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Use aggregate functions to assess, aggregate, and return values in your data. Aggregate functions return one row containing the aggregate values from each InfluxQL group.

Each aggregate function below covers syntax including parameters to pass to the function, and examples of how to use the function. Examples use NOAA water sample data.

COUNT()

Returns the number of non-null field values. Supports all field value data types.

Syntax

SELECT COUNT( [ * | <field_key> | /<regular_expression>/ ] ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

COUNT(*)

Returns the number of field values associated with each field key in the measurement.

COUNT(field_key)

Returns the number of field values associated with the field key.

COUNT(/regular_expression/)

Returns the number of field values associated with each field key that matches the regular expression.

Examples

{{< expand-wrapper >}} {{% expand "Count values for a field" %}}

Return the number of non-null field values in the water_level field key in the h2o_feet measurement.

SELECT COUNT("water_level") FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time count
1970-01-01T00:00:00Z 61026.0000000000

{{% /expand %}}

{{% expand "Count values for each field in a measurement" %}}

Return the number of non-null field values for each field key associated with the h2o_feet measurement. The h2o_feet measurement has two field keys: level description and water_level.

SELECT COUNT(*) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time count_level description count_water_level
1970-01-01T00:00:00Z 61026.0000000000 61026.0000000000

{{% /expand %}}

{{% expand "Count the values that match a regular expression" %}}

Return the number of non-null field values for every field key that contains the word water in the h2o_feet measurement.

SELECT COUNT(/water/) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time count_water_level
1970-01-01T00:00:00Z 61026.0000000000

{{% /expand %}}

{{% expand "Count distinct values for a field" %}}

Return the number of unique field values for the level description field key and the h2o_feet measurement. InfluxQL supports nesting DISTINCT() in COUNT().

SELECT COUNT(DISTINCT("level description")) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time count
1970-01-01T00:00:00Z 4.0000000000

{{% /expand %}}

{{< /expand-wrapper >}}

DISTINCT()

Returns the list of unique field values. Supports all field value data types.

InfluxQL supports nesting DISTINCT() with COUNT().

Syntax

SELECT DISTINCT( [ <field_key> | /<regular_expression>/ ] ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

DISTINCT(field_key)

Returns the unique field values associated with the field key.

Examples

{{< expand-wrapper >}} {{% expand "List the distinct field values associated with a field key" %}}

Return a tabular list of the unique field values in the level description field key in the h2o_feet measurement.

SELECT DISTINCT("level description") FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time distinct
1970-01-01T00:00:00Z between 6 and 9 feet
1970-01-01T00:00:00Z below 3 feet
1970-01-01T00:00:00Z between 3 and 6 feet
1970-01-01T00:00:00Z at or greater than 9 feet

{{% /expand %}}

{{% expand "List the distinct field values associated with each field key in a measurement" %}}

Return a tabular list of the unique field values for each field key in the h2o_feet measurement. The h2o_feet measurement has two field keys: level description and water_level.

SELECT DISTINCT(*) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time distinct_level description distinct_water_level
1970-01-01T00:00:00Z between 6 and 9 feet 8.12
1970-01-01T00:00:00Z between 3 and 6 feet 8.005
1970-01-01T00:00:00Z at or greater than 9 feet 7.887
1970-01-01T00:00:00Z below 3 feet 7.762

{{% /expand %}} -->

{{< /expand-wrapper >}}

INTEGRAL()

Returns the area under the curve for subsequent field values.

{{% note %}} INTEGRAL() does not support fill(). INTEGRAL() supports int64 and float64 field value data types. {{% /note %}}

Syntax

SELECT INTEGRAL( [ * | <field_key> | /<regular_expression>/ ] [ , <unit> ]  ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

InfluxDB calculates the area under the curve for subsequent field values and converts those results into the summed area per unit. The unit argument is an integer followed by an optional duration literal. If the query does not specify the unit, the unit defaults to one second (1s).

INTEGRAL(field_key)

Returns the area under the curve for subsequent field values associated with the field key.

INTEGRAL(/regular_expression/)

Returns the area under the curve for subsequent field values associated with each field key that matches the regular expression.

INTEGRAL(*)

Returns the average field value associated with each field key in the measurement.

