0.028071127831935883,
-0.005505031906068325,
-0.12508203089237213,
0.04078766331076622,
0.06269349157810211,
-0.03989233449101448,
-0.03818473592400551,
-0.04769585654139519,
-0.07785496115684509,
-0.01966102607548237,
-0.013... |
9b9f1122-55cc-4df3-bfb1-8ceae3e8d2ea | description: 'Aggregate function that calculates the maximum across a group of values.'
sidebar_position: 162
slug: /sql-reference/aggregate-functions/reference/max
title: 'max'
doc_type: 'reference'
Aggregate function that calculates the maximum across a group of values.
Example:
sql
SELECT max(salary) FROM em... | {"source_file": "max.md"} | [
0.020406626164913177,
0.0009003105224110186,
-0.019086048007011414,
-0.059947073459625244,
-0.12713652849197388,
-0.015536082908511162,
-0.04306602105498314,
0.09482674300670624,
-0.06530582904815674,
0.026967622339725494,
0.01183082815259695,
0.009827069006860256,
0.04100201278924942,
-0.... |
4091364b-386a-401f-a128-bc4810b86016 | description: 'Applies bit-wise
XOR
for series of numbers.'
sidebar_position: 153
slug: /sql-reference/aggregate-functions/reference/groupbitxor
title: 'groupBitXor'
doc_type: 'reference'
groupBitXor
Applies bit-wise
XOR
for series of numbers.
sql
groupBitXor(expr)
Arguments
expr
β An expression that re... | {"source_file": "groupbitxor.md"} | [
0.01636764220893383,
0.048841290175914764,
-0.064630426466465,
0.030375557020306587,
-0.0621243380010128,
-0.04555104300379753,
0.07872679084539413,
0.02129516936838627,
-0.015228262171149254,
-0.03507579118013382,
0.023119524121284485,
-0.06175500154495239,
0.06072166562080383,
-0.0654093... |
e1e5109f-e5e9-4f0b-b329-cab5d99ca6cd | description: 'With the determined precision computes the quantile of a numeric data
sequence according to the weight of each sequence member.'
sidebar_position: 181
slug: /sql-reference/aggregate-functions/reference/quantiletimingweighted
title: 'quantileTimingWeighted'
doc_type: 'reference'
quantileTimingWeighte... | {"source_file": "quantiletimingweighted.md"} | [
-0.07569252699613571,
-0.020484542474150658,
0.00596612086519599,
0.02069641463458538,
-0.11344544589519501,
-0.07444468885660172,
0.03058898262679577,
0.06772001832723618,
0.007169595453888178,
-0.01677054539322853,
-0.011036128737032413,
-0.08333270251750946,
0.010331098921597004,
-0.059... |
85145795-ccef-41bc-a14e-d93430c0dbdf | quantilesTimingWeighted
Same as
quantileTimingWeighted
, but accept multiple parameters with quantile levels and return an Array filled with many values of that quantiles.
Example
Input table:
text
ββresponse_timeββ¬βweightββ
β 68 β 1 β
β 104 β 2 β
β 112 β 3 β
β ... | {"source_file": "quantiletimingweighted.md"} | [
-0.004608729854226112,
0.04080076143145561,
-0.013262886554002762,
0.01771734654903412,
-0.0792820081114769,
-0.05885891243815422,
0.056768208742141724,
-0.022324323654174805,
-0.0036376318894326687,
-0.03146873787045479,
-0.03051748313009739,
-0.07688123732805252,
-0.03398917242884636,
0.... |
cbaa1dd7-2072-48f8-a93d-7881f9cde40e | description: 'Computes quantile of a numeric data sequence using linear interpolation,
taking into account the weight of each element.'
