docs-v2/content/influxdb/clustered/reference/sql/functions/aggregate.md

title	list_title	description	menu	weight	related
SQL aggregate functions	Aggregate functions	Aggregate data with SQL aggregate functions.	influxdb_clustered name parent Aggregate sql-functions	301	/influxdb/clustered/query-data/sql/aggregate-select/

SQL aggregate functions aggregate values in a specified column for each group or SQL partition and return a single row per group containing the aggregate value.

• General aggregate functions
  • array_agg
  • avg
  • bit_and
  • bit_or
  • bit_xor
  • bool_and
  • bool_or
  • count
  • first_value
  • last_value
  • max
  • mean
  • median
  • min
  • sum
• Statistical aggregate functions
  • corr
  • covar
  • covar_pop
  • covar_samp
  • regr_avgx
  • regr_avgy
  • regr_count
  • regr_intercept
  • regr_r2
  • regr_slope
  • regr_sxx
  • regr_syy
  • regr_sxy
  • stddev
  • stddev_pop
  • stddev_samp
  • var
  • var_pop
  • var_samp
• Approximate aggregate functions
  • approx_distinct
  • approx_median
  • approx_percentile_cont
  • approx_percentile_cont_with_weight

---

General aggregate functions

• array_agg
• avg
• bit_and
• bit_or
• bit_xor
• bool_and
• bool_or
• count
• first_value
• last_value
• max
• mean
• median
• min
• sum

array_agg

Returns an array created from the expression elements.

{{% note %}} array_agg returns a LIST arrow type which is not supported by InfluxDB. To use with InfluxDB, use bracket notation to reference the index of an element in the returned array. Arrays are 1-indexed. {{% /note %}}

array_agg(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View array_agg query example" %}}

The following example uses the sample data set provided in the Get started with InfluxDB tutorial.

SELECT
  room,
  array_agg(temp)[3] AS '3rd_temp'
FROM home
GROUP BY room

room	3rd_temp
Kitchen	22.7
Living Room	21.8

{{% /expand %}} {{< /expand-wrapper >}}

avg

Returns the average of numeric values in the specified column.

avg(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

Aliases

• mean

{{< expand-wrapper >}} {{% expand "View avg query example" %}}

SELECT 
  location,
  avg(water_level) AS water_level_avg
FROM h2o_feet
GROUP BY location

location	water_level_avg
coyote_creek	5.359142420303919
santa_monica	3.5307120942458843

{{% /expand %}} {{< /expand-wrapper >}}

bit_and

Computes the bitwise AND of all non-null input values.

bit_and(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View bit_and query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  bit_and(precip::BIGINT) AS precip_bit_and
FROM weather
GROUP BY location

location	precip_bit_and
Concord	0
Hayward	0
San Francisco	0

{{% /expand %}} {{< /expand-wrapper >}}

bit_or

Computes the bitwise OR of all non-null input values.

bit_or(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View bit_or query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  bit_or(precip::BIGINT) AS precip_bit_or
FROM weather
GROUP BY location

location	precip_bit_or
Concord	7
Hayward	7
San Francisco	7

{{% /expand %}} {{< /expand-wrapper >}}

bit_xor

Computes the bitwise exclusive OR of all non-null input values.

bit_xor(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View bit_xor query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  bit_xor(precip::BIGINT) AS precip_bit_xor
FROM weather
GROUP BY location

location	precip_bit_xor
Concord	4
Hayward	6
San Francisco	4

{{% /expand %}} {{< /expand-wrapper >}}

bool_and

Returns true if all non-null input values are true, otherwise returns false.

bool_and(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View bool_and query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  bool_and(precip > 0) AS precip_bool_and
FROM weather
GROUP BY location

location	precip_bool_and
Concord	false
Hayward	false
San Francisco	false

{{% /expand %}} {{< /expand-wrapper >}}

bool_or

Returns true if any non-null input value is true, otherwise returns false.

bool_or(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View bool_or query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  bool_or(precip > 0) AS precip_bool_or
FROM weather
GROUP BY location

location	precip_bool_or
Concord	true
Hayward	true
San Francisco	true

{{% /expand %}} {{< /expand-wrapper >}}

count

Returns the number of rows in the specified column.

