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移除书签Group data in InfluxDB with Flux
With Flux, you can group data by any column in your queried data set. “Grouping” partitions data into tables in which each row shares a common value for specified columns. This guide walks through grouping data in Flux and provides examples of how data is shaped in the process.
If you’re just getting started with Flux queries, check out the following:
- Get started with Flux for a conceptual overview of Flux and parts of a Flux query.
- Execute queries to discover a variety of ways to run your queries.
Group keys
Every table has a group key – a list of columns which for which every row in the table has the same value.
Example group key
[_start, _stop, _field, _measurement, host]
Grouping data in Flux is essentially defining the group key of output tables. Understanding how modifying group keys shapes output data is key to successfully grouping and transforming data into your desired output.
group() Function
Flux’s group() function defines the group key for output tables, i.e. grouping records based on values for specific columns.
group() example
dataStream|> group(columns: ["cpu", "host"])
Resulting group key
[cpu, host]
The group() function has the following parameters:
columns
The list of columns to include or exclude (depending on the mode) in the grouping operation.
mode
The method used to define the group and resulting group key. Possible values include by and except.
Example grouping operations
To illustrate how grouping works, define a dataSet variable that queries System CPU usage from the example-bucket bucket. Filter the cpu tag so it only returns results for each numbered CPU core.
Data set
CPU used by system operations for all numbered CPU cores. It uses a regular expression to filter only numbered cores.
dataSet = from(bucket: "example-bucket")|> range(start: -2m)|> filter(fn: (r) =>r._field == "usage_system" andr.cpu =~ /cpu[0-9*]/)|> drop(columns: ["host"])
This example drops the host column from the returned data since the CPU data is only tracked for a single host and it simplifies the output tables. Don’t drop the host column if monitoring multiple hosts.
Table: keys: [_start, _stop, _field, _measurement, cpu]_start:time _stop:time _field:string _measurement:string cpu:string _time:time _value:float------------------------------ ------------------------------ ---------------------- ---------------------- ---------------------- ------------------------------ ----------------------------2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:34:00.000000000Z 7.8921078921078922018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:34:10.000000000Z 7.22018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:34:20.000000000Z 7.42018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:34:30.000000000Z 5.52018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:34:40.000000000Z 7.42018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:34:50.000000000Z 7.52018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:35:00.000000000Z 10.32018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:35:10.000000000Z 9.22018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:35:20.000000000Z 8.42018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:35:30.000000000Z 8.52018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:35:40.000000000Z 8.62018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:35:50.000000000Z 10.22018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu0 2018-11-05T21:36:00.000000000Z 10.6Table: keys: [_start, _stop, _field, _measurement, cpu]_start:time _stop:time _field:string _measurement:string cpu:string _time:time _value:float------------------------------ ------------------------------ ---------------------- ---------------------- ---------------------- ------------------------------ ----------------------------2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:34:00.000000000Z 0.79920079920079922018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:34:10.000000000Z 0.72018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:34:20.000000000Z 0.72018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:34:30.000000000Z 0.42018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:34:40.000000000Z 0.72018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:34:50.000000000Z 0.72018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:35:00.000000000Z 1.42018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:35:10.000000000Z 1.22018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:35:20.000000000Z 0.82018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:35:30.000000000Z 0.89910089910089912018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:35:40.000000000Z 0.80080080080080082018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:35:50.000000000Z 0.9990009990009992018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu1 2018-11-05T21:36:00.000000000Z 1.1022044088176353Table: keys: [_start, _stop, _field, _measurement, cpu]_start:time _stop:time _field:string _measurement:string cpu:string _time:time _value:float------------------------------ ------------------------------ ---------------------- ---------------------- ---------------------- ------------------------------ ----------------------------2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:34:00.000000000Z 4.12018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:34:10.000000000Z 3.62018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:34:20.000000000Z 3.52018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:34:30.000000000Z 2.62018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:34:40.000000000Z 4.52018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:34:50.000000000Z 4.8951048951048952018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:35:00.000000000Z 6.9069069069069072018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:35:10.000000000Z 5.72018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:35:20.000000000Z 5.12018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:35:30.000000000Z 4.72018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:35:40.000000000Z 5.12018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:35:50.000000000Z 5.92018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu2 2018-11-05T21:36:00.000000000Z 6.4935064935064934Table: keys: [_start, _stop, _field, _measurement, cpu]_start:time _stop:time _field:string _measurement:string cpu:string _time:time _value:float------------------------------ ------------------------------ ---------------------- ---------------------- ---------------------- ------------------------------ ----------------------------2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:34:00.000000000Z 0.50050050050050052018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:34:10.000000000Z 0.52018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:34:20.000000000Z 0.52018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:34:30.000000000Z 0.32018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:34:40.000000000Z 0.62018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:34:50.000000000Z 0.62018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:35:00.000000000Z 1.39860139860139852018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:35:10.000000000Z 0.92018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:35:20.000000000Z 0.50050050050050052018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:35:30.000000000Z 0.72018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:35:40.000000000Z 0.62018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:35:50.000000000Z 0.82018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z usage_system cpu cpu3 2018-11-05T21:36:00.000000000Z 0.9
Note that the group key is output with each table: Table: keys: <group-key>.
