VACUUM
Clean up files associated with a table.
Note
This command works differently depending on whether you’re working on a Delta or Apache Spark table.
Vacuum a Delta table (Delta Lake on Databricks)
Recursively vacuum directories associated with the Delta table and remove data files that are no longer in the latest state of the transaction log for the table and are older than a retention threshold. Files are deleted according to the time they have been logically removed from Delta’s transaction log + retention hours, not their modification timestamps on the storage system. The default threshold is 7 days.
On Delta tables, Databricks does not automatically trigger VACUUM operations. See Remove files no longer referenced by a Delta table.
If you run VACUUM on a Delta table, you lose the ability time travel back to a
version older than the specified data retention period.
Warning
Databricks recommends that you set a retention interval to be at least 7 days,
because old snapshots and uncommitted files can still be in use by concurrent
readers or writers to the table. If VACUUM cleans up active files,
concurrent readers can fail or, worse, tables can be corrupted when VACUUM
deletes files that have not yet been committed. You must choose an interval
that is longer than the longest running concurrent transaction and the longest
period that any stream can lag behind the most recent update to the table.
Delta Lake has a safety check to prevent you from running a dangerous VACUUM
command. If you are certain that there are no operations being performed on
this table that take longer than the retention interval you plan to specify,
you can turn off this safety check by setting the Spark configuration property
spark.databricks.delta.retentionDurationCheck.enabled to false.
VACUUM table_name [RETAIN num HOURS] [DRY RUN]
Parameters
-
Identifies an existing Delta table. The name must not include a temporal specification.
RETAIN num HOURS
The retention threshold.
DRY RUN
Return a list of files to be deleted.
Vacuum a Spark table (Apache Spark)
Recursively vacuums directories associated with the Spark table and remove uncommitted files older than a retention threshold. The default threshold is 7 days.
On Spark tables, Databricks automatically triggers VACUUM
operations as data is written. See Clean up uncommitted files.