DBR 16.4 LTS - Spark 3.5.2 is not compatible with Delta Lake 3.3.1

leireroman
New Contributor III

I'm migrating to Databricks Runtime 16.4 LTS, which is using Spark 3.5.2 and Delta Lake 3.3.1 according to the documentation: Databricks Runtime 16.4 LTS - Azure Databricks | Microsoft Learn

I've upgraded my conda environment to use those versions, but I get this error message when I try to upgrade my environment:

Captura de pantalla 2025-06-09 084355.png

According to Delta Lake releases (Releases · delta-io/delta), the last version compatible with Spark 3.5.2 is 3.2.0, because the next one (3.2.1) is built on Spark 3.5.3.

Is Databricks really using Delta Lake version 3.3.1? How can I check this from a cluster with DBR 16.4 LTS?

Renu_
Valued Contributor II

Hi @leireroman, Databricks Runtime 16.4 LTS includes Delta Lake 3.3.1, paired with Spark 3.5.2. This combination works within Databricks because it’s a custom build. In your Conda environment, the conflict occurs because delta-spark 3.3.1 requires pyspark >=3.5.3, but you’ve set it to 3.5.2.

To resolve this, you can either:

  • Upgrade pyspark to 3.5.3 to work with delta-spark 3.3.1
  • Downgrade to delta-spark 3.2.0 to stay compatible with Spark 3.5.2.

View solution in original post

SamAdams
Contributor

@leireroman encountered the same and used an override (like a pip constraints.txt file or PDM resolution override specification) to make sure my local development environment matched the runtime.