Group by CPU
Group the dataSet stream by the cpu column.
dataSet|> group(columns: ["cpu"])
This won’t actually change the structure of the data since it already has cpu in the group key and is therefore grouped by cpu. However, notice that it does change the group key:
Group by CPU output tables
Table: keys: [cpu]cpu:string _stop:time _time:time _value:float _field:string _measurement:string _start:time---------------------- ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------cpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:00.000000000Z 7.892107892107892 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:10.000000000Z 7.2 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:20.000000000Z 7.4 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:30.000000000Z 5.5 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:40.000000000Z 7.4 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:50.000000000Z 7.5 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:00.000000000Z 10.3 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:10.000000000Z 9.2 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:20.000000000Z 8.4 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:30.000000000Z 8.5 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:40.000000000Z 8.6 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:50.000000000Z 10.2 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu0 2018-11-05T21:36:00.000000000Z 2018-11-05T21:36:00.000000000Z 10.6 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [cpu]cpu:string _stop:time _time:time _value:float _field:string _measurement:string _start:time---------------------- ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------cpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:00.000000000Z 0.7992007992007992 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:10.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:20.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:30.000000000Z 0.4 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:40.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:50.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:00.000000000Z 1.4 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:10.000000000Z 1.2 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:20.000000000Z 0.8 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:30.000000000Z 0.8991008991008991 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:40.000000000Z 0.8008008008008008 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:50.000000000Z 0.999000999000999 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu1 2018-11-05T21:36:00.000000000Z 2018-11-05T21:36:00.000000000Z 1.1022044088176353 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [cpu]cpu:string _stop:time _time:time _value:float _field:string _measurement:string _start:time---------------------- ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------cpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:00.000000000Z 4.1 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:10.000000000Z 3.6 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:20.000000000Z 3.5 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:30.000000000Z 2.6 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:40.000000000Z 4.5 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:50.000000000Z 4.895104895104895 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:00.000000000Z 6.906906906906907 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:10.000000000Z 5.7 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:20.000000000Z 5.1 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:30.000000000Z 4.7 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:40.000000000Z 5.1 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:50.000000000Z 5.9 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu2 2018-11-05T21:36:00.000000000Z 2018-11-05T21:36:00.000000000Z 6.4935064935064934 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [cpu]cpu:string _stop:time _time:time _value:float _field:string _measurement:string _start:time---------------------- ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------cpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:00.000000000Z 0.5005005005005005 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:10.000000000Z 0.5 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:20.000000000Z 0.5 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:30.000000000Z 0.3 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:40.000000000Z 0.6 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:50.000000000Z 0.6 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:00.000000000Z 1.3986013986013985 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:10.000000000Z 0.9 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:20.000000000Z 0.5005005005005005 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:30.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:40.000000000Z 0.6 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:35:50.000000000Z 0.8 usage_system cpu 2018-11-05T21:34:00.000000000Zcpu3 2018-11-05T21:36:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.9 usage_system cpu 2018-11-05T21:34:00.000000000Z
The visualization remains the same.
Group by time
Grouping data by the _time column is a good illustration of how grouping changes the structure of your data.
dataSet|> group(columns: ["_time"])
When grouping by _time, all records that share a common _time value are grouped into individual tables. So each output table represents a single point in time.