Examples

The following examples use a subset of the NOAA water sample data data:

SELECT "water_level" FROM "h2o_feet" WHERE "location" = 'santa_monica' AND time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z'

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time water_level
2019-08-18T00:00:00Z 2.3520000000
2019-08-18T00:06:00Z 2.3790000000
2019-08-18T00:12:00Z 2.3430000000
2019-08-18T00:18:00Z 2.3290000000
2019-08-18T00:24:00Z 2.2640000000
2019-08-18T00:30:00Z 2.2670000000

{{< expand-wrapper >}} {{% expand "Calculate the integral for the field values associated with a field key" %}}

Return the area under the curve (in seconds) for the field values associated with the water_level field key and in the h2o_feet measurement.

SELECT INTEGRAL("water_level") FROM "h2o_feet" WHERE "location" = 'santa_monica' AND time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z'

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time integral
1970-01-01T00:00:00Z 4184.8200000000

{{% /expand %}}

{{% expand "Calculate the integral for the field values associated with a field key and specify the unit option" %}}

Return the area under the curve (in minutes) for the field values associated with the water_level field key and in the h2o_feet measurement.

SELECT INTEGRAL("water_level",1m) FROM "h2o_feet" WHERE "location" = 'santa_monica' AND time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z'

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time integral
1970-01-01T00:00:00Z 69.7470000000

{{% /expand %}}

{{% expand "Calculate the integral for the field values associated with each field key in a measurement and specify the unit option" %}}

Return the area under the curve (in minutes) for the field values associated with each field key that stores numeric values in the h2o_feet measurement. The h2o_feet measurement has on numeric field: water_level.

SELECT INTEGRAL(*,1m) FROM "h2o_feet" WHERE "location" = 'santa_monica' AND time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z'

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time integral_water_level
1970-01-01T00:00:00Z 69.7470000000

{{% /expand %}}

{{% expand "Calculate the integral for the field values associated with each field key that matches a regular expression and specify the unit option" %}}

Return the area under the curve (in minutes) for the field values associated with each field key that stores numeric values includes the word water in the h2o_feet measurement.

SELECT INTEGRAL(/water/,1m) FROM "h2o_feet" WHERE "location" = 'santa_monica' AND time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z'

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time integral_water_level
1970-01-01T00:00:00Z 69.7470000000

{{% /expand %}}

{{% expand "Calculate the integral for the field values associated with a field key and include several clauses" %}}

Return the area under the curve (in minutes) for the field values associated with the water_level field key and in the h2o_feet measurement in the time range between 2019-08-18T00:00:00Z and 2019-08-18T00:30:00Z, grouped results into 12-minute intervals, and limit the number of results returned to one.

SELECT INTEGRAL("water_level",1m) FROM "h2o_feet" WHERE "location" = 'santa_monica' AND time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z' GROUP BY time(12m) LIMIT 1

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time integral
2019-08-18T00:00:00Z 28.3590000000

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

MEAN()

Returns the arithmetic mean (average) of field values. MEAN() supports int64 and float64 field value data types.

Syntax

SELECT MEAN( [ * | <field_key> | /<regular_expression>/ ] ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

MEAN(field_key) Returns the average field value associated with the field key.

`MEAN(/regular_expression/)

Returns the average field value associated with each field key that matches the regular expression.

MEAN(*) Returns the average field value associated with each field key in the measurement.

Examples

{{< expand-wrapper >}} {{% expand "Calculate the mean field value associated with a field key" %}}

Return the average field value in the water_level field key in the h2o_feet measurement.

SELECT MEAN("water_level") FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time mean
1970-01-01T00:00:00Z 4.4418674882

{{% /expand %}}

{{% expand "Calculate the mean field value associated with each field key in a measurement" %}}

Return the average field value for every field key that stores numeric values in the h2o_feet measurement. The h2o_feet measurement has one numeric field: water_level.

SELECT MEAN(*) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time mean_water_level
1970-01-01T00:00:00Z 4.4418674882

{{% /expand %}}

{{% expand "Calculate the mean field value associated with each field key that matches a regular expression" %}}

Return the average field value for each field key that stores numeric values and includes the word water in the h2o_feet measurement.

SELECT MEAN(/water/) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time mean_water_level
1970-01-01T00:00:00Z 4.4418674882

{{% /expand %}}

{{% expand "Calculate the mean field value associated with a field key and include several clauses" %}}

Return the average of the values in the water_level field key in the time range between 2019-08-18T00:00:00Z and 2019-08-18T00:30:00Z and group results into 12-minute time intervals and per tag. Then fill empty time intervals with 9.01 and limit the number of points and series returned to seven and one.

