使用flink 1.10版本的flinkSQL 做UNbound流多表join时 遇到了内存溢出的问

你好我自使用flink 1.10版本的flinkSQL 做UNbound流多表join时 遇到了内存溢出的问题？有几个疑问想咨询下;

1,关于使用rocksdb 我的设置是在代码中指定如下 env.setStateBackend(new RocksDBStateBackend("hdfs://beh/user/dc_cbss/flink5/checkpoints" , true).getCheckpointBackend());

但是我在jobmanager启动日志中看到如下info Using application-defined state backend: File State Backend (checkpoints: 'hdfs://beh/user/dc_cbss/flink5/checkpoints', savepoints: 'null', asynchronous: UNDEFINED, fileStateThreshold: -1) 这是不是意味着rocksdb设置失败？

我任务从检查点恢复是日志显示：感觉也是fsstatebackend?

java.lang.OutOfMemoryError: GC overhead limit exceeded at org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy(DFSInputStream.java:831) at org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:889) at org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:696) at java.io.FilterInputStream.read(FilterInputStream.java:83) at org.apache.flink.runtime.fs.hdfs.HadoopDataInputStream.read(HadoopDataInputStream.java:84) at org.apache.flink.core.fs.FSDataInputStreamWrapper.read(FSDataInputStreamWrapper.java:51) at org.apache.flink.runtime.util.ForwardingInputStream.read(ForwardingInputStream.java:41) at java.io.DataInputStream.readInt(DataInputStream.java:389) at org.apache.flink.api.common.typeutils.base.ListSerializer.deserialize(ListSerializer.java:129) at org.apache.flink.api.common.typeutils.base.ListSerializer.deserialize(ListSerializer.java:42) at org.apache.flink.api.common.typeutils.base.MapSerializer.deserialize(MapSerializer.java:151) at org.apache.flink.api.common.typeutils.base.MapSerializer.deserialize(MapSerializer.java:43) at org.apache.flink.runtime.state.heap.StateTableByKeyGroupReaders.lambda$createV2PlusReader$0(StateTableByKeyGroupReaders.java:77) at org.apache.flink.runtime.state.heap.StateTableByKeyGroupReaders$$Lambda$163/413838894.readElement(Unknown Source) at org.apache.flink.runtime.state.KeyGroupPartitioner$PartitioningResultKeyGroupReader.readMappingsInKeyGroup(KeyGroupPartitioner.java:297) at org.apache.flink.runtime.state.heap.HeapRestoreOperation.readKeyGroupStateData(HeapRestoreOperation.java:293) at org.apache.flink.runtime.state.heap.HeapRestoreOperation.readStateHandleStateData(HeapRestoreOperation.java:254) at org.apache.flink.runtime.state.heap.HeapRestoreOperation.restore(HeapRestoreOperation.java:153) at org.apache.flink.runtime.state.heap.HeapKeyedStateBackendBuilder.build(HeapKeyedStateBackendBuilder.java:114) at org.apache.flink.runtime.state.filesystem.FsStateBackend.createKeyedStateBackend(FsStateBackend.java:529) at org.apache.flink.streaming.api.operators.StreamTaskStateInitializerImpl.lambda$keyedStatedBackend$1(StreamTaskStateInitializerImpl.java:288) at org.apache.flink.streaming.api.operators.StreamTaskStateInitializerImpl$$Lambda$138/1902710867.apply(Unknown Source) at org.apache.flink.streaming.api.operators.BackendRestorerProcedure.attemptCreateAndRestore(BackendRestorerProcedure.java:142) at org.apache.flink.streaming.api.operators.BackendRestorerProcedure.createAndRestore(BackendRestorerProcedure.java:121) at org.apache.flink.streaming.api.operators.StreamTaskStateInitializerImpl.keyedStatedBackend(StreamTaskStateInitializerImpl.java:304) at org.apache.flink.streaming.api.operators.StreamTaskStateInitializerImpl.streamOperatorStateContext(StreamTaskStateInitializerImpl.java:131) at org.apache.flink.streaming.api.operators.AbstractStreamOperator.initializeState(AbstractStreamOperator.java:255) at org.apache.flink.streaming.runtime.tasks.StreamTask.initializeStateAndOpen(StreamTask.java:1006) at org.apache.flink.streaming.runtime.tasks.StreamTask.lambda$beforeInvoke$0(StreamTask.java:454) at org.apache.flink.streaming.runtime.tasks.StreamTask$$Lambda$132/1758917910.run(Unknown Source) at org.apache.flink.streaming.runtime.tasks.StreamTaskActionExecutor$SynchronizedStreamTaskActionExecutor.runThrowing(StreamTaskActionExecutor.java:94) at org.apache.flink.streaming.runtime.tasks.StreamTask.beforeInvoke(StreamTask.java:449) [flink-akka.actor.default-dispatcher-20] INFO org.apache.flink.runtime.executiongraph.failover.flip1.RestartPipelinedRegionStrat

所以我不知道 backend是否正确指定

2.我的任务设置过期时间为24小时，当状态超过1g后会出现内存溢出，日志如上；就是gc时间太频繁；想知道实际生产大家是怎么做的；我给的内存远超1g 每个taskmanager内存8G， jobmanager.heap.size: 2048m taskmanager.memory.process.size: 8192m taskmanager.memory.managed.size: 2048m 希望给与帮助，

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