Count includes null values in the total count. To exclude null values from the total count, include <column> IS NOT NULL in the WHERE clause.

count(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View count query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  count(precip) AS precip_count
FROM weather
GROUP BY location

location	precip_count
Concord	1094
Hayward	1096
San Francisco	1096

{{% /expand %}} {{< /expand-wrapper >}}

first_value

Returns the first element in an aggregation group according to the specified ordering. If no ordering is specified, returns an arbitrary element from the group.

first_value(expression [ORDER BY expression])

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View first_value query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  first_value(temp_max ORDER BY time) AS temp_max_first_value
FROM weather
GROUP BY location

location	temp_max_first_value
Concord	59
Hayward	57
San Francisco	66

{{% /expand %}} {{< /expand-wrapper >}}

last_value

Returns the last element in an aggregation group according to the specified ordering. If no ordering is specified, returns an arbitrary element from the group.

last_value(expression [ORDER BY expression])

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View last_value query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  last_value(temp_max ORDER BY time) AS temp_max_last_value
FROM weather
GROUP BY location

location	temp_max_last_value
Concord	59
Hayward	58
San Francisco	62

{{% /expand %}} {{< /expand-wrapper >}}

max

Returns the maximum value in the specified column.

max(expression)

To return both the maximum value and its associated timestamp, use selector_max.

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View max query example" %}}

SELECT 
  location,
  max(water_level) AS water_level_max
FROM h2o_feet
GROUP BY location

location	water_level_max
santa_monica	7.205
coyote_creek	9.964

{{% /expand %}} {{< /expand-wrapper >}}

mean

Alias of avg.

median

Returns the median value in the specified column.

median(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View median query example" %}}

SELECT 
  location,
  median(water_level) AS water_level_max
FROM h2o_feet
GROUP BY location

location	water_level_median
coyote_creek	5.4645
santa_monica	3.471

{{% /expand %}} {{< /expand-wrapper >}}

min

Returns the minimum value in the specified column.

min(expression)

To return both the minimum value and its associated timestamp, use selector_max.

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View min query example" %}}

SELECT 
  location,
  min(water_level) AS water_level_min
FROM h2o_feet
GROUP BY location

location	water_level_min
coyote_creek	-0.61
santa_monica	-0.243

{{% /expand %}} {{< /expand-wrapper >}}

sum

Returns the sum of all values in the specified column.

sum(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View sum query example" %}}

SELECT 
  location,
  sum(water_level) AS water_level_sum
FROM h2o_feet
GROUP BY location

location	water_level_sum
santa_monica	27024.070369358
coyote_creek	40750.918963991004

{{% /expand %}} {{< /expand-wrapper >}}

Statistical aggregate functions

• corr
• covar
• covar_pop
• covar_samp
• regr_avgx
• regr_avgy
• regr_count
• regr_intercept
• regr_r2
• regr_slope
• regr_sxx
• regr_syy
• regr_sxy
• stddev
• stddev_pop
• stddev_samp
• var
• var_pop
• var_samp

corr

Returns the coefficient of correlation between two numeric values.

corr(expression1, expression2)

Arguments

• expression1: First column or literal value to operate on.
• expression2: Second column or literal value to operate on.

{{< expand-wrapper >}} {{% expand "View corr query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  corr(hum, temp) AS correlation
FROM home
GROUP BY room

room	correlation
Living Room	0.43665270457835725
Kitchen	0.6741766954929539

{{% /expand %}} {{< /expand-wrapper >}}

covar

Returns the covariance of a set of number pairs.

covar(expression1, expression2)

Arguments

• expression1: First column or literal value to operate on.
• expression2: Second column or literal value to operate on.

{{< expand-wrapper >}} {{% expand "View covar query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  covar(hum, temp) AS covar
FROM home
GROUP BY room

room	covar
Living Room	0.03346153846153959
Kitchen	0.11134615384615432

{{% /expand %}} {{< /expand-wrapper >}}

covar_pop

Returns the population covariance of a set of number pairs.

covar_pop(expression1, expression2)

Arguments

• expression1: First column or literal value to operate on.
• expression2: Second column or literal value to operate on.

{{< expand-wrapper >}} {{% expand "View covar_pop query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  covar_pop(hum, temp) AS covar_pop
FROM home
GROUP BY room

room	covar_pop
Kitchen	0.10278106508875783
Living Room	0.030887573964498087

{{% /expand %}} {{< /expand-wrapper >}}

covar_samp

Returns the sample covariance of a set of number pairs.

covar_samp(expression1, expression2)

Arguments

• expression1: First column or literal value to operate on.
• expression2: Second column or literal value to operate on.

