pyflink.table.Table.group_by

Table.group_by(*fields: Expression) → GroupedTable

Groups the elements on some grouping keys. Use this before a selection with aggregations to perform the aggregation on a per-group basis. Similar to a SQL GROUP BY statement.

Example:

>>> tab.group_by(col('key')).select(col('key'), col('value').avg)

Parameters:

fields – Group keys.

Returns:

The grouped table.