SELECT MEAN("water_level") FROM "h2o_feet" WHERE time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z' GROUP BY time(12m),* fill(9.01) LIMIT 7 SLIMIT 1

{{% influxql/table-meta %}} name: h2o_feet tags: location=coyote_creek {{% /influxql/table-meta %}}

time mean
2019-08-18T00:00:00Z 8.4615000000
2019-08-18T00:12:00Z 8.2725000000
2019-08-18T00:24:00Z 8.0710000000

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

MEDIAN()

Returns the middle value from a sorted list of field values. MEDIAN() supports int64 and float64 field value data types.

{{% note %}} Note: MEDIAN() is nearly equivalent to PERCENTILE(field_key, 50), except MEDIAN() returns the average of the two middle field values if the field contains an even number of values. {{% /note %}}

Syntax

SELECT MEDIAN( [ * | <field_key> | /<regular_expression>/ ] ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

MEDIAN(field_key)

Returns the middle field value associated with the field key.

MEDIAN(/regular_expression/)

Returns the middle field value associated with each field key that matches the regular expression.

MEDIAN(*)

Returns the middle field value associated with each field key in the measurement.

Examples

{{< expand-wrapper >}} {{% expand "Calculate the median field value associated with a field key" %}}

Return the middle field value in the water_level field key and in the h2o_feet measurement.

SELECT MEDIAN("water_level") FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time median
1970-01-01T00:00:00Z 4.1240000000

{{% /expand %}}

{{% expand "Calculate the median field value associated with each field key in a measurement" %}}

Return the middle field value for every field key that stores numeric values in the h2o_feet measurement. The h2o_feet measurement has one numeric field: water_level.

SELECT MEDIAN(*) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time median_water_level
1970-01-01T00:00:00Z 4.1240000000

{{% /expand %}}

{{% expand "Calculate the median field value associated with each field key that matches a regular expression" %}}

Return the middle field value for every field key that stores numeric values and includes the word water in the h2o_feet measurement.

SELECT MEDIAN(/water/) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time median_water_level
1970-01-01T00:00:00Z 4.1240000000

{{% /expand %}}

{{% expand "Calculate the median field value associated with a field key and include several clauses" %}}

Return the middle field value in the water_level field key in the time range between 2019-08-18T00:00:00Z and 2019-08-18T00:30:00Z and group results into 12-minute time intervals and per tag. Then fill empty time intervals with 700 , limit the number of points and series returned to seven and one, and offset the series returned by one.

SELECT MEDIAN("water_level") FROM "h2o_feet" WHERE time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z' GROUP BY time(12m),* fill(700) LIMIT 7 SLIMIT 1 SOFFSET 1

{{% influxql/table-meta %}} name: h2o_feet tags: location=santa_monica {{% /influxql/table-meta %}}

time median
2019-08-18T00:00:00Z 2.3655000000
2019-08-18T00:12:00Z 2.3360000000
2019-08-18T00:24:00Z 2.2655000000

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

MODE()

Returns the most frequent value in a list of field values. MODE() supports all field value data types.

{{% note %}} Note: MODE() returns the field value with the earliest timestamp if there's a tie between two or more values for the maximum number of occurrences. {{% /note %}}

Syntax

SELECT MODE( [ * | <field_key> | /<regular_expression>/ ] ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

MODE(field_key)

Returns the most frequent field value associated with the field key.

MODE(/regular_expression/)

Returns the most frequent field value associated with each field key that matches the regular expression.

MODE(*)

Returns the most frequent field value associated with each field key in the measurement.

Examples

{{< expand-wrapper >}}

{{% expand "Calculate the mode field value associated with a field key" %}}

Return the most frequent field value in the level description field key and in the h2o_feet measurement.

SELECT MODE("level description") FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time mode
1970-01-01T00:00:00Z between 3 and 6 feet

{{% /expand %}}

{{% expand "Calculate the mode field value associated with each field key in a measurement" %}}

Return the most frequent field value for every field key in the h2o_feet measurement. The h2o_feet measurement has two field keys: level description and water_level.

