ChangeFeed Spark Bug Processing All Partitions #42553
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/azp run java - cosmos - tests |
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API change check APIView has identified API level changes in this PR and created following API reviews. |
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...re-cosmos-spark_3_2-12/src/main/scala/com/azure/cosmos/spark/ChangeFeedPartitionReader.scala
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...re-cosmos-spark_3_2-12/src/main/scala/com/azure/cosmos/spark/ChangeFeedPartitionReader.scala
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sdk/cosmos/azure-cosmos/src/main/java/com/azure/cosmos/BridgeInternal.java
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xinlian12
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Oct 25, 2024
...re-cosmos-spark_3_2-12/src/main/scala/com/azure/cosmos/spark/ChangeFeedPartitionReader.scala
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/azp run java - cosmos - spark |
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…to tvaron3/changeFeedSparkBug
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xinlian12
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Nov 20, 2024
...smos-spark_3_2-12/src/test/scala/com/azure/cosmos/spark/ChangeFeedPartitionReaderITest.scala
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…to tvaron3/changeFeedSparkBug
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Description
In our spark connector, all cosmos partitions should be processed up to a precalculated lsn in most cases using streaming mode. When a spark partition is being processed and a split happens, there is a chance that a child partition is not fully drained because spark will keep grabbing changes into an endLSN but has no knowledge of the split.
Implementation
Spark will set a request option for continuing the changefeed until an endLSN and the java sdk will keep returning changes up to the endLSN. If there is a 304 it will continue reading because the endLSN is always calculated with a known lsn. The 304 would happen if there is a delay in change feed.