sidebar_position: 176
slug: /sql-reference/aggregate-functions/reference/quantileInterpolatedWeighted
title: 'quantileInterpolatedWeighted'
doc_type: 'reference'
quantileInterpol... | {"source_file": "quantileinterpolatedweighted.md"} | [
-0.08718591928482056,
0.00651442538946867,
0.042400479316711426,
0.005877922289073467,
-0.09403061866760254,
-0.06837435066699982,
0.03003528341650963,
0.08329331129789352,
-0.043250251561403275,
-0.0010106442496180534,
-0.02019154466688633,
-0.08225304633378983,
0.061955928802490234,
-0.0... |
ff1ae1e3-b5fb-4525-9ad9-2f494d28e2d8 | description: 'The result is equal to the square root of varPop.'
sidebar_position: 188
slug: /sql-reference/aggregate-functions/reference/stddevpop
title: 'stddevPop'
doc_type: 'reference'
stddevPop
The result is equal to the square root of
varPop
.
Aliases:
STD
,
STDDEV_POP
.
:::note
This function uses a ... | {"source_file": "stddevpop.md"} | [
0.0118697015568614,
0.007838724181056023,
0.013815626502037048,
0.04216237738728523,
-0.06820069253444672,
-0.046927377581596375,
0.03465772420167923,
0.1298537701368332,
0.03461333364248276,
-0.0236872136592865,
0.06700471043586731,
-0.02060377225279808,
0.056634530425071716,
-0.128103226... |
eeaafade-a941-4e7f-9615-6e51c6fbc1a7 | description: 'Calculates the approximate number of different argument values.'
sidebar_position: 205
slug: /sql-reference/aggregate-functions/reference/uniqcombined
title: 'uniqCombined'
doc_type: 'reference'
uniqCombined
Calculates the approximate number of different argument values.
sql
uniqCombined(HLL_preci... | {"source_file": "uniqcombined.md"} | [
0.04619449004530907,
0.02211967296898365,
-0.08594276756048203,
0.018622880801558495,
-0.10457743704319,
-0.012369879521429539,
0.08159440010786057,
0.01671214960515499,
-0.00554317282512784,
-0.0145995132625103,
-0.025472071021795273,
-0.006384633481502533,
0.05998195707798004,
-0.0682409... |
f11ce719-461c-4353-8a63-040379de7eb6 | description: 'Calculates the value of the population covariance'
sidebar_position: 123
slug: /sql-reference/aggregate-functions/reference/covarpopstable
title: 'covarPopStable'
doc_type: 'reference'
covarPopStable
Calculates the value of the population covariance:
$$
\frac{\Sigma{(x - \bar{x})(y - \bar{y})}}{n}... | {"source_file": "covarpopstable.md"} | [
-0.01076620165258646,
-0.08199422061443329,
-0.009812559001147747,
0.03154883161187172,
-0.05192882567644119,
-0.06601189821958542,
0.05660043656826019,
0.02863302081823349,
-0.0007879528566263616,
0.0029820252675563097,
0.06883173435926437,
-0.02937191165983677,
0.011690194718539715,
-0.0... |
98701afa-d478-489a-a63e-d35f6f98528f | description: 'Aggregate function that calculates PromQL-like changes over time series data on the specified grid.'
sidebar_position: 229
slug: /sql-reference/aggregate-functions/reference/timeSeriesChangesToGrid
title: 'timeSeriesChangesToGrid'
doc_type: 'reference'
Aggregate function that takes time series data as... | {"source_file": "timeSeriesChangesToGrid.md"} | [
-0.07435086369514465,
-0.004902002401649952,
-0.0679187923669815,
0.054010216146707535,
-0.030211759731173515,
-0.023779144510626793,
0.029958490282297134,
0.0473550446331501,
0.0635761246085167,
0.03150938078761101,
-0.04286261647939682,
-0.07587293535470963,
-0.01376335695385933,
-0.0238... |
e0cd1042-ebb1-4932-8278-75bbe4754b92 | Also it is possible to pass multiple samples of timestamps and values as Arrays of equal size. The same query with array arguments:
sql
WITH
[110, 120, 130, 190, 200, 210, 220, 230]::Array(DateTime) AS timestamps,
[1, 1, 3, 5, 5, 8, 12, 13]::Array(Float32) AS values,
90 AS start_ts,
90 + 135 AS end_ts... | {"source_file": "timeSeriesChangesToGrid.md"} | [
-0.030458806082606316,
0.007097488734871149,
-0.0040633799508214,
0.033053044229745865,
-0.049320198595523834,
0.0157928504049778,
0.051577214151620865,
0.0034328089095652103,
0.003394232364371419,
0.0006997704040259123,
-0.07335778325796127,
-0.10307113081216812,
-0.026301991194486618,
0.... |
b29caf3d-7b9f-48af-8872-80c938e8591b | description: 'Calculates the
arg
value for a maximum
val
value.'