SELECT MODE(*) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time mode_level description mode_water_level
1970-01-01T00:00:00Z between 3 and 6 feet 2.6900000000

{{% /expand %}}

{{% expand "Calculate the mode field value associated with each field key that matches a regular expression" %}}

Return the most frequent field value for every field key that includes the word /water/ in the h2o_feet measurement.

SELECT MODE(/water/) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time mode_water_level
1970-01-01T00:00:00Z 2.6900000000

{{% /expand %}}

{{% expand "Calculate the mode field value associated with a field key and include several clauses" %}}

Return the mode of the values associated with the water_level field key in the time range between 2019-08-18T00:00:00Z and 2019-08-18T00:30:00Z and group results into 12-minute time intervals and per tag. Then limits the number of points and series returned to three and one, and it [offsets](/influxdb/version/query-data/influxql/explore-data #the-offset-and-soffset-clauses) the series returned by one.

SELECT MODE("level description") FROM "h2o_feet" WHERE time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z' GROUP BY time(12m),* LIMIT 3 SLIMIT 1 SOFFSET 1

{{% influxql/table-meta %}} name: h2o_feet tags: location=santa_monica {{% /influxql/table-meta %}}

time mode
2019-08-18T00:00:00Z below 3 feet
2019-08-18T00:12:00Z below 3 feet
2019-08-18T00:24:00Z below 3 feet

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

SPREAD()

Returns the difference between the minimum and maximum field values. SPREAD() supports int64 and float64 field value data types.

Syntax

SELECT SPREAD( [ * | <field_key> | /<regular_expression>/ ] ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

SPREAD(field_key)

Returns the difference between the minimum and maximum field values associated with the field key.

SPREAD(/regular_expression/)

Returns the difference between the minimum and maximum field values associated with each field key that matches the regular expression.

SPREAD(*)

Returns the difference between the minimum and maximum field values associated with each field key in the measurement.

Examples

{{< expand-wrapper >}}

{{% expand "Calculate the spread for the field values associated with a field key" %}}

Return the difference between the minimum and maximum field values in the water_level field key and in the h2o_feet measurement.

SELECT SPREAD("water_level") FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time spread
1970-01-01T00:00:00Z 10.5740000000

{{% /expand %}}

{{% expand "Calculate the spread for the field values associated with each field key in a measurement" %}}

Return the difference between the minimum and maximum field values for every field key that stores numeric values in the h2o_feet measurement. The h2o_feet measurement has one numeric field: water_level.

SELECT SPREAD(*) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time spread_water_level
1970-01-01T00:00:00Z 10.5740000000

{{% /expand %}}

{{% expand "Calculate the spread for the field values associated with each field key that matches a regular expression" %}}

Return the difference between the minimum and maximum field values for every field key that stores numeric values and includes the word water in the h2o_feet measurement.

SELECT SPREAD(/water/) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time spread_water_level
1970-01-01T00:00:00Z 10.5740000000

{{% /expand %}}

{{% expand "Calculate the spread for the field values associated with a field key and include several clauses" %}}

Return the difference between the minimum and maximum field values in the water_level field key in the time range between 2019-08-18T00:00:00Z and 2019-08-18T00:30:00Z and group results into 12-minute time intervals and per tag. Then fill empty time intervals with 18, lim ts the number of points and series returned to three and one, and offsets the series returned by one.

SELECT SPREAD("water_level") FROM "h2o_feet" WHERE time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z' GROUP BY time(12m),* fill(18) LIMIT 3 SLIMIT 1 SOFFSET 1

{{% influxql/table-meta %}} name: h2o_feet tags: location=santa_monica {{% /influxql/table-meta %}}

time spread
2019-08-18T00:00:00Z 0.0270000000
2019-08-18T00:12:00Z 0.0140000000
2019-08-18T00:24:00Z 0.0030000000

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

STDDEV()

Returns the standard deviation of field values. STDDEV() supports int64 and float64 field value data types.

Syntax

SELECT STDDEV( [ * | <field_key> | /<regular_expression>/ ] ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

STDDEV(field_key)

Returns the standard deviation of field values associated with the field key.

STDDEV(/regular_expression/)

Returns the standard deviation of field values associated with each field key that matches the regular expression.

STDDEV(*)

Returns the standard deviation of field values associated with each field key in the measurement.

