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Update CHANGELOG
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docs/changelog/0.3.0.rst

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0.3.0 (2025-12-16)
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0.3.0 (2025-12-18)
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==================
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Release of Data.SyncMaster 0.3.0 brings up support for Iceberg, Spark-on-K8s and Spark-on-Yarn.

docs/reference/worker/create_spark_session.rst

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SyncMaster Worker creates `SparkSession <https://spark.apache.org/docs/latest/sql-getting-started.html#starting-point-sparksession>`_ for each Run.
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By default, SparkSession is created with ``master=local``, including all required .jar packages for DB/FileSystem types, and limited by transfer resources.
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By default, SparkSession is created with ``spark.master: local``, including all required .jar packages for DB/FileSystem types, and limited by transfer resources.
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Custom Spark session configuration
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spark.sql.pyspark.jvmStacktrace.enabled: true
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spark.ui.enabled: false
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For example, to use SyncMaster on Spark + Kubernetes, you can use worker image for Spark executor containers:
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For example, to use SyncMaster on Spark-on-K8s, you can use worker image for Spark executor containers:
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.. code-block:: yaml
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:caption: config.yml
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spark.sql.pyspark.jvmStacktrace.enabled: true
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spark.kubernetes.container.image: mtsrus/syncmaster-worker:{TAG}
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.. note::
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Currently Spark-on-K8s and Spark-on-Yarn do not support interaction FTP, FTPS, SFTP, Samba and WebDAV.
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This requires ``sparm.master: local``.
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Custom Spark session factory
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return SparkSession.builde.config(...).getOrCreate()
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Module with custom function should be placed into the same Docker image or Python virtual environment used by SyncMaster worker.
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.. note::
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For now, SyncMaster haven't been tested with ``master=k8s`` and ``master=yarn``, so there can be some caveats.

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