sidebar_position: 109
slug: /sql-reference/aggregate-functions/reference/argmax
title: 'argMax'
doc_type: 'reference'
argMax
Calculates the
arg
value for a maximum
val
value. If there are multiple rows with equal
val
being the maximum, whi... | {"source_file": "argmax.md"} | [
-0.025974879041314125,
-0.016977008432149887,
-0.0342649482190609,
0.04487421736121178,
-0.07792097330093384,
-0.04594457522034645,
0.09749827533960342,
0.02084197662770748,
-0.06957491487264633,
0.029229916632175446,
0.00868988037109375,
0.001871206215582788,
0.0710449069738388,
-0.087207... |
b077725c-4ab5-4aa5-a48a-3867de481b02 | description: 'Applies bit-wise
OR
to a series of numbers.'
sidebar_position: 152
slug: /sql-reference/aggregate-functions/reference/groupbitor
title: 'groupBitOr'
doc_type: 'reference'
groupBitOr
Applies bit-wise
OR
to a series of numbers.
sql
groupBitOr(expr)
Arguments
expr
β An expression that result... | {"source_file": "groupbitor.md"} | [
0.009615493938326836,
0.06514894217252731,
-0.08342631906270981,
0.0410761758685112,
-0.06899791955947876,
-0.038279034197330475,
0.0717511996626854,
0.0403621606528759,
-0.004541604779660702,
-0.03160467743873596,
0.017981192097067833,
-0.06924159079790115,
0.03749419003725052,
-0.0654359... |
5ec34fea-304a-414e-9aa1-ea52c33cb79c | description: 'Computes an approximate quantile of a numeric data sequence using the
t-digest algorithm.'
sidebar_position: 179
slug: /sql-reference/aggregate-functions/reference/quantiletdigestweighted
title: 'quantileTDigestWeighted'
doc_type: 'reference'
quantileTDigestWeighted
Computes an approximate
quanti... | {"source_file": "quantiletdigestweighted.md"} | [
-0.06186294183135033,
0.021809106692671776,
-0.02715003304183483,
0.02117694541811943,
-0.06182629242539406,
-0.09042855352163315,
0.029557794332504272,
0.07503392547369003,
0.06874222308397293,
-0.017988601699471474,
-0.027523130178451538,
-0.012386256828904152,
0.00804829876869917,
-0.04... |
ab735232-9c9f-40db-9bfd-3b3cf6730297 | description: 'Calculates the list of distinct data types stored in Dynamic column.'
sidebar_position: 215
slug: /sql-reference/aggregate-functions/reference/distinctdynamictypes
title: 'distinctDynamicTypes'
doc_type: 'reference'
distinctDynamicTypes
Calculates the list of distinct data types stored in
Dynamic
... | {"source_file": "distinctdynamictypes.md"} | [
0.018143752589821815,
0.008946170099079609,
0.040637582540512085,
0.07512930780649185,
-0.06756148487329483,
-0.018075257539749146,
0.06510226428508759,
0.04690433666110039,
0.0007808972150087357,
0.004132863599807024,
0.02637382596731186,
-0.0024518403224647045,
0.015081058256328106,
-0.0... |
061333b0-f2bb-4b72-85f6-a01f330e9296 | description: 'Totals one or more
value
arrays according to the keys specified in the
key
array. Returns a tuple of arrays: keys in sorted order, followed by values summed for
the corresponding keys without overflow.'
sidebar_position: 198
slug: /sql-reference/aggregate-functions/reference/summap
title: 'sumMap'... | {"source_file": "summap.md"} | [
0.03719814121723175,
0.03636996075510979,
-0.006188944913446903,
-0.02024925872683525,
-0.037327077239751816,
-0.008316866122186184,
0.09930974990129471,
0.02868168242275715,
-0.057210762053728104,
0.01244570966809988,
-0.0490320548415184,
-0.012723305262625217,
0.06834381818771362,
-0.055... |
cebbc1ab-0ed9-4628-b79e-17871bbe691b | Example with Multiple Value Arrays
sumMap
also supports aggregating multiple value arrays simultaneously.
