Re: Flink 1.10 内存问题
最后我发现问题的根源是双流JOIN没设置TTL。双流JOIN task的 OutputBuffer会被打满。然后Flink就处于假死状态了。不再消费任何数据。 Ada Luna 于2021年7月19日周一 下午7:06写道： > > 异步IO的Order队列打满，导致算子卡死？ > > Ada Luna 于2021年7月19日周一 下午2:02写道： > > > > 我通过反压信息观察到，这个 async wait operator > > 算子上游全部出现严重反压。很有可能是这个算子死锁或者死循环等类似问题。但是我还不知道如何进一步排查。 > > > > "async wait operator -> (where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, > > 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, ITEM, VAL, UNIT, > > DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, currtime2(DATATIME, > > _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 AS ISFILL, 1 AS > > STATE, 0E0 AS P5) -> to: Tuple2, where: (=(CASE(>(ABS(Z), > > WaterRoseMax_5), 1, 0), 1)), select: (STID, DATATIME, _UTF-16LE'2' AS > > DATATYPE, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS > > VALTIME, _UTF-16LE'' AS CORTIME, VAL AS CORBERVAL, _UTF-16LE'' AS > > CORAFTVAL, _UTF-16LE'' AS CORNAME, _UTF-16LE'' AS CORPHONE, 0 AS > > STATE, 0 AS ISFILL, 1 AS TYPE) -> to: Tuple2, where: (=(CASE(>(ABS(Z), > > WaterRoseMax_5), 1, 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, > > ITEM, VAL, UNIT, DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, > > currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 > > AS ISFILL, 1 AS STATE, 0E0 AS P5) -> to: Tuple2) (2/2)" #82 prio=5 > > os_prio=0 tid=0x7fd4c4ac5000 nid=0x21c3 in Object.wait() > > [0x7fd4d5416000] > > java.lang.Thread.State: WAITING (on object monitor) > > at java.lang.Object.wait(Native Method) > > at java.lang.Object.wait(Object.java:502) > > at > > org.apache.flink.streaming.api.operators.async.AsyncWaitOperator.addAsyncBufferEntry(AsyncWaitOperator.java:403) > > at > > org.apache.flink.streaming.api.operators.async.AsyncWaitOperator.processElement(AsyncWaitOperator.java:224) > > at > > org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:202) > > - locked <0x00074cb5b3a0> (a java.lang.Object) > > at > > org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:105) > > at > > org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) > > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) > > at java.lang.Thread.run(Thread.java:748) > > > > "async wait operator -> (where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, > > 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, ITEM, VAL, UNIT, > > DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, currtime2(DATATIME, > > _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 AS ISFILL, 1 AS > > STATE, 0E0 AS P5) -> to: Tuple2, where: (=(CASE(>(ABS(Z), > > WaterRoseMax_5), 1, 0), 1)), select: (STID, DATATIME, _UTF-16LE'2' AS > > DATATYPE, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS > > VALTIME, _UTF-16LE'' AS CORTIME, VAL AS CORBERVAL, _UTF-16LE'' AS > > CORAFTVAL, _UTF-16LE'' AS CORNAME, _UTF-16LE'' AS CORPHONE, 0 AS > > STATE, 0 AS ISFILL, 1 AS TYPE) -> to: Tuple2, where: (=(CASE(>(ABS(Z), > > WaterRoseMax_5), 1, 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, > > ITEM, VAL, UNIT, DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, > > currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 > > AS ISFILL, 1 AS STATE, 0E0 AS P5) -> to: Tuple2) (1/2)" #81 prio=5 > > os_prio=0 tid=0x7fd4c4ac3000 nid=0x21c2 in Object.wait() > > [0x7fd4d5517000] > > java.lang.Thread.State: WAITING (on object monitor) > > at java.lang.Object.wait(Native Method) > > at java.lang.Object.wait(Object.java:502) > > at > > org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate.getNextBufferOrEvent(SingleInputGate.java:539) > > - locked <0x00074cb5d560> (a java.util.ArrayDeque) > > at > > org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate.getNextBufferOrEvent(SingleInputGate.java:508) > > at > > org.apache.flink.streaming.runtime.io.BarrierBuffer.getNextNonBlocked(BarrierBuffer.java:165) > > at > > org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:209) > > at > > org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:105) > > at > > org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) > > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) > > at java.lang.Thread.run(Thread.java:748) > > > > Yun Tang 于2021年7月6日周二 下午4:01写道： > > > > > > Hi, > > > > > > 有可能的，如果下游发生了死锁，无法消费任何数据的话，整个作业就假死了。要定位ro