{{< expand-wrapper >}} {{% expand "View covar_samp query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  covar_samp(hum, temp) AS covar_samp
FROM home
GROUP BY room

room	covar_samp
Kitchen	0.11134615384615432
Living Room	0.03346153846153959

{{% /expand %}} {{< /expand-wrapper >}}

regr_avgx

Computes the average of the independent variable (input), expression_x, for the non-null dependent variable, expression_y.

regr_avgx(expression_y, expression_x)

Arguments

• expression_y: Dependent variable. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: Independent variable. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_avgx query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_avgx(temp_min, temp_max) AS temp_regr_avgx
FROM weather
GROUP BY location

location	temp_regr_avgx
Concord	75.54379562043796
Hayward	69.14808043875686
San Francisco	67.59945255474454

{{% /expand %}} {{< /expand-wrapper >}}

regr_avgy

Computes the average of the dependent variable (output), expression_y, for the non-null dependent variable, expression_y.

regr_avgy(expression_y, expression_x)

Arguments

• expression_y: Dependent variable. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: Independent variable. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_avgy query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_avgy(temp_min, temp_max) AS temp_regr_avgy
FROM weather
GROUP BY location

location	temp_regr_avgy
Concord	50.153284671532845
Hayward	50.913162705667276
San Francisco	51.52372262773722

{{% /expand %}} {{< /expand-wrapper >}}

regr_count

Counts the number of non-null paired data points.

regr_count(expression_y, expression_x)

Arguments

• expression_y: Dependent variable. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: Independent variable. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_count query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_count(temp_min, temp_max) AS temp_regr_count
FROM weather
GROUP BY location

location	temp_regr_count
Concord	1096
Hayward	1094
San Francisco	1096

{{% /expand %}} {{< /expand-wrapper >}}

regr_intercept

Computes the y-intercept of the linear regression line. For the equation (y = kx + b), this function returns b.

regr_intercept(expression_y, expression_x)

Arguments

• expression_y: Dependent variable. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: Independent variable. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_intercept query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_intercept(temp_min, temp_max) AS temp_regr_intercept
FROM weather
GROUP BY location

location	temp_regr_intercept
Concord	11.636281392206769
Hayward	12.876956842745152
San Francisco	19.125237647086607

{{% /expand %}} {{< /expand-wrapper >}}

regr_r2

Computes the square of the correlation coefficient between the independent and dependent variables.

regr_r2(expression_y, expression_x)

Arguments

• expression_y: Dependent variable. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: Independent variable. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_r2 query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_r2(temp_min, temp_max) AS temp_regr_r2
FROM weather
GROUP BY location

location	temp_regr_r2
Concord	0.6474628308450441
Hayward	0.5166296626320914
San Francisco	0.5032317511200297

{{% /expand %}} {{< /expand-wrapper >}}

regr_slope

Returns the slope of the linear regression line for non-null pairs in aggregate columns. Given input column Y and X: regr_slope(Y, X) returns the slope (k in Y = k*X + b) using minimal RSS fitting.

regr_slope(expression_y, expression_x)

Arguments

• expression_y: Y expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: X expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_slope query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_slope(temp_min, temp_max) AS temp_regr_slope
FROM weather
GROUP BY location

location	temp_regr_slope
Concord	0.5098632252058237
Hayward	0.5500688612261629
San Francisco	0.4792714105844738

{{% /expand %}} {{< /expand-wrapper >}}

regr_sxx

Computes the sum of squares of the independent variable.

regr_sxx(expression_y, expression_x)

Arguments

• expression_y: Dependent variable. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: Independent variable. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_sxx query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_sxx(temp_min, temp_max) AS temp_regr_sxx
FROM weather
GROUP BY location

location	temp_regr_sxx
Concord	210751.89781021897
Hayward	99644.01096892142
San Francisco	77413.15967153282

{{% /expand %}} {{< /expand-wrapper >}}

regr_syy

Computes the sum of squares of the dependent variable.

regr_syy(expression_y, expression_x)

Arguments

• expression_y: Dependent variable. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: Independent variable. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_syy query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_syy(temp_min, temp_max) AS temp_regr_syy
FROM weather
GROUP BY location

location	temp_regr_syy
Concord	84618.24817518248
Hayward	58358.750457038404
San Francisco	35335.38321167884

{{% /expand %}} {{< /expand-wrapper >}}

regr_sxy

Computes the sum of products of paired data points.

regr_sxy(expression_y, expression_x)

Arguments

• expression_y: Dependent variable. Can be a constant, column, or function, and any combination of arithmetic operators.
• expression_x: Independent variable. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View regr_sxy query example" %}}

The following example uses the NOAA Bay Area weather data.

