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title: 'Partitioning' sidebar_label: 'Partitioning' description: 'Partitioning for accelerated datasets' sidebar_position: 4

Accelerations can be partitioned using an arbitrary expression to group rows together into separate files. This enables Spice to avoid reading unnecessary partitions, making particular queries faster. To partition your accelerations, add the partition_by acceleration parameter:

This example uses a bucket user-defined function (UDF) to hash the PULocationID column and put each row into one of 50 partition files.

This enables partition pruning for queries that filter on the column referenced in the partition_by expression:

This will result in a scan plan that only reads from the partitions that contain the values from the IN list.

:::warning[Limitations]

• Partitioning is currently limited to engine: duckdb or engine: cayenne with mode: file.
• partition_by currently only supports 1 expression for partitioning.
• Expression must reference exactly one column from the dataset.
• Expression must produce a scalar value.
• Expression cannot contain a subquery.
• Partition pruning is limited to specific filter expressions such as:
  • WHERE foo = bar
  • WHERE foo IN (bar, baz, ...)
  • WHERE foo NOT IN (bar, baz, ...)

:::