join() function

The join() function merges two input streams into a single output stream based on columns with equal values. Null values are not considered equal when comparing column values. 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

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

(Required) Map of two streams to join.

Data type: Record

on

(Required) List of columns to join on.

Data type: Array of strings

method

Join method to use to join. Defaults to "inner".

Data type: String

Possible Values:

• inner

Examples

Example join with sample data

Given the following two streams of data:

SF_Temp**

NY_Temp**

And the following join query:

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

The output will be:

Cross-measurement join

data_1 = from(bucket:"example-bucket")
  |> range(start:-15m)
  |> filter(fn: (r) =>
    r._measurement == "cpu" and
    r._field == "usage_system"
  )

data_2 = from(bucket:"example-bucket")
  |> 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"]
)

join() versus union()

join() creates new rows based on common values in one or more specified columns. Output rows also contain the differing values from each of the joined streams. union() does not modify data in rows, but unifies separate streams of tables into a single stream of tables and groups rows of data based on existing group keys.

Given two streams of tables, t1 and t2, the results of join() and union() are illustrated below: