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Join data | Join data with Flux | Flux supports inner, full outer, left outer, and right outer joins. Learn how to use the `join` package to join two data sets with common values. |
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Use the Flux join
package to join two data sets based on common values.
Learn how join two data sets using the following join methods:
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Inner join
{{< svg svg="static/svgs/join-diagram.svg" class="inner small center" >}} {{< /flex-content >}} {{< flex-content "quarter" >}}Left outer join
{{< svg svg="static/svgs/join-diagram.svg" class="left small center" >}} {{< /flex-content >}} {{< flex-content "quarter" >}}Right outer join
{{< svg svg="static/svgs/join-diagram.svg" class="right small center" >}} {{< /flex-content >}} {{< flex-content "quarter" >}}Full outer join
{{< svg svg="static/svgs/join-diagram.svg" class="full small center" >}} {{< /flex-content >}} {{< /flex >}}{{% note %}}
When to use the join package
We recommend using the join
package to join streams that have mostly different
schemas or that come from two separate data sources.
If you're joining data from the same data source with the same schema, using
union()
and pivot()
to combine the data will likely be more performant.
For more information, see [When to use union and pivot instead of join functions](/{{< latest "influxdb" >}}/query-data/flux/join/#when-to-use-union-and-pivot-instead-of-join-functions). {{% /note %}}
- How join functions work
- Perform join operations {{< children type="anchored-list" filterOut="Troubleshoot join operations" >}}
- Troubleshoot join operations
How join functions work
join
functions join two streams of tables together based
on common values in each input stream.
Input streams
Each input stream is assigned to the left
or right
parameter.
Input streams can be defined from any valid data source.
For more information, see:
- Query data sources
- Define ad hoc tables with
array.from()
Data requirements
To join data, each input stream must have the following:
-
One or more columns with common values to join on.
Columns do not need identical labels, but they do need to have comparable values. -
Identical group keys.
Functions in thejoin
package use group keys to quickly determine what tables from each input stream should be paired and evaluated for the join operation.
Both input streams should have the same group key. If they don't, your join operation may not find any matching tables and will return unexpected output. If the group keys of your input streams are not identical, usegroup()
to regroup each input stream before joining them together.{{% note %}} Only tables with the same group key instance are joined. {{% /note %}}
Join predicate function (on)
join
package functions require the on
parameter to compare values from each input stream (represented by l
(left) and r
(right))
and returns true
or false
.
Rows that return true
are joined.
This parameter is a predicate function.
(l, r) => l.column == r.column
Join output function (as)
join
package functions (except join.time()
)
require the as
parameter to define the output schema of the join.
The as
parameter returns a new record using values from
joined rows–left (l
) and right (r
).
(l, r) => ({l with name: r.name, location: r.location})
{{% note %}}
Do not modify group key columns
Do not modify group key columns. The as
function must return the same group key as both input streams to successfully perform a join.
{{% /note %}}
Perform join operations
The join
package supports the following join types and special use cases:
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Troubleshoot join operations
For information about unexpected behaviors and errors when using the join
package,
see Troubleshoot join operations.