SELECT 
  location,
  regr_sxy(temp_min, temp_max) AS temp_regr_sxy
FROM weather
GROUP BY location

location	temp_regr_sxy
Concord	107454.64233576645
Hayward	54811.06764168191
San Francisco	37101.914233576645

{{% /expand %}} {{< /expand-wrapper >}}

stddev

Returns the standard deviation of a set of numbers.

stddev(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View stddev query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  stddev(co) AS stddev
FROM home
GROUP BY room

room	stddev
Living Room	5.885662718931967
Kitchen	9.321879418735037

{{% /expand %}} {{< /expand-wrapper >}}

stddev_pop

Returns the population standard deviation of a set of numbers.

stddev_pop(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View stddev_pop query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  stddev_pop(co) AS stddev_pop
FROM home
GROUP BY room

room	stddev_pop
Kitchen	8.956172047894082
Living Room	5.654761830612032

{{% /expand %}} {{< /expand-wrapper >}}

stddev_samp

Returns the sample standard deviation of a set of numbers.

stddev_samp(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View stddev_samp query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  stddev_samp(co) AS stddev_samp
FROM home
GROUP BY room

room	stddev_samp
Living Room	5.885662718931967
Kitchen	9.321879418735037

{{% /expand %}} {{< /expand-wrapper >}}

var

Returns the statistical variance of a set of numbers.

var(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View var query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  var(co) AS var
FROM home
GROUP BY room

room	var
Living Room	34.64102564102564
Kitchen	86.89743589743587

{{% /expand %}} {{< /expand-wrapper >}}

var_pop

Returns the statistical population variance of a set of numbers.

var_pop(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View var_pop query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  var_pop(co) AS var_pop
FROM home
GROUP BY room

room	var_pop
Living Room	31.976331360946745
Kitchen	80.21301775147927

{{% /expand %}} {{< /expand-wrapper >}}

var_samp

Returns the statistical sample variance of a set of numbers.

var_samp(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View var_samp query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  var_samp(co) AS var_samp
FROM home
GROUP BY room

room	var_samp
Kitchen	86.89743589743587
Living Room	34.64102564102564

{{% /expand %}} {{< /expand-wrapper >}}

Approximate aggregate functions

• approx_distinct
• approx_median
• approx_percentile_cont
• approx_percentile_cont_with_weight

approx_distinct

Returns the approximate number of distinct input values calculated using the HyperLogLog algorithm.

approx_distinct(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View approx_distinct query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  approx_distinct(co::string) AS approx_distinct
FROM home
GROUP BY room

room	approx_distinct
Living Room	7
Kitchen	8

{{% /expand %}} {{< /expand-wrapper >}}

approx_median

Returns the approximate median (50th percentile) of input values. It is an alias of approx_percentile_cont(x, 0.5).

approx_median(expression)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

{{< expand-wrapper >}} {{% expand "View approx_median query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  approx_median(temp) AS approx_median
FROM home
GROUP BY room

room	approx_median
Kitchen	22.7
Living Room	22.3

{{% /expand %}} {{< /expand-wrapper >}}

approx_percentile_cont

Returns the approximate percentile of input values using the t-digest algorithm.

approx_percentile_cont(expression, percentile, centroids)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.

• percentile: Percentile to compute. Must be a float value between 0 and 1 (inclusive).

• centroids: Number of centroids to use in the t-digest algorithm. Default is 100.

  If there are this number or fewer unique values, you can expect an exact result. A higher number of centroids results in a more accurate approximation, but requires more memory to compute.

{{< expand-wrapper >}} {{% expand "View approx_percentile_cont query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  approx_percentile_cont(temp, 0.99) AS "99th_percentile"
FROM home
GROUP BY room

room	99th_percentile
Kitchen	23.3
Living Room	22.8

{{% /expand %}} {{< /expand-wrapper >}}

approx_percentile_cont_with_weight

Returns the weighted approximate percentile of input values using the t-digest algorithm.

approx_percentile_cont_with_weight(expression, weight, percentile)

Arguments

• expression: Expression to operate on. Can be a constant, column, or function, and any combination of arithmetic operators.
• weight: Expression to use as weight. Can be a constant, column, or function, and any combination of arithmetic operators.
• percentile: Percentile to compute. Must be a float value between 0 and 1 (inclusive).

{{< expand-wrapper >}} {{% expand "View approx_percentile_cont_with_weight query example" %}}

The following example uses the sample data set provided in Get started with InfluxDB tutorial.

SELECT
  room,
  approx_percentile_cont_with_weight(temp, co, 0.99) AS "co_weighted_99th_percentile"
FROM home
GROUP BY room

room	co_weighted_99th_percentile
Kitchen	23.3
Living Room	22.8

{{% /expand %}} {{< /expand-wrapper >}}