Re: Flink 1.10 内存问题
异步IO的Order队列打满，导致算子卡死？ Ada Luna 于2021年7月19日周一 下午2:02写道： > > 我通过反压信息观察到，这个 async wait operator > 算子上游全部出现严重反压。很有可能是这个算子死锁或者死循环等类似问题。但是我还不知道如何进一步排查。 > > "async wait operator -> (where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, > 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, ITEM, VAL, UNIT, > DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, currtime2(DATATIME, > _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 AS ISFILL, 1 AS > STATE, 0E0 AS P5) -> to: Tuple2, where: (=(CASE(>(ABS(Z), > WaterRoseMax_5), 1, 0), 1)), select: (STID, DATATIME, _UTF-16LE'2' AS > DATATYPE, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS > VALTIME, _UTF-16LE'' AS CORTIME, VAL AS CORBERVAL, _UTF-16LE'' AS > CORAFTVAL, _UTF-16LE'' AS CORNAME, _UTF-16LE'' AS CORPHONE, 0 AS > STATE, 0 AS ISFILL, 1 AS TYPE) -> to: Tuple2, where: (=(CASE(>(ABS(Z), > WaterRoseMax_5), 1, 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, > ITEM, VAL, UNIT, DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, > currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 > AS ISFILL, 1 AS STATE, 0E0 AS P5) -> to: Tuple2) (2/2)" #82 prio=5 > os_prio=0 tid=0x7fd4c4ac5000 nid=0x21c3 in Object.wait() > [0x7fd4d5416000] > java.lang.Thread.State: WAITING (on object monitor) > at java.lang.Object.wait(Native Method) > at java.lang.Object.wait(Object.java:502) > at > org.apache.flink.streaming.api.operators.async.AsyncWaitOperator.addAsyncBufferEntry(AsyncWaitOperator.java:403) > at > org.apache.flink.streaming.api.operators.async.AsyncWaitOperator.processElement(AsyncWaitOperator.java:224) > at > org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:202) > - locked <0x00074cb5b3a0> (a java.lang.Object) > at > org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:105) > at > org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) > at java.lang.Thread.run(Thread.java:748) > > "async wait operator -> (where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, > 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, ITEM, VAL, UNIT, > DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, currtime2(DATATIME, > _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 AS ISFILL, 1 AS > STATE, 0E0 AS P5) -> to: Tuple2, where: (=(CASE(>(ABS(Z), > WaterRoseMax_5), 1, 0), 1)), select: (STID, DATATIME, _UTF-16LE'2' AS > DATATYPE, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS > VALTIME, _UTF-16LE'' AS CORTIME, VAL AS CORBERVAL, _UTF-16LE'' AS > CORAFTVAL, _UTF-16LE'' AS CORNAME, _UTF-16LE'' AS CORPHONE, 0 AS > STATE, 0 AS ISFILL, 1 AS TYPE) -> to: Tuple2, where: (=(CASE(>(ABS(Z), > WaterRoseMax_5), 1, 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, > ITEM, VAL, UNIT, DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, > currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 > AS ISFILL, 1 AS STATE, 0E0 AS P5) -> to: Tuple2) (1/2)" #81 prio=5 > os_prio=0 tid=0x7fd4c4ac3000 nid=0x21c2 in Object.wait() > [0x7fd4d5517000] > java.lang.Thread.State: WAITING (on object monitor) > at java.lang.Object.wait(Native Method) > at java.lang.Object.wait(Object.java:502) > at > org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate.getNextBufferOrEvent(SingleInputGate.java:539) > - locked <0x00074cb5d560> (a