docs-v2/content/flux/v0/join-data/inner.md

title	description	menu	weight	related	list_code_example
Perform an inner join	Use [`join.inner()`](/flux/v0/stdlib/join/inner/) to perform an inner join of two streams of data. Inner joins drop any rows from both input streams that do not have a matching row in the other stream.	flux_v0 name parent Inner join Join data	101	/flux/v0/join-data/troubleshoot-joins/ /flux/v0/stdlib/join/ /flux/v0/stdlib/join/inner/	```js import "join" left = from(bucket: "example-bucket-1") |> //... right = from(bucket: "example-bucket-2") |> //... join.inner( left: left, right: right, on: (l, r) => l.column == r.column, as: (l, r) => ({l with name: r.name, location: r.location}), ) ```

Use join.inner() to perform an inner join of two streams of data. Inner joins drop any rows from both input streams that do not have a matching row in the other stream.

{{< svg svg="static/svgs/join-diagram.svg" class="inner" >}}

{{< expand-wrapper >}} {{% expand "View table illustration of an inner join" %}} {{< flex >}} {{% flex-content "third" %}}

left

r1	●	●
r2	●	●
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right

r1	▲	▲
r3	▲	▲
r4	▲	▲
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{{% flex-content "third" %}}

Inner join result

r1	●	●	▲	▲
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Use join.inner to join your data

1. Import the join package.

2. Define the left and right data streams to join:

   • Each stream must have one or more columns with common values. Column labels do not need to match, but column values do.
   • Each stream should have identical group keys.

   For more information, see join data requirements.

3. Use join.inner() to join the two streams together. Provide the following required parameters:

   • left: Stream of data representing the left side of the join.
   • right: Stream of data representing the right side of the join.
   • on: Join predicate. For example: (l, r) => l.column == r.column.
   • as: Join output function that returns a record with values from each input stream. For example: (l, r) => ({l with column1: r.column1, column2: r.column2}).

The following example uses a filtered selection from the machineProduction sample data set as the left data stream and an ad-hoc table created with array.from() as the right data stream.

{{% note %}}

Example data grouping

The example below ungroups the left stream to match the grouping of the right stream. After the two streams are joined together, the joined data is grouped by stationID. {{% /note %}}

import "array"
import "influxdata/influxdb/sample"
import "join"

left =
    sample.data(set: "machineProduction")
        |> filter(fn: (r) => r.stationID == "g1" or r.stationID == "g2" or r.stationID == "g3")
        |> filter(fn: (r) => r._field == "oil_temp")
        |> limit(n: 5)

right =
    array.from(
        rows: [
            {station: "g1", opType: "auto", last_maintained: 2021-07-15T00:00:00Z},
            {station: "g2", opType: "manned", last_maintained: 2021-07-02T00:00:00Z},
        ],
    )

join.inner(
    left: left |> group(),
    right: right,
    on: (l, r) => l.stationID == r.station,
    as: (l, r) => ({l with opType: r.opType, maintained: r.last_maintained}),
)
    |> group(columns: ["stationID"])

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

{{% note %}} _start and _stop columns have been omitted from example input and output. {{% /note %}}

Input

left

_time	_measurement	stationID	_field	_value
2021-08-01T00:00:00Z	machinery	g1	oil_temp	39.1
2021-08-01T00:00:11.51Z	machinery	g1	oil_temp	40.3
2021-08-01T00:00:19.53Z	machinery	g1	oil_temp	40.6
2021-08-01T00:00:25.1Z	machinery	g1	oil_temp	40.72
2021-08-01T00:00:36.88Z	machinery	g1	oil_temp	40.8

_time	_measurement	stationID	_field	_value
2021-08-01T00:00:00Z	machinery	g2	oil_temp	40.6
2021-08-01T00:00:27.93Z	machinery	g2	oil_temp	40.6
2021-08-01T00:00:54.96Z	machinery	g2	oil_temp	40.6
2021-08-01T00:01:17.27Z	machinery	g2	oil_temp	40.6
2021-08-01T00:01:41.84Z	machinery	g2	oil_temp	40.6

_time	_measurement	stationID	_field	_value
2021-08-01T00:00:00Z	machinery	g3	oil_temp	41.4
2021-08-01T00:00:14.46Z	machinery	g3	oil_temp	41.36
2021-08-01T00:00:25.29Z	machinery	g3	oil_temp	41.4
2021-08-01T00:00:38.77Z	machinery	g3	oil_temp	41.4
2021-08-01T00:00:51.2Z	machinery	g3	oil_temp	41.4

right

station	opType	last_maintained
g1	auto	2021-07-15T00:00:00Z
g2	manned	2021-07-02T00:00:00Z

Output

_time	_measurement	stationID	_field	_value	opType	maintained
2021-08-01T00:00:00Z	machinery	g1	oil_temp	39.1	auto	2021-07-15T00:00:00Z
2021-08-01T00:00:11.51Z	machinery	g1	oil_temp	40.3	auto	2021-07-15T00:00:00Z
2021-08-01T00:00:19.53Z	machinery	g1	oil_temp	40.6	auto	2021-07-15T00:00:00Z
2021-08-01T00:00:25.1Z	machinery	g1	oil_temp	40.72	auto	2021-07-15T00:00:00Z
2021-08-01T00:00:36.88Z	machinery	g1	oil_temp	40.8	auto	2021-07-15T00:00:00Z

_time	_measurement	stationID	_field	_value	opType	maintained
2021-08-01T00:00:00Z	machinery	g2	oil_temp	40.6	manned	2021-07-02T00:00:00Z
2021-08-01T00:00:27.93Z	machinery	g2	oil_temp	40.6	manned	2021-07-02T00:00:00Z
2021-08-01T00:00:54.96Z	machinery	g2	oil_temp	40.6	manned	2021-07-02T00:00:00Z
2021-08-01T00:01:17.27Z	machinery	g2	oil_temp	40.6	manned	2021-07-02T00:00:00Z
2021-08-01T00:01:41.84Z	machinery	g2	oil_temp	40.6	manned	2021-07-02T00:00:00Z

Things to note about the join output

• Because the right stream does not have a row with the g3 station tag, the joined output drops all rows with the g3 stationID tag from the left stream. join.inner() drops any rows that do not have a matching row in the other data stream.

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