This is useful when you have related metrics that share the same keys.
```sql title="Query"
CREATE TABLE multi_metrics(
date Date,
browser_metrics Nested(
browser String,
impressions UI... | {"source_file": "summap.md"} | [
0.04589028283953667,
-0.033777184784412384,
0.02515992894768715,
-0.006076439283788204,
-0.07580462843179703,
0.00553175201639533,
0.08402162045240402,
0.01038214098662138,
-0.03251590579748154,
-0.060684800148010254,
0.00877799279987812,
-0.09360779821872711,
0.037971317768096924,
-0.0449... |
e7827485-fa64-4da1-a313-10f120819ac1 | description: 'Computes the sample kurtosis of a sequence.'
sidebar_position: 158
slug: /sql-reference/aggregate-functions/reference/kurtsamp
title: 'kurtSamp'
doc_type: 'reference'
kurtSamp
Computes the
sample kurtosis
of a sequence.
It represents an unbiased estimate of the kurtosis of a random variable if p... | {"source_file": "kurtsamp.md"} | [
-0.06263129413127899,
-0.05105283111333847,
-0.002491510007530451,
-0.007371077314019203,
-0.0048162383027374744,
-0.08078417181968689,
0.06984137743711472,
0.053451742976903915,
0.03257302939891815,
0.07906223833560944,
0.07928722351789474,
-0.041856370866298676,
-0.007839646190404892,
-0... |
caedfbb8-0a1d-4aab-8b8a-71a53466d036 | description: 'This function implements stochastic logistic regression. It can be used
for binary classification problem, supports the same custom parameters as stochasticLinearRegression
and works the same way.'
sidebar_position: 193
slug: /sql-reference/aggregate-functions/reference/stochasticlogisticregression
ti... | {"source_file": "stochasticlogisticregression.md"} | [
-0.04807903245091438,
-0.05999905616044998,
-0.07462777197360992,
0.04075859487056732,
-0.035920970141887665,
0.002290223026648164,
0.030580462887883186,
0.03227803856134415,
-0.08260888606309891,
-0.07290278375148773,
0.004416422452777624,
-0.01197010837495327,
-0.004685898311436176,
-0.1... |
f5062210-e687-4027-9002-52d4090e1b22 | description: 'Calculates the exponential moving average of values for the determined
time.'
