join() function

The join() function merges two or more input streams whose values are equal on a set of common columns into a single output stream. The resulting schema is the union of the input schemas. The resulting group key is the union of the input group keys.

Function type: Transformation
Output data type: Object

join(tables: {key1: table1, key2: table2}, on: ["_time", "_field"], method: "inner")

Output schema

The column schema of the output stream is the union of the input schemas. It is also the same for the output group key. Columns are renamed using the pattern <column>_<table> to prevent ambiguity in joined tables.

Example:

If you have two streams of data, data_1 and data_2, with the following group keys:

data_1: [_time, _field]
data_2: [_time, _field]

And join them with:

join(tables: {d1: data_1, d2: data_2}, on: ["_time"])

The resulting group keys for all tables will be: [_time, _field_d1, _field_d2]

Parameters

tables

The map of streams to be joined. Required.

Data type: Object

join() currently only supports two input streams.

on

The list of columns on which to join. Required.

Data type: Array of strings

method

The method used to join. Defaults to "inner".

Data type: String

Possible Values:
  • inner
  • cross
  • left
  • right
  • full

The on parameter and the cross method are mutually exclusive.

Examples

Example join with sample data

Given the following two streams of data:

SF_Temp**
_time _field _value
0001 “temp” 70
0002 “temp” 75
0003 “temp” 72
NY_Temp**
_time _field _value
0001 “temp” 55
0002 “temp” 56
0003 “temp” 55

And the following join query:

join(
  tables: {sf: SF_Temp, ny: NY_Temp},
  on: ["_time", "_field"]
)

The output will be:

_time _field _value_ny _value_sf
0001 “temp” 55 70
0002 “temp” 56 75
0003 “temp” 55 72

Cross-measurement join

data_1 = from(bucket:"telegraf/autogen")
  |> range(start:-15m)
  |> filter(fn: (r) =>
    r._measurement == "cpu" AND
    r._field == "usage_system"
  )

data_2 = from(bucket:"telegraf/autogen")
  |> range(start:-15m)
  |> filter(fn: (r) =>
    r._measurement == "mem" AND
    r._field == "used_percent"
  )

join(
  tables: {d1: data_1, d2: data_2},
  on: ["_time", "host"]
)

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