[SPARK-45814][CONNECT][SQL]Make ArrowConverters.createEmptyArrowBatch call close() to avoid memory leak #43691
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xieshuaihu
changed the title
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cc @sunchao , too |
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hmm... a little strange to call super.hasNext in next. How about make |
added 2 commits
November 8, 2023 09:41
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@LuciferYang This pr is updated, please review again |
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the PR title/description should be updated |
LuciferYang
reviewed
Nov 8, 2023
| Iterator.empty, schema, 0L, 0L, | ||
| timeZoneId, errorOnDuplicatedFieldNames, TaskContext.get()) { | ||
| override def hasNext: Boolean = true | ||
| }.next() | ||
| } | ||
| val emptyBatch = batches.next() |
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Utils.tryWithSafeFinally {
batches.next()
} {
if (TaskContext.get() == null) { // If taskContext is not null, it can be successfully closed, right?
batches.close()
}
}
xieshuaihu
changed the title
LuciferYang
approved these changes
Nov 8, 2023
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It seems like that this test failure is unrelated to this pr |
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Could re-trigger the failed one? make all tasks green is safer @xieshuaihu |
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@LuciferYang all ut passed |
LuciferYang
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that referenced
this pull request
Nov 9, 2023
…h call close() to avoid memory leak ### What changes were proposed in this pull request? Make `ArrowBatchIterator` implement `AutoCloseable` and `ArrowConverters.createEmptyArrowBatch()` call close() to avoid memory leak. ### Why are the changes needed? `ArrowConverters.createEmptyArrowBatch` don't call `super.hasNext`, if `TaskContext.get` returns `None`, then memory allocated in `ArrowBatchIterator` is leaked. In spark connect, `createEmptyArrowBatch` is called in [SparkConnectPlanner](https://github.com/apache/spark/blob/master/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala#L2558) and [SparkConnectPlanExecution](https://github.com/apache/spark/blob/master/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/execution/SparkConnectPlanExecution.scala#L224), which cause a long running driver consume all off-heap memory specified by `-XX:MaxDirectMemorySize`. This is the exception stack: ``` org.apache.arrow.memory.OutOfMemoryException: Failure allocating buffer. at io.netty.buffer.PooledByteBufAllocatorL.allocate(PooledByteBufAllocatorL.java:67) at org.apache.arrow.memory.NettyAllocationManager.<init>(NettyAllocationManager.java:77) at org.apache.arrow.memory.NettyAllocationManager.<init>(NettyAllocationManager.java:84) at org.apache.arrow.memory.NettyAllocationManager$1.create(NettyAllocationManager.java:34) at org.apache.arrow.memory.BaseAllocator.newAllocationManager(BaseAllocator.java:354) at org.apache.arrow.memory.BaseAllocator.newAllocationManager(BaseAllocator.java:349) at org.apache.arrow.memory.BaseAllocator.bufferWithoutReservation(BaseAllocator.java:337) at org.apache.arrow.memory.BaseAllocator.buffer(BaseAllocator.java:315) at org.apache.arrow.memory.BaseAllocator.buffer(BaseAllocator.java:279) at org.apache.arrow.vector.BaseValueVector.allocFixedDataAndValidityBufs(BaseValueVector.java:192) at org.apache.arrow.vector.BaseFixedWidthVector.allocateBytes(BaseFixedWidthVector.java:338) at org.apache.arrow.vector.BaseFixedWidthVector.allocateNew(BaseFixedWidthVector.java:308) at org.apache.arrow.vector.BaseFixedWidthVector.allocateNew(BaseFixedWidthVector.java:273) at org.apache.spark.sql.execution.arrow.ArrowWriter$.$anonfun$create$1(ArrowWriter.scala:44) at scala.collection.StrictOptimizedIterableOps.map(StrictOptimizedIterableOps.scala:100) at scala.collection.StrictOptimizedIterableOps.map$(StrictOptimizedIterableOps.scala:87) at scala.collection.convert.JavaCollectionWrappers$JListWrapper.map(JavaCollectionWrappers.scala:103) at org.apache.spark.sql.execution.arrow.ArrowWriter$.create(ArrowWriter.scala:43) at org.apache.spark.sql.execution.arrow.ArrowConverters$ArrowBatchIterator.<init>(ArrowConverters.scala:93) at org.apache.spark.sql.execution.arrow.ArrowConverters$ArrowBatchWithSchemaIterator.<init>(ArrowConverters.scala:138) at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$1.