Group by time output tables
Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:34:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 7.892107892107892 usage_system cpu cpu02018-11-05T21:34:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.7992007992007992 usage_system cpu cpu12018-11-05T21:34:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 4.1 usage_system cpu cpu22018-11-05T21:34:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.5005005005005005 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:34:10.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 7.2 usage_system cpu cpu02018-11-05T21:34:10.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu cpu12018-11-05T21:34:10.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 3.6 usage_system cpu cpu22018-11-05T21:34:10.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.5 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:34:20.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 7.4 usage_system cpu cpu02018-11-05T21:34:20.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu cpu12018-11-05T21:34:20.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 3.5 usage_system cpu cpu22018-11-05T21:34:20.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.5 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:34:30.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 5.5 usage_system cpu cpu02018-11-05T21:34:30.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.4 usage_system cpu cpu12018-11-05T21:34:30.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 2.6 usage_system cpu cpu22018-11-05T21:34:30.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.3 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:34:40.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 7.4 usage_system cpu cpu02018-11-05T21:34:40.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu cpu12018-11-05T21:34:40.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 4.5 usage_system cpu cpu22018-11-05T21:34:40.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.6 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:34:50.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 7.5 usage_system cpu cpu02018-11-05T21:34:50.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu cpu12018-11-05T21:34:50.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 4.895104895104895 usage_system cpu cpu22018-11-05T21:34:50.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.6 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:35:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 10.3 usage_system cpu cpu02018-11-05T21:35:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 1.4 usage_system cpu cpu12018-11-05T21:35:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 6.906906906906907 usage_system cpu cpu22018-11-05T21:35:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 1.3986013986013985 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:35:10.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 9.2 usage_system cpu cpu02018-11-05T21:35:10.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 1.2 usage_system cpu cpu12018-11-05T21:35:10.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 5.7 usage_system cpu cpu22018-11-05T21:35:10.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.9 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:35:20.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 8.4 usage_system cpu cpu02018-11-05T21:35:20.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.8 usage_system cpu cpu12018-11-05T21:35:20.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 5.1 usage_system cpu cpu22018-11-05T21:35:20.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.5005005005005005 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:35:30.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 8.5 usage_system cpu cpu02018-11-05T21:35:30.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.8991008991008991 usage_system cpu cpu12018-11-05T21:35:30.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 4.7 usage_system cpu cpu22018-11-05T21:35:30.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:35:40.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 8.6 usage_system cpu cpu02018-11-05T21:35:40.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.8008008008008008 usage_system cpu cpu12018-11-05T21:35:40.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 5.1 usage_system cpu cpu22018-11-05T21:35:40.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.6 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:35:50.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 10.2 usage_system cpu cpu02018-11-05T21:35:50.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.999000999000999 usage_system cpu cpu12018-11-05T21:35:50.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 5.9 usage_system cpu cpu22018-11-05T21:35:50.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.8 usage_system cpu cpu3Table: keys: [_time]_time:time _start:time _stop:time _value:float _field:string _measurement:string cpu:string------------------------------ ------------------------------ ------------------------------ ---------------------------- ---------------------- ---------------------- ----------------------2018-11-05T21:36:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 10.6 usage_system cpu cpu02018-11-05T21:36:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 1.1022044088176353 usage_system cpu cpu12018-11-05T21:36:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 6.4935064935064934 usage_system cpu cpu22018-11-05T21:36:00.000000000Z 2018-11-05T21:34:00.000000000Z 2018-11-05T21:36:00.000000000Z 0.9 usage_system cpu cpu3
Because each timestamp is structured as a separate table, when visualized, all points that share the same timestamp appear connected.
With some further processing, you could calculate the average CPU usage across all CPUs per point of time and group them into a single table, but we won’t cover that in this example. If you’re interested in running and visualizing this yourself, here’s what the query would look like:
dataSet|> group(columns: ["_time"])|> mean()|> group(columns: ["_value", "_time"], mode: "except")
Group by CPU and time
Group by the cpu and _time columns.
dataSet|> group(columns: ["cpu", "_time"])
This outputs a table for every unique cpu and _time combination:
Group by CPU and time output tables
Table: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:00.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 7.892107892107892 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:00.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.7992007992007992 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:00.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 4.1 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:00.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.5005005005005005 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:10.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 7.2 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:10.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:10.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 3.6 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:10.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.5 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:20.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 7.4 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:20.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:20.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 3.5 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:20.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.5 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:30.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 5.5 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:30.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.4 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:30.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 2.6 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:30.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.3 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:40.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 7.4 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:40.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:40.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 4.5 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:40.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.6 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:50.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 7.5 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:50.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:50.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 4.895104895104895 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:34:50.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.6 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:00.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 10.3 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:00.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 1.4 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:00.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 6.906906906906907 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:00.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 1.3986013986013985 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:10.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 9.2 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:10.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 1.2 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:10.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 5.7 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:10.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.9 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:20.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 8.4 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:20.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.8 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:20.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 5.1 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:20.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.5005005005005005 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:30.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 8.5 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:30.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.8991008991008991 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:30.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 4.7 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:30.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.7 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:40.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 8.6 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:40.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.8008008008008008 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:40.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 5.1 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:40.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.6 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:50.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 10.2 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:50.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 0.999000999000999 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:50.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 5.9 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:35:50.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.8 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:36:00.000000000Z cpu0 2018-11-05T21:36:00.000000000Z 10.6 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:36:00.000000000Z cpu1 2018-11-05T21:36:00.000000000Z 1.1022044088176353 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:36:00.000000000Z cpu2 2018-11-05T21:36:00.000000000Z 6.4935064935064934 usage_system cpu 2018-11-05T21:34:00.000000000ZTable: keys: [_time, cpu]_time:time cpu:string _stop:time _value:float _field:string _measurement:string _start:time------------------------------ ---------------------- ------------------------------ ---------------------------- ---------------------- ---------------------- ------------------------------2018-11-05T21:36:00.000000000Z cpu3 2018-11-05T21:36:00.000000000Z 0.9 usage_system cpu 2018-11-05T21:34:00.000000000Z
When visualized, tables appear as individual, unconnected points.
Grouping by cpu and _time is a good illustration of how grouping works.
In conclusion
Grouping is a powerful way to shape your data into your desired output format. It modifies the group keys of output tables, grouping records into tables that all share common values within specified columns.
