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* Revamped loading assemblies used inside UDFs ([#180](https://github.com/dotnet/spark/pull/180))
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* Support for Vector UDFs ([#127](https://github.com/dotnet/spark/pull/127))
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* Support for Grouped Map UDFs ([#143](https://github.com/dotnet/spark/pull/143))
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* Resolve the signer mismatch issue ([#186](https://github.com/dotnet/spark/pull/186))
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* Ability to launch a debugger from the worker ([#150](https://github.com/dotnet/spark/pull/150))
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* Compatibility check for Microsoft.Spark.dll in the worker ([#170](https://github.com/dotnet/spark/pull/170))
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* Update Apache.Arrow to v0.14.1 ([#167](https://github.com/dotnet/spark/pull/167))
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* Support for RuntimeConfig in SparkSession ([#184](https://github.com/dotnet/spark/pull/184))
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* Support for `Trigger` in `DataStreamWriter` ([#153](https://github.com/dotnet/spark/pull/153))
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* The ability to use `--archives` option to deploy the worker binaries and assemblies that UDFs depend on ([#187](https://github.com/dotnet/spark/pull/187))
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### Breaking Changes
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* Due to the changes in loading assemblies ([#180](https://github.com/dotnet/spark/pull/180)), the Microsoft.Spark.Worker executable is no longer compatible with the previous versions.
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* The `--class org.apache.spark.deploy.DotnetRunner` option in `spark-submit` is changed to **`--class org.apache.spark.deploy.dotnet.DotnetRunner`** to resolve the signer mismatch issue ([#186](https://github.com/dotnet/spark/pull/186)).
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### Supported Spark Versions
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The following table outlines the supported Spark versions along with the microsoft-spark JAR to use with:
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