<init>(ArrowConverters.scala:231) at org.apache.spark.sql.execution.arrow.ArrowConverters$.createEmptyArrowBatch(ArrowConverters.scala:229) at org.apache.spark.sql.connect.planner.SparkConnectPlanner.handleSqlCommand(SparkConnectPlanner.scala:2481) at org.apache.spark.sql.connect.planner.SparkConnectPlanner.process(SparkConnectPlanner.scala:2426) at org.apache.spark.sql.connect.execution.ExecuteThreadRunner.handleCommand(ExecuteThreadRunner.scala:202) at org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1(ExecuteThreadRunner.scala:158) at org.apache.spark.sql.connect.execution.ExecuteThreadRunner.$anonfun$executeInternal$1$adapted(ExecuteThreadRunner.scala:132) at org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$2(SessionHolder.scala:189) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900) at org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withSession$1(SessionHolder.scala:189) at org.apache.spark.JobArtifactSet$.withActiveJobArtifactState(JobArtifactSet.scala:94) at org.apache.spark.sql.connect.service.SessionHolder.$anonfun$withContextClassLoader$1(SessionHolder.scala:176) at org.apache.spark.util.Utils$.withContextClassLoader(Utils.scala:178) at org.apache.spark.sql.connect.service.SessionHolder.withContextClassLoader(SessionHolder.scala:175) at org.apache.spark.sql.connect.service.SessionHolder.withSession(SessionHolder.scala:188) at org.apache.spark.sql.connect.execution.ExecuteThreadRunner.executeInternal(ExecuteThreadRunner.scala:132) at org.apache.spark.sql.connect.execution.ExecuteThreadRunner.org$apache$spark$sql$connect$execution$ExecuteThreadRunner$$execute(ExecuteThreadRunner.scala:84) at org.apache.spark.sql.connect.execution.ExecuteThreadRunner$ExecutionThread.run(ExecuteThreadRunner.scala:228) Caused by: io.netty.util.internal.OutOfDirectMemoryError: failed to allocate 4194304 byte(s) of direct memory (used: 1069547799, max: 1073741824) at io.netty.util.internal.PlatformDependent.incrementMemoryCounter(PlatformDependent.java:845) at io.netty.util.internal.PlatformDependent.allocateDirectNoCleaner(PlatformDependent.java:774) at io.netty.buffer.PoolArena$DirectArena.allocateDirect(PoolArena.java:721) at io.netty.buffer.PoolArena$DirectArena.newChunk(PoolArena.java:696) at io.netty.buffer.PoolArena.allocateNormal(PoolArena.java:215) at io.netty.buffer.PoolArena.tcacheAllocateSmall(PoolArena.java:180) at io.netty.buffer.PoolArena.allocate(PoolArena.java:137) at io.netty.buffer.PoolArena.allocate(PoolArena.java:129) at io.netty.buffer.PooledByteBufAllocatorL$InnerAllocator.newDirectBufferL(PooledByteBufAllocatorL.java:181) at io.netty.buffer.PooledByteBufAllocatorL$InnerAllocator.directBuffer(PooledByteBufAllocatorL.java:214) at io.netty.buffer.PooledByteBufAllocatorL.allocate(PooledByteBufAllocatorL.java:58) ... 37 more ``` ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Manually test ### Was this patch authored or co-authored using generative AI tooling? No Closes #43691 from xieshuaihu/spark-45814. Authored-by: xieshuaihu <xieshuaihu@agora.io> Signed-off-by: yangjie01 <yangjie01@baidu.com> (cherry picked from commit c128f81) Signed-off-by: yangjie01 <yangjie01@baidu.com>
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Merged into master and branch-3.5. Thanks @xieshuaihu @hvanhovell @dongjoon-hyun @cfmcgrady This patch conflicts with branch-3.4. Could you submit a separate pr for branch-3.4? @xieshuaihu |
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I will submit a new pr @LuciferYang |
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Thanks @xieshuaihu ~ |
HyukjinKwon
reviewed
Dec 20, 2023
| } { | ||
| // If taskContext is null, `batches.close()` should be called to avoid memory leak. | ||
| if (TaskContext.get() == null) { | ||
| batches.close() |
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Can we actually add a small test for this? This memory leaking should be easy to test if the close is actually being invoked with createEmptyArrowBatch.
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What changes were proposed in this pull request?
Make
ArrowBatchIteratorimplementAutoCloseableandArrowConverters.createEmptyArrowBatch()call close() to avoid memory leak.Why are the changes needed?
ArrowConverters.createEmptyArrowBatchdon't callsuper.hasNext, ifTaskContext.getreturnsNone, then memory allocated inArrowBatchIteratoris leaked.In spark connect,
createEmptyArrowBatchis called in SparkConnectPlanner and SparkConnectPlanExecution, which cause a long running driver consume all off-heap memory specified by-XX:MaxDirectMemorySize.This is the exception stack:
Does this PR introduce any user-facing change?
No
How was this patch tested?
Manually test
Was this patch authored or co-authored using generative AI tooling?
No