sidebar_position: 132
slug: /sql-reference/aggregate-functions/reference/exponentialMovingAverage
title: 'exponentialMovingAverage'
doc_type: 'reference'
exponentialMovingAverage {#exponentialmovingaverage}
Calculates th... | {"source_file": "exponentialmovingaverage.md"} | [
-0.10004518926143646,
0.010479414835572243,
-0.064855195581913,
0.041349366307258606,
-0.012248622253537178,
-0.11826612055301666,
0.03704467788338661,
0.09853663295507431,
-0.001972064608708024,
-0.005717617925256491,
0.05608930066227913,
-0.07583284378051758,
0.0434933565557003,
-0.00212... |
8c8d3c5b-cd56-4d8c-99ba-b3e62fb6a698 | text
ββvalueββ¬βtimeββ¬βround(exp_smooth, 3)ββ¬βbarβββββββββββββββββββββββββββββββββββββββββ
β 1 β 0 β 0.067 β ββββ β
β 0 β 1 β 0.062 β βββ β
β 0 β 2 β 0.058 β βββ ... | {"source_file": "exponentialmovingaverage.md"} | [
-0.027695782482624054,
-0.002298541134223342,
-0.03854485973715782,
0.019989751279354095,
-0.03384868800640106,
-0.10878176242113113,
0.10489727556705475,
-0.03768517076969147,
-0.03664698079228401,
0.04698941856622696,
0.09636275470256805,
-0.033348631113767624,
0.018311018124222755,
-0.0... |
c1a59c83-e2c5-49d4-b4bb-3e7deb8cef0d | β 1 β 32 β 0.433 β ββββββββββββββββββββββ β
β 1 β 33 β 0.471 β ββββββββββββββββββββββββ β
β 1 β 34 β 0.506 β ββββββββββββββββββββββββββ β
β 1 β 35 β 0.539 β βββββββββββββββββββββββββ... | {"source_file": "exponentialmovingaverage.md"} | [
0.008792988024652004,
0.014759434387087822,
-0.05452706664800644,
-0.01829824410378933,
-0.04318508133292198,
-0.07447654008865356,
0.06624894589185715,
-0.051525626331567764,
-0.05011564865708351,
0.1044921800494194,
0.014298651367425919,
-0.04397069290280342,
0.07646362483501434,
-0.0125... |
65431da0-7318-42d4-9728-3ffd5000599a | ```sql
CREATE TABLE data
ENGINE = Memory AS
SELECT
10 AS value,
toDateTime('2020-01-01') + (3600 * number) AS time
FROM numbers_mt(10);
-- Calculate timeunit using intDiv
SELECT
value,
time,
exponentialMovingAverage(1)(value, intDiv(toUInt32(time), 3600)) OVER (ORDER BY time ASC) AS res,
intDiv(... | {"source_file": "exponentialmovingaverage.md"} | [
-0.020547248423099518,
-0.008887499570846558,
-0.029432864859700203,
0.03628590330481529,
-0.05414724722504616,
-0.04317663982510567,
-0.013765309937298298,
0.023477137088775635,
0.004913045559078455,
0.019114913418889046,
0.051063962280750275,
-0.059008028358221054,
-0.011610418558120728,
... |
b5c211d8-3c96-413b-a356-60a58911d9e4 | description: 'Aggregate function for re-sampling time series data for PromQL-like irate and idelta calculation'
sidebar_position: 224
slug: /sql-reference/aggregate-functions/reference/timeSeriesLastTwoSamples
title: 'timeSeriesLastTwoSamples'
doc_type: 'reference'
Aggregate function that takes time series data as ... | {"source_file": "timeSeriesLastTwoSamples.md"} | [
-0.10218439251184464,
-0.012889198958873749,
-0.0518815852701664,
0.016640443354845047,
-0.050884976983070374,
-0.030659131705760956,
0.013167859055101871,
0.02700202725827694,
0.01853296160697937,
0.023368800058960915,
-0.04345684498548508,
-0.03467300906777382,
-0.022217508405447006,
-0.... |
4d678779-92d2-4308-921b-1c6c8fce1eb2 | -- Check raw data
SELECT *
FROM t_raw_timeseries
WHERE metric_id = 3 AND timestamp BETWEEN '2024-12-12 12:00:12' AND '2024-12-12 12:00:31'
ORDER BY metric_id, timestamp;
```
response
3 2024-12-12 12:00:12.870 29
3 2024-12-12 12:00:13.770 8
3 2024-12-12 12:00:14.670 19
3 2024-12-12 12:00:15.570 ... | {"source_file": "timeSeriesLastTwoSamples.md"} | [
0.011954485438764095,
0.0009220971260219812,
0.061837248504161835,
-0.015908969566226006,
-0.030644694343209267,
-0.042105548083782196,
-0.011005272157490253,
-0.023114336654543877,
0.04646824300289154,
0.01684531755745411,
0.012878633104264736,
-0.049035780131816864,
-0.058162640780210495,
... |
6e86b69a-d1ca-4da0-ac58-1edc86795060 | response
3 [11,8,-18,8,11] [12.222222222222221,8.88888888888889,1.1111111111111112,8.88888888888889,12.222222222222221]
sql
-- Calculate idelta and irate from the re-sampled data
WITH
'2024-12-12 12:00:15'::DateTime64(3,'UTC') AS start_ts, -- start of timestamp grid
start_ts + INTERVAL 60 SECOND A... | {"source_file": "timeSeriesLastTwoSamples.md"} | [
-0.05985187739133835,
0.03578932583332062,
0.009771807119250298,
0.01924918219447136,
-0.02827012911438942,
-0.011425737291574478,
0.030151741579174995,
0.0478023886680603,
0.05171212553977966,
0.012882162816822529,
-0.04140844568610191,
-0.07815771549940109,
-0.03977758809924126,
-0.04744... |
c6bbb6a5-7e51-4c20-945f-3f2c946b39f9 | description: 'Calculates the approximate number of different argument values. It is
the same as uniqCombined, but uses a 64-bit hash for all data types rather than
just for the String data type.'
