Optimize & Compaction

[thushar]

Hi,

From which data bricks runtime will support Optimize and compaction

[Debayan]

Hi, DBR 9.1 LTS and above. Please refer: https://docs.databricks.com/optimizations/auto-optimize.html#enable-auto-optimize

Please let us know if this helps. 

Also, please tag @Debayan​ with your next response which will notify me. Thank you!

[thushar]

Thanks, only SQL version will support this feature in 9.1 LTS, PySpark scripts are availbe or not ?

[-werners-]

yes, as the optimize is set in spark config options, this is language agnostic.

[Anonymous]

Hi @Thushar R​ 

Hope all is well! Just wanted to check in if you were able to resolve your issue and would you be happy to share the solution or mark an answer as best? Else please let us know if you need more help. 

We'd love to hear from you.

Thanks!

[Joe_Suarez]

Optimize and compaction are operations commonly used in Apache Spark for optimizing and improving the performance of data storage and processing. Databricks, which is a cloud-based platform for Apache Spark, provides support for these operations on various runtime versions.

Here are some runtime versions in Databricks that support optimize and compaction:

1. Databricks Runtime 7.2 and later versions: Databricks Runtime 7.2 introduced a new feature called Delta Lake Auto Optimize, which enables automatic optimization and compaction of Delta Lake tables based on a set of predefined rules. This feature is available in all later versions of Databricks Runtime as well.
2. Databricks Runtime 6.4 and later versions: Databricks Runtime 6.4 introduced the OPTIMIZE command for Delta Lake tables, which enables manual optimization and compaction of Delta Lake tables.
3. Earlier runtime versions: Optimize and compaction are not available in earlier versions of Databricks Runtime. If you're using an earlier version, you can consider upgrading to a later version to take advantage of these features.