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experimental.join() function

content/flux/v0/stdlib/experimental/join.md

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<!------------------------------------------------------------------------------ IMPORTANT: This page was generated from comments in the Flux source code. Any edits made directly to this page will be overwritten the next time the documentation is generated. To make updates to this documentation, update the function comments above the function definition in the Flux source code: https://github.com/influxdata/flux/blob/master/stdlib/experimental/experimental.flux#L399-L403 Contributing to Flux: https://github.com/influxdata/flux#contributing Fluxdoc syntax: https://github.com/influxdata/flux/blob/master/docs/fluxdoc.md ------------------------------------------------------------------------------->

experimental.join() joins two streams of tables on the group key and _time column.

{{% warn %}}

Deprecated

experimental.join() is deprecated in favor of join.time(). The join package provides support for multiple join methods. {{% /warn %}}

Use the fn parameter to map new output tables using values from input tables.

Note: To join streams of tables with different fields or measurements, use group() or drop() to remove _field and _measurement from the group key before joining.

Function type signature
js
(fn: (left: A, right: B) => C, left: stream[A], right: stream[B]) => stream[C] where A: Record, B: Record, C: Record

{{% caption %}} For more information, see Function type signatures. {{% /caption %}}

Parameters

left

({{< req >}}) First of two streams of tables to join.

({{< req >}}) Second of two streams of tables to join.

fn

({{< req >}}) Function with left and right arguments that maps a new output record using values from the left and right input records. The return value must be a record.

Examples

Join two streams of tables

js
import "array"
import "experimental"

left =
    array.from(
        rows: [
            {_time: 2021-01-01T00:00:00Z, _field: "temp", _value: 80.1},
            {_time: 2021-01-01T01:00:00Z, _field: "temp", _value: 80.6},
            {_time: 2021-01-01T02:00:00Z, _field: "temp", _value: 79.9},
            {_time: 2021-01-01T03:00:00Z, _field: "temp", _value: 80.1},
        ],
    )
right =
    array.from(
        rows: [
            {_time: 2021-01-01T00:00:00Z, _field: "temp", _value: 75.1},
            {_time: 2021-01-01T01:00:00Z, _field: "temp", _value: 72.6},
            {_time: 2021-01-01T02:00:00Z, _field: "temp", _value: 70.9},
            {_time: 2021-01-01T03:00:00Z, _field: "temp", _value: 71.1},
        ],
    )

experimental.join(
    left: left,
    right: right,
    fn: (left, right) =>
        ({left with lv: left._value, rv: right._value, diff: left._value - right._value}),
)

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

Output data

_field_time_valuedifflvrv
temp2021-01-01T00:00:00Z80.1580.175.1
temp2021-01-01T01:00:00Z80.6880.672.6
temp2021-01-01T02:00:00Z79.9979.970.9
temp2021-01-01T03:00:00Z80.1980.171.1

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

Join two streams of tables with different fields and measurements

js
import "experimental"

s1 =
    from(bucket: "example-bucket")
        |> range(start: -1h)
        |> filter(fn: (r) => r._measurement == "foo" and r._field == "bar")
        |> group(columns: ["_time", "_measurement", "_field", "_value"], mode: "except")

s2 =
    from(bucket: "example-bucket")
        |> range(start: -1h)
        |> filter(fn: (r) => r._measurement == "baz" and r._field == "quz")
        |> group(columns: ["_time", "_measurement", "_field", "_value"], mode: "except")

experimental.join(
    left: s1,
    right: s2,
    fn: (left, right) => ({left with bar_value: left._value, quz_value: right._value}),
)