sidebar_position: 206
slug: /sql-reference/aggregate-functions/reference/uniqcombined64
title: 'uniqCombined64'
doc_type... | {"source_file": "uniqcombined64.md"} | [
0.025689946487545967,
0.015098579227924347,
-0.056763071566820145,
0.028388725593686104,
-0.08340208977460861,
-0.014427751302719116,
0.07034268230199814,
0.020888574421405792,
0.003467763541266322,
-0.012477120384573936,
0.015508666634559631,
0.00610368512570858,
0.07348863035440445,
-0.1... |
e4dbe0d4-3e96-4925-9ee8-9f62c3ba04ed | description: 'Applies mean z-test to samples from two populations.'
sidebar_label: 'meanZTest'
sidebar_position: 166
slug: /sql-reference/aggregate-functions/reference/meanztest
title: 'meanZTest'
doc_type: 'reference'
meanZTest
Applies mean z-test to samples from two populations.
Syntax
sql
meanZTest(populat... | {"source_file": "meanztest.md"} | [
-0.00801396556198597,
0.03475669398903847,
-0.023245561867952347,
0.07033739238977432,
-0.02828972041606903,
-0.07364910840988159,
0.0029732456896454096,
0.08706093579530716,
-0.11861670762300491,
-0.009950446896255016,
0.030899345874786377,
-0.11653643101453781,
0.09873072057962418,
-0.09... |
4475bec2-b9c2-4b6f-afb7-f54c9e963cdd | description: 'Applies the one-sample Student t-test to a sample and a known population mean.'
sidebar_label: 'studentTTestOneSample'
sidebar_position: 195
slug: /sql-reference/aggregate-functions/reference/studentttestonesample
title: 'studentTTestOneSample'
doc_type: 'reference'
studentTTestOneSample
Applies the... | {"source_file": "studentttestonesample.md"} | [
0.0027456304524093866,
0.025156928226351738,
0.0002511051425244659,
-0.001836569863371551,
-0.0433068610727787,
-0.07339217513799667,
-0.003019633935764432,
0.10014744848012924,
-0.06686432659626007,
0.05519011989235878,
0.0727202296257019,
-0.15101635456085205,
0.08462489396333694,
-0.113... |
08110071-5624-4e0d-8ac8-cd93ed2aafb2 | description: 'Calculates the approximate number of different argument values, using
the HyperLogLog algorithm.'
sidebar_position: 208
slug: /sql-reference/aggregate-functions/reference/uniqhll12
title: 'uniqHLL12'
doc_type: 'reference'
uniqHLL12
Calculates the approximate number of different argument values, us... | {"source_file": "uniqhll12.md"} | [
0.014404946938157082,
0.024934202432632446,
-0.06718271225690842,
0.004210681188851595,
-0.052435457706451416,
-0.07580527663230896,
0.04187455028295517,
0.01857604645192623,
-0.00460209371522069,
-0.021332159638404846,
-0.04645150154829025,
0.019067542627453804,
0.08832468092441559,
-0.08... |
8a37326b-86f6-4a36-bf1f-f1239d2fc10f | description: 'Aggregates arrays into a larger array of those arrays.'
