Documentation

Perform an inner join

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.

View table illustration of an inner join

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.

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.

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"])

View example input and output


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