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pyflink.table.Table.group_by#

Table.group_by(*fields: Union[str, pyflink.table.expression.Expression]) → pyflink.table.table.GroupedTable[source]#

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.

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