Optimizing Iceberg tables - Amazon Athena
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Optimizing Iceberg tables

As data accumulates into an Iceberg table, queries gradually become less efficient because of the increased processing time required to open files. Additional computational cost is incurred if the table contains delete files. In Iceberg, delete files store row-level deletes, and the engine must apply the deleted rows to query results.

To help optimize the performance of queries on Iceberg tables, Athena supports manual compaction as a table maintenance command. Compactions optimize the structural layout of the table without altering table content.


The OPTIMIZE table REWRITE DATA compaction action rewrites data files into a more optimized layout based on their size and number of associated delete files. For syntax and table property details, see OPTIMIZE.


The following example merges delete files into data files and produces files near the targeted file size where the value of category is c1.

OPTIMIZE iceberg_table REWRITE DATA USING BIN_PACK WHERE category = 'c1'


VACUUM performs snapshot expiration and orphan file removal. These actions reduce metadata size and remove files not in the current table state that are also older than the retention period specified for the table. For syntax details, see VACUUM.


The following example uses a table property to configure the table iceberg_table to retain the last three days of data, then uses VACUUM to expire the old snapshots and remove the orphan files from the table.

ALTER TABLE iceberg_table SET TBLPROPERTIES ( 'vacuum_max_snapshot_age_seconds'='259200' ) VACUUM iceberg_table