java.util.ArrayDeque) > at > org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate.getNextBufferOrEvent(SingleInputGate.java:508) > at > org.apache.flink.streaming.runtime.io.BarrierBuffer.getNextNonBlocked(BarrierBuffer.java:165) > at > org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:209) > at > org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:105) > at > org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) > at java.lang.Thread.run(Thread.java:748) > > Yun Tang 于2021年7月6日周二 下午4:01写道： > > > > Hi, > > > > 有可能的，如果下游发生了死锁，无法消费任何数据的话，整个作业就假死了。要定位root cause还是需要查一下下游的task究竟怎么了 > > > > 祝好 > > 唐云 > > > > From: Ada Luna > > Sent: Tuesday, July 6, 2021 12:04 > > To: user-zh@flink.apache.org > > Subject: Re: Flink 1.10 内存问题 > > > > 反压会导致整个Flink任务假死吗？一条Kafka数据都不消费了。持续几天，不重启不恢复的 > > > > Yun Tang 于2021年7月6日周二 上午11:12写道： > > > > > > Hi, > > > > > > LocalBufferPool.requestMemorySegment > > > 这个方法并不是在申请内存，而是因为作业存在反压，因为下游没有及时消费，相关buffer被占用，所以上游
Re: Flink 1.10 内存问题
我通过反压信息观察到，这个 async wait operator 算子上游全部出现严重反压。很有可能是这个算子死锁或者死循环等类似问题。但是我还不知道如何进一步排查。 "async wait operator -> (where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, ITEM, VAL, UNIT, DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 AS ISFILL, 1 AS STATE, 0E0 AS P5) -> to: Tuple2, where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, 0), 1)), select: (STID, DATATIME, _UTF-16LE'2' AS DATATYPE, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS VALTIME, _UTF-16LE'' AS CORTIME, VAL AS CORBERVAL, _UTF-16LE'' AS CORAFTVAL, _UTF-16LE'' AS CORNAME, _UTF-16LE'' AS CORPHONE, 0 AS STATE, 0 AS ISFILL, 1 AS TYPE) -> to: Tuple2, where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, ITEM, VAL, UNIT, DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 AS ISFILL, 1 AS STATE, 0E0 AS P5) -> to: Tuple2) (2/2)" #82 prio=5 os_prio=0 tid=0x7fd4c4ac5000 nid=0x21c3 in Object.wait() [0x7fd4d5416000] java.lang.Thread.State: WAITING (on object monitor) at java.lang.Object.wait(Native Method) at java.lang.Object.wait(Object.java:502) at org.apache.flink.streaming.api.operators.async.AsyncWaitOperator.addAsyncBufferEntry(AsyncWaitOperator.java:403) at org.apache.flink.streaming.api.operators.async.AsyncWaitOperator.processElement(AsyncWaitOperator.java:224) at org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:202) - locked <0x00074cb5b3a0> (a java.lang.Object) at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:105) at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) at java.lang.Thread.run(Thread.java:748) "async wait operator -> (where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, ITEM, VAL, UNIT, DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 AS ISFILL, 1 AS STATE, 0E0 AS P5) -> to: Tuple2, where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, 0), 1)), select: (STID, DATATIME, _UTF-16LE'2' AS DATATYPE, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS VALTIME, _UTF-16LE'' AS CORTIME, VAL AS CORBERVAL, _UTF-16LE'' AS CORAFTVAL, _UTF-16LE'' AS CORNAME, _UTF-16LE'' AS CORPHONE, 0 AS STATE, 0 AS ISFILL, 1 AS TYPE) -> to: Tuple2, where: (=(CASE(>(ABS(Z), WaterRoseMax_5), 1, 0), 0)), select: (ID, STID, _UTF-16LE'' AS STCD, ITEM, VAL, UNIT, DATATIME AS DT, _UTF-16LE'2.6' AS DATAINDEX, currtime2(DATATIME, _UTF-16LE'-MM-dd HH:mm:ss') AS CREATETIME, 0 AS ISFILL, 1 AS STATE, 0E0 AS P5) -> to: Tuple2) (1/2)" #81 prio=5 os_prio=0 tid=0x7fd4c4ac3000 nid=0x21c2 in Object.wait() [0x7fd4d5517000] java.lang.Thread.State: WAITING (on object monitor) at java.lang.Object.wait(Native Method) at java.lang.Object.wait(Object.java:502) at org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate.getNextBufferOrEvent(SingleInputGate.java:539) - locked <0x00074cb5d560> (a java.util.ArrayDeque) at org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate.getNextBufferOrEvent(SingleInputGate.java:508) at org.apache.flink.streaming.runtime.io.BarrierBuffer.getNextNonBlocked(BarrierBuffer.java:165) at org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:209) at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:105) at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) at java.lang.Thread.run(Thread.java:748) Yun Tang 于2021年7月6日周二 下午4:01写道： > > Hi, > > 有可能的，如果下游发生了死锁，无法消费任何数据的话，整个作业就假死了。