Documentation

Perform a left outer join

Use join.left() to perform an left outer join of two streams of data. Left joins output a row for each row in the left data stream with data matching from the right data stream. If there is no matching data in the right data stream, non-group-key columns with values from the right data stream are null.

View table illustration of a left outer join

Use join.left 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.left() to join the two streams together. Provide the following 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.left(
    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 data


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The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Flux is going into maintenance mode and will not be supported in InfluxDB 3.0. This was a decision based on the broad demand for SQL and the continued growth and adoption of InfluxQL. We are continuing to support Flux for users in 1.x and 2.x so you can continue using it with no changes to your code. If you are interested in transitioning to InfluxDB 3.0 and want to future-proof your code, we suggest using InfluxQL.

For information about the future of Flux, see the following: