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databricks Platform · Updated Aug 25, 2025

Automatic liquid clustering is now available for Lakeflow Spark Declarative…

You can now use automatic liquid clustering with Lakeflow Spark Declarative Pipelines.

GA Open docs ↗release note ↗
What it does

You can now use automatic liquid clustering with Lakeflow Spark Declarative Pipelines. Use automatic liquid clustering with CLUSTER BY AUTO, and Databricks intelligently chooses clustering keys to optimize query performance. A streaming table is a table with support for streaming or incremental data processing.

Why it matters

Use automatic liquid clustering with CLUSTER BY AUTO, and Databricks intelligently chooses clustering keys to optimize query performance.

Key capabilities
They are not added to
They are not added to the catalog and are only accessible within the defining pipeline
They can have the same
They can have the same name as an existing object in the catalog. Within the pipeline, if a private streaming table and an…
Private streaming tables are only
Private streaming tables are only persisted across the lifetime of the pipeline, not just a single update.
column\identifier
column\identifier
Recommended use cases
DEFAULT default\expression
Limitations · remember
!PARTITIONED BY an identity column
!UPDATE an identity column
Architecture
Databricks Platform → Platform
In short

You can now use automatic liquid clustering with Lakeflow Spark Declarative Pipelines. Use automatic liquid clustering with CLUSTER BY AUTO, and Databricks intelligently chooses clustering keys to optimize query performance.

Read the full documentation ↗
Key takeaway
You can now use automatic liquid clustering with Lakeflow Spark Declarative Pipelines.
2025-08-25-b6cf5dc4 Generated by the Databricks Updates Agent · browse all updates