要定位root cause还是需要查一下下游的task究竟怎么了 > > 祝好 > 唐云 > > From: Ada Luna > Sent: Tuesday, July 6, 2021 12:04 > To: user-zh@flink.apache.org > Subject: Re: Flink 1.10 内存问题 > > 反压会导致整个Flink任务假死吗？一条Kafka数据都不消费了。持续几天，不重启不恢复的 > > Yun Tang 于2021年7月6日周二 上午11:12写道： > > > > Hi, > > > > LocalBufferPool.requestMemorySegment > > 这个方法并不是在申请内存，而是因为作业存在反压，因为下游没有及时消费，相关buffer被占用，所以上游会卡在requestMemorySegment上面。 > > > > 想要解决还是查一下为什么下游会反压。 > > > > > > 祝好 > > 唐云 > > > > From: Ada Luna > > Sent: Tuesday, July 6, 2021 10:43 > > To: user-zh@flink.apache.org > > Subject: Re: Flink 1.10 内存问题 > > > > "Source: test_records (2/3)" #78 prio=5 os_prio=0 > > tid=0x7fd4c4a24800 nid=0x21bf in Object.wait() > > [0x7fd4d581a000] > > java.lang.Thread.St
Re: Flink 1.10 内存问题
Hi, 有可能的，如果下游发生了死锁，无法消费任何数据的话，整个作业就假死了。要定位root cause还是需要查一下下游的task究竟怎么了 祝好 唐云 From: Ada Luna Sent: Tuesday, July 6, 2021 12:04 To: user-zh@flink.apache.org Subject: Re: Flink 1.10 内存问题 反压会导致整个Flink任务假死吗？一条Kafka数据都不消费了。持续几天，不重启不恢复的 Yun Tang 于2021年7月6日周二 上午11:12写道： > > Hi, > > LocalBufferPool.requestMemorySegment > 这个方法并不是在申请内存，而是因为作业存在反压，因为下游没有及时消费，相关buffer被占用，所以上游会卡在requestMemorySegment上面。 > > 想要解决还是查一下为什么下游会反压。 > > > 祝好 > 唐云 > > From: Ada Luna > Sent: Tuesday, July 6, 2021 10:43 > To: user-zh@flink.apache.org > Subject: Re: Flink 1.10 内存问题 > > "Source: test_records (2/3)" #78 prio=5 os_prio=0 > tid=0x7fd4c4a24800 nid=0x21bf in Object.wait() > [0x7fd4d581a000] > java.lang.Thread.State: TIMED_WAITING (on object monitor) > at java.lang.Object.wait(Native Method) > at > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestMemorySegment(LocalBufferPool.java:251) > - locked <0x00074d8b0df0> (a java.util.ArrayDeque) > at > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestBufferBuilderBlocking(LocalBufferPool.java:218) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.requestNewBufferBuilder(RecordWriter.java:264) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.copyFromSerializerToTargetChannel(RecordWriter.java:192) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:162) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:128) > at > org.apache.flink.streaming.runtime.io.RecordWriterOutput.pushToRecordWriter(RecordWriterOutput.java:107) > at > org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:89) > at > org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:45) > at > org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718) > at > org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696) > at > org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collect(StreamSourceContexts.java:104) > - locked <0x00074cbd3be0> (a java.lang.Object) > at > org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collectWithTimestamp(StreamSourceContexts.java:111) > at > org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordWithTimestamp(AbstractFetcher.java:398) > - locked <0x00074cbd3be0> (a java.lang.Object) > at > org.apache.flink.streaming.connectors.kafka.internal.Kafka010Fetcher.emitRecord(Kafka010Fetcher.java:91) > at > org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:156) > at > org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:711) > at > com.dtstack.flink.sql.source.kafka.KafkaConsumer011.run(KafkaConsumer011.java:66) > at > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:93) > at > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:57) > at > org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:97) > at > org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) > at java.lang.Thread.run(Thread.java:748) > > Ada Luna 于2021年7月6日周二 上午10:13写道： > > > > 下面报错调大TaskManager内存即可解决，但是我不知道为什么Flink内存不够大会出现如下假死情况。