Back to Influxdb

count() function

content/flux/v0/stdlib/universe/count.md

latest2.8 KB
Original Source
<!------------------------------------------------------------------------------ IMPORTANT: This page was generated from comments in the Flux source code. Any edits made directly to this page will be overwritten the next time the documentation is generated. To make updates to this documentation, update the function comments above the function definition in the Flux source code: https://github.com/influxdata/flux/blob/master/stdlib/universe/universe.flux#L163-L163 Contributing to Flux: https://github.com/influxdata/flux#contributing Fluxdoc syntax: https://github.com/influxdata/flux/blob/master/docs/fluxdoc.md ------------------------------------------------------------------------------->

count() returns the number of records in each input table.

The function counts both null and non-null records.

Empty tables

count() returns 0 for empty tables. To keep empty tables in your data, set the following parameters for the following functions:

FunctionParameter
filter()onEmpty: "keep"
window()createEmpty: true
aggregateWindow()createEmpty: true
Function type signature
js
(<-tables: stream[A], ?column: string) => stream[B] where A: Record, B: Record

{{% caption %}} For more information, see Function type signatures. {{% /caption %}}

Parameters

column

Column to count values in and store the total count.

tables

Input data. Default is piped-forward data (<-).

Examples

Count the number of records in each input table

js
import "sampledata"

sampledata.string()
    |> count()

Count the number of records with a specific value

  1. Use filter() to filter data by the specific value you want to count.
  2. Use count() to count the number of rows in the table.
js
import "sampledata"

data =
    sampledata.int()
        |> filter(fn: (r) => r._value > 10)

data
    |> count()

{{< expand-wrapper >}} {{% expand "View example input and output" %}}

Input data

_time_value*tag
2021-01-01T00:00:30Z17t1
2021-01-01T00:00:40Z15t1
_time_value*tag
2021-01-01T00:00:00Z19t2
2021-01-01T00:00:30Z19t2
2021-01-01T00:00:40Z13t2

Output data

*tag_value
t12
*tag_value
t23

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