Troubleshoot join operations

Cause

The group keys of each input stream aren’t the same. Functions in the join package use group keys to quickly identify what tables should be compared.

Solution

Use group() to regroup your two input streams so their group keys match before attempting to join them together.

Cause

There are no matching group key instances in your data streams. Functions in the join package only compare tables with matching group key instances. Input streams may have matching group keys, but there are no matching group key instances in your stream.

This may happen when joining two separate fields queried from InfluxDB. By default, InfluxDB returns data with _field as part of the group key. If each stream contains a different field, tables in the two streams won’t be compared because they won’t have any matching group key instances.

Solution

Use group() to remove any columns from the group keys of each input stream that would prevent group key instances from matching.

Cause

Your on join predicate uses a column that doesn’t exist. In the on predicate function, you’re trying to compare a column that doesn’t exist in one of your input streams.

Solution

Ensure the columns that you’re comparing in the on predicate function exist in the input streams. If necessary, update column names in the predicate function.

Cause

Your on join predicate uses a column that doesn’t exist. In the on predicate function for an outer join, you’re trying to use a value from a column that doesn’t exist in the “primary” input stream (left for join.left() and right for join.right()).

Solution

Ensure the columns that you’re comparing in the on predicate function actually exist in the input streams. If necessary, update column names in the predicate function.

Cause

Your on join predicate uses a column that doesn’t exist. In the on predicate function, you’re trying to compare a column that doesn’t exist in one of your input streams.

Solution

Ensure the columns that you’re comparing in the on predicate function actually exist in the input streams. If necessary, update column names in the predicate function.

Cause

Your as output schema function uses a column that doesn’t exist. If using an outer join, the as is trying to use a value from a column that doesn’t exist in the “primary” input stream (left for join.left() and right for join.right()).

Solution

Ensure the columns that you’re using in the as output function to assign values to the output actually exist in the input streams.

Cause

One of your input streams is an empty stream of tables. Functions in the join package error when one or both of the input streams are empty.

Solution

Use array.from() and union() to insert a dummy table into each stream that you filter out after the join operation. The dummy table needs to include all group key columns of the stream it is unioned with.