申请内存卡住。整个任务状态为RUNNING但是不再消费数据。 > > > > > > > > "Map -> to: Tuple2 -> Map -> (from: (id, sid, item, val, unit, dt, > > after_index, tablename, PROCTIME) -> where: (AND(=(tablename, > > CONCAT(_UTF-16LE't_real', currtime2(dt, _UTF-16LE'MMdd'))), > > OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, _UTF-16LE'7296'), > > =(after_index, _UTF-16LE'2.10'))), LIKE(item, _UTF-16LE'??5%'), > > =(MOD(getminutes(dt), 5), 0))), select: (id AS ID, sid AS STID, item > > AS ITEM, val AS VAL, unit AS UNIT, dt AS DATATIME), from: (id, sid, > > item, val, unit, dt, after_index, tablename, PROCTIME) -> where: > > (AND(=(tablename, CONCAT(_UTF-16LE't_real', currtime2(dt, > > _UTF-16LE'MMdd'))), OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, > > _UTF-16LE'7296'), =(after_index, _UTF-16LE'2.10'))), LIKE(item, > > _UTF-16LE'??5%'), =(MOD(getminutes(dt), 5), 0))), select: (sid AS > > STID, val AS VAL, dt AS DATATIME)) (1/1)" #7
Re: Flink 1.10 内存问题
Mark.这个问题我也遇到过，不清楚为啥。我也很奇怪，之前我的任务经常这样，反压到直接停滞，CPU使用率也会降低。 按照正常的理解，反压时候压力高，CPU使用率应该高。 而我的情况是反压到整个任务停滞，导致CPU使用率就很低很低了。 Ada Luna 于2021年7月6日周二 下午12:05写道： > > 反压会导致整个Flink任务假死吗？一条Kafka数据都不消费了。持续几天，不重启不恢复的 > > Yun Tang 于2021年7月6日周二 上午11:12写道： > > > > Hi, > > > > LocalBufferPool.requestMemorySegment > > 这个方法并不是在申请内存，而是因为作业存在反压，因为下游没有及时消费，相关buffer被占用，所以上游会卡在requestMemorySegment上面。 > > > > 想要解决还是查一下为什么下游会反压。 > > > > > > 祝好 > > 唐云 > > > > From: Ada Luna > > Sent: Tuesday, July 6, 2021 10:43 > > To: user-zh@flink.apache.org > > Subject: Re: Flink 1.10 内存问题 > > > > "Source: test_records (2/3)" #78 prio=5 os_prio=0 > > tid=0x7fd4c4a24800 nid=0x21bf in Object.wait() > > [0x7fd4d581a000] > > java.lang.Thread.State: TIMED_WAITING (on object monitor) > > at java.lang.Object.wait(Native Method) > > at > > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestMemorySegment(LocalBufferPool.java:251) > > - locked <0x00074d8b0df0> (a java.util.ArrayDeque) > > at > > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestBufferBuilderBlocking(LocalBufferPool.java:218) > > at > > org.apache.flink.runtime.io.network.api.writer.RecordWriter.requestNewBufferBuilder(RecordWriter.java:264) > > at > > org.apache.flink.runtime.io.network.api.writer.RecordWriter.copyFromSerializerToTargetChannel(RecordWriter.java:192) > > at > > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:162) > > at > > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:128) > > at > > org.apache.flink.streaming.runtime.io.RecordWriterOutput.pushToRecordWriter(RecordWriterOutput.java:107) > > at > > org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:89) > > at > > org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:45) > > at > > org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718) > > at > > org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696) > > at > > org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collect(StreamSourceContexts.java:104) > > - locked <0x00074cbd3be0> (a java.lang.Object) > > at > > org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collectWithTimestamp(StreamSourceContexts.java:111) > > at > > org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordWithTimestamp(AbstractFetcher.java:398) > > - locked <0x00074cbd3be0> (a java.lang.Object) > > at > > org.apache.flink.streaming.connectors.kafka.internal.Kafka010Fetcher.emitRecord(Kafka010Fetcher.java:91) > > at > > