Transactional writes to cloud storage with DBIO

The Databricks DBIO package provides transactional writes to cloud storage for Apache Spark jobs. This solves a number of performance and correctness issues that occur when Spark is used in a cloud-native setting (for example, writing directly to storage services).

With DBIO transactional commit, metadata files starting with _started_<id> and _committed_<id> accompany data files created by Spark jobs. Generally you shouldn’t alter these files directly. Rather, you should use the VACUUM command to clean them up.

Clean up uncommitted files

To clean up uncommitted files left over from Spark jobs, use the VACUUM command to remove them. Normally VACUUM happens automatically after Spark jobs complete, but you can also run it manually if a job is aborted.

For example, VACUUM ... RETAIN 1 HOUR removes uncommitted files older than one hour.

Important

  • Avoid vacuuming with a horizon of less than one hour. It can cause data inconsistency.

Also see Vacuum.

-- recursively vacuum an output path
VACUUM '/path/to/output/directory' [RETAIN <N> HOURS]

-- vacuum all partitions of a catalog table
VACUUM tableName [RETAIN <N> HOURS]
// recursively vacuum an output path
spark.sql("VACUUM '/path/to/output/directory' [RETAIN <N> HOURS]")

// vacuum all partitions of a catalog table
spark.sql("VACUUM tableName [RETAIN <N> HOURS]")