xuanyuanking opened a new pull request #26164: [SPARK-21492][SQL] Fix memory leak in SortMergeJoin URL: https://github.com/apache/spark/pull/26164 ### What changes were proposed in this pull request? We shall have a new mechanism that the downstream operators may notify its parents that they may release the output data stream. In this PR, we implement the mechanism as below: - Add function named `cleanupResources` in SparkPlan, which default call children's `cleanupResources` function, the operator which need a resource cleanup should rewrite this with the self cleanup and also call `super.cleanupResources`, like SortExec in this PR. - Add logic support on the trigger side, in this PR is SortMergeJoinExec, which make sure and call the `cleanupResources` to do the cleanup job for all its upstream(children) operator. - Add a conf `spark.sql.sortMergeJoinExec.eagerCleanupResources` to control this behavior for safety, default value is true. ### Why are the changes needed? Bugfix for SortMergeJoin memory leak, and implement a general framework for SparkPlan resource cleanup. ### Does this PR introduce any user-facing change? No. ### How was this patch tested? UT: Add new test suite JoinWithResourceCleanSuite to check both standard and code generation scenario. Integrate Test: Test with driver/executor default memory set 1g, local mode 10 thread. Set `spark.sql.sortMergeJoinExec.eagerCleanupResources=fasle` the below test(thanks @taosaildrone for providing this test [here](https://github.com/apache/spark/pull/23762#issuecomment-463303175)) will fail by OOM, while open the conf it'll pass. ``` from pyspark.sql.functions import rand, col spark.conf.set("spark.sql.join.preferSortMergeJoin", "true") spark.conf.set("spark.sql.autoBroadcastJoinThreshold", -1) # spark.conf.set("spark.sql.sortMergeJoinExec.eagerCleanupResources", "true") r1 = spark.range(1, 1001).select(col("id").alias("timestamp1")) r1 = r1.withColumn('value', rand()) r2 = spark.range(1000, 1001).select(col("id").alias("timestamp2")) r2 = r2.withColumn('value2', rand()) joined = r1.join(r2, r1.timestamp1 == r2.timestamp2, "inner") joined = joined.coalesce(1) joined.explain() joined.show() ```
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