Upgrade to Azure Synapse runtimes for Apache Spark 3.4 & previous runtimes deprecation
It is important to stay ahead of the curve and keep services up to date. That's why we encourage all Azure Synapse customers with Apache Spark workloads to migrate to the newest GA version, Azure Synapse Runtime for Apache Spark 3.4. The update brings Apache Spark to version 3.4 and Delta Lake to version 2.4, introduces Mariner as the new operating system, and updates Java from version 8 to 11.
Within a few days/weeks, we are disabling Apache Spark 2.4, 3.1, 3.2 job execution. If you are affected you have already been notified. Using the runtime after EOS date is at one's own risk, and with the agreement and acceptance of the risks that jobs will eventually stop executing. All support tickets will be auto-resolved. Learn more about the Microsoft Lifecycle Policy.
Migrate to the latest GA version of Azure Synapse runtimes for Apache Spark 3.4 before the deprecation and disablement of previous versions.
Please refer to the following article for more information on the lifecycle and supportability of our runtimes: Azure Synapse runtimes.
Go to Synapse runtime for Apache Spark lifecycle and supportability - Azure Synapse Analytics | Microsoft Learn and Migration Guide: Spark Core - Spark 3.4.1 Documentation (apache.org) for more details on how to migrate and how to change Apache Spark-based runtime in Azure Synapse Analytics.
Published on:
Learn moreRelated posts
We're moving!
We’re moving to the Analytics on Azure Tech Community! All new Azure Synapse Analytics content will be published there. In the next few days a...
Interpreting Script activity output json with Azure Data Factory\Synapse analytics
Script activity in Azure Data Factory\ Synapse analytics is very helpful to run queries against data sources mentioned here in this document.&...
ADF\Synapse Analytics - Replace Columns names using Rule based mapping in Mapping data flows
In real time, the column names from source might not be uniform, some columns will have a space in it, some other columns will not. For exampl...
Synapse Connectivity Series Part #4 - Advanced network troubleshooting and network trace analysis
Continuing the series of this blog posts I would like to go more advanced on troubleshooting connectivity issues. I would like to thank also&n...
Boost your CICD automation for Synapse SQL Serverless by taking advantage of SSDT and SqlPackage CLI
Introduction Azure Synapse Analytics Serverless SQL is a query service mostly used over the data in your data lake, for data discovery,...
Metadata-Based Ingestion in Synapse with Delta Lake
Overview The crucial first step in any ETL (extract, transform, load) process or data engineering program is ingestion, w...
Missing Fields Added to Dedicated SQL pool Diagnostic Settings Logs
Over the past year, customers have informed the team there were a set of key columns missing in the standalone Dedicated SQL pools (formerly S...
Using Azure DevOps with Synapse Workspaces to create hot fixes in production environments
Have you ever deployed a release to production only to find out a bug has escaped your testing process and now users are being severely impact...
Azure Synapse MVP Corner - March 2023
About this blog series Microsoft Most Valuable Professionals, or MVPs, are technology experts who passionately share their knowledge with the ...
CI & CD With Azure Synapse Dedicated SQL Pool
Author(s): Pradeep Srikakolapu is a Program Manager in Azure Synapse Customer Success Engineering (CSE) team. Automating de...