Note
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Caution
Azure Synapse Runtime for Apache Spark 3.4 was deprecated, with support ending on March 31, 2026. While it may continue to run for a limited period beyond this date, it is no longer supported and does not receive bug fixes, security updates, or vulnerability patches. If you do not upgrade, workloads running on Azure Synapse Runtime for Apache Spark 3.4 will continue to operate on an unsupported runtime. This increases both operational and security risks, as the runtime will no longer receive critical fixes or updates. We strongly recommend you upgrade your Apache Spark 3.4 based workloads to Azure Synapse Runtime for Apache Spark 3.5 (GA).
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.