keywords: ['groupArrayArray', 'array_concat_agg']
sidebar_position: 111
slug: /sql-reference/aggregate-functions/reference/grouparrayarray
title: 'groupArrayArray'
doc_type: 'reference'
groupArrayArray
Aggregates arrays into a larger array of t... | {"source_file": "grouparrayarray.md"} | [
0.04244811460375786,
0.026877116411924362,
-0.047413621097803116,
0.029529273509979248,
-0.09833292663097382,
-0.04087619110941887,
0.10576387494802475,
0.004988350439816713,
-0.046876534819602966,
-0.033861029893159866,
-0.0010895855957642198,
0.020367557182908058,
0.04388098418712616,
-0... |
b607cdb7-7fe7-4b3b-b28a-8245bc33b7b4 | description: 'Creates an array from different argument values.'
sidebar_position: 154
slug: /sql-reference/aggregate-functions/reference/groupuniqarray
title: 'groupUniqArray'
doc_type: 'reference'
groupUniqArray
Syntax:
groupUniqArray(x)
or
groupUniqArray(max_size)(x)
Creates an array from different argumen... | {"source_file": "groupuniqarray.md"} | [
0.04520116373896599,
-0.008835851214826107,
-0.07876891642808914,
0.0667763352394104,
-0.03758309409022331,
-0.0026958726812154055,
0.026678018271923065,
0.0068663847632706165,
0.030417470261454582,
-0.019461356103420258,
0.03309252858161926,
0.07581175863742828,
0.06535076349973679,
-0.10... |
8083f3cf-7bdb-45b8-9dad-ad226e2d441d | description: 'Applies bit-wise
AND
for series of numbers.'
sidebar_position: 147
slug: /sql-reference/aggregate-functions/reference/groupbitand
title: 'groupBitAnd'
doc_type: 'reference'
groupBitAnd
Applies bit-wise
AND
for series of numbers.
sql
groupBitAnd(expr)
Arguments
expr
β An expression that re... | {"source_file": "groupbitand.md"} | [
0.03370784968137741,
0.05512525513768196,
-0.07679498195648193,
0.042900968343019485,
-0.0831657126545906,
-0.022115956991910934,
0.05583437159657478,
0.04709332808852196,
-0.021984416991472244,
-0.01775587722659111,
0.004399976693093777,
-0.0680803507566452,
0.03915483504533768,
-0.081599... |
c38e7324-3642-4fb2-b956-91c4a667aaa0 | description: 'Sums the arithmetic difference between consecutive rows.'
sidebar_position: 129
slug: /sql-reference/aggregate-functions/reference/deltasum
title: 'deltaSum'
doc_type: 'reference'
deltaSum
Sums the arithmetic difference between consecutive rows. If the difference is negative, it is ignored.
:::not... | {"source_file": "deltasum.md"} | [
-0.052733127027750015,
0.015025570057332516,
0.021743860095739365,
-0.037390146404504776,
-0.11026731878519058,
0.00583918672055006,
0.057514794170856476,
0.007789826951920986,
0.012845173478126526,
0.000022607380742556415,
0.023684555664658546,
-0.057266250252723694,
0.011231588199734688,
... |
bd74b0ae-377c-46cb-9d12-1b88d7ceb3a7 | description: 'Returns an array with the first N items in ascending order.'
sidebar_position: 146
slug: /sql-reference/aggregate-functions/reference/grouparraysorted
title: 'groupArraySorted'
doc_type: 'reference'
groupArraySorted
Returns an array with the first N items in ascending order.
sql
groupArraySorted(N... | {"source_file": "grouparraysorted.md"} | [
0.01549512054771185,
0.009044033475220203,
-0.009039729833602905,
0.003224351443350315,
-0.04612303152680397,
0.005752816330641508,
0.048605646938085556,
-0.002892332384362817,
-0.008943911641836166,
-0.015813080593943596,
-0.012376219034194946,
0.11393067240715027,
0.013053420931100845,
-... |
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