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Caution
Azure Synapse Runtime for Apache Spark 3.4 reached end of support on March 31, 2026. Although existing workloads may continue to run for a limited period beyond this date, the runtime is no longer supported and no longer receives bug fixes, security updates, or vulnerability remediations. As a result, workloads running on Spark 3.4 are exposed to increasing operational and security risks over time.
In addition, the phased disablement of Spark 3.4 jobs will begin shortly, and there is no guarantee that Spark 3.4 workloads will continue to run in the future. To minimize disruption and remain on a supported platform, We strongly recommend you upgrade your Apache Spark 3.4 based workloads to Azure Synapse Runtime for Apache Spark 3.5 (GA) as soon as possible.
Azure Synapse Analytics supports multiple runtimes for Apache Spark. This document covers the runtime components and versions for the Azure Synapse Runtime for Apache Spark 3.4.
Component versions
| Component | Version |
|---|---|
| Apache Spark | 3.4.1 |
| Operating System | Mariner 2.0 |
| Java | 11 |
| Scala | 2.12.17 |
| Delta Lake | 2.4.0 |
| Python | 3.10 |
| R | 4.2.2 |
Tip
For up-to-date information, a detailed list of changes, and specific release notes for Spark runtimes, check and subscribe Spark Runtimes Releases and Updates.
Libraries
To check the libraries included in Azure Synapse Runtime for Apache Spark 3.4 for Java/Scala, Python and R go to Azure Synapse Runtime for Apache Spark 3.4 Releases Notes.
Tip
spark.memoryOverheadFactor.preferred: If set to true, Spark will prioritize spark.driver.memoryOverheadFactor and spark.executor.memoryOverheadFactor over the explicit values defined by spark.driver.memoryOverhead and spark.executor.memoryOverhead. When enabled, the overhead is always computed using the factor, and the explicit overhead settings are ignored. The default is false for backward compatibility.