Examples

{{< expand-wrapper >}} {{% expand "Calculate the standard deviation for the field values associated with a field key" %}}

Return the standard deviation of the field values in the water_level field key and in the h2o_feet measurement.

SELECT STDDEV("water_level") FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time stddev
1970-01-01T00:00:00Z 2.2789744110

{{% /expand %}}

{{% expand "Calculate the standard deviation for the field values associated with each field key in a measurement" %}}

Return the standard deviation of numeric fields in the h2o_feet measurement. The h2o_feet measurement has one numeric field: water_level.

SELECT STDDEV(*) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time stddev_water_level
1970-01-01T00:00:00Z 2.2789744110

{{% /expand %}}

{{% expand "Calculate the standard deviation for the field values associated with each field key that matches a regular expression" %}}

Return the standard deviation of numeric fields with water in the field key in the h2o_feet measurement.

SELECT STDDEV(/water/) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time stddev_water_level
1970-01-01T00:00:00Z 2.2789744110

{{% /expand %}}

{{% expand "Calculate the standard deviation for the field values associated with a field key and include several clauses" %}}

Return the standard deviation of the field values in the water_level field key in the time range between 2019-08-18T00:00:00Z and 2019-08-18T00:30:00Z and group results into 12-minute time intervals and per tag. Then fill empty time intervals with 18000, limit the number of points and series returned to two and one, and offsets the series returned by one.

SELECT STDDEV("water_level") FROM "h2o_feet" WHERE time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z' GROUP BY time(12m),* fill(18000) LIMIT 2 SLIMIT 1 SOFFSET 1

{{% influxql/table-meta %}} name: h2o_feet tags: location=santa_monica {{% /influxql/table-meta %}}

time stddev
2019-08-18T00:00:00Z 0.0190918831
2019-08-18T00:12:00Z 0.0098994949

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

SUM()

Returns the sum of field values. SUM() supports int64 and float64 field value data types.

Syntax

SELECT SUM( [ * | <field_key> | /<regular_expression>/ ] ) FROM_clause [WHERE_clause] [GROUP_BY_clause] [ORDER_BY_clause] [LIMIT_clause] [OFFSET_clause] [SLIMIT_clause] [SOFFSET_clause]

SUM(field_key)

Returns the sum of field values associated with the field key.

SUM(/regular_expression/)

Returns the sum of field values associated with each field key that matches the regular expression.

SUM(*)

Returns the sums of field values associated with each field key in the measurement.

Examples

{{< expand-wrapper >}} {{% expand "Calculate the sum of the field values associated with a field key" %}}

Return the summed total of the field values in the water_level field key and in the h2o_feet measurement.

SELECT SUM("water_level") FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time sum
1970-01-01T00:00:00Z 271069.4053333958

{{% /expand %}}

{{% expand "Calculate the sum of the field values associated with each field key in a measurement" %}}

Return the summed total of numeric fields in the h2o_feet measurement. The h2o_feet measurement has one numeric field: water_level.

SELECT SUM(*) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time sum_water_level
1970-01-01T00:00:00Z 271069.4053333958

{{% /expand %}}

{{% expand "Calculate the sum of the field values associated with each field key that matches a regular expression" %}}

Return the summed total of numeric fields with water in the field key in the h2o_feet measurement.

SELECT SUM(/water/) FROM "h2o_feet"

{{% influxql/table-meta %}} name: h2o_feet {{% /influxql/table-meta %}}

time sum_water_level
1970-01-01T00:00:00Z 271069.4053333958

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{{% expand "Calculate the sum of the field values associated with a field key and include several clauses" %}}

Return the summed total of the field values in the water_level field key in the time range between 2019-08-18T00:00:00Z and 2019-08-18T00:30:00Z and group results into 12-minute time intervals and per tag. Then fill empty time intervals with 18000, and limit the number of points and series returned to four and one.

SELECT SUM("water_level") FROM "h2o_feet" WHERE time >= '2019-08-18T00:00:00Z' AND time <= '2019-08-18T00:30:00Z' GROUP BY time(12m),* fill(18000) LIMIT 4 SLIMIT 1

{{% influxql/table-meta %}} name: h2o_feet tags: location=coyote_creek {{% /influxql/table-meta %}}

time sum
2019-08-18T00:00:00Z 16.9230000000
2019-08-18T00:12:00Z 16.5450000000
2019-08-18T00:24:00Z 16.1420000000

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