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06-08-2025 11:44 PM - edited 06-08-2025 11:45 PM
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:
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?
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06-17-2025 04:50 AM
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.
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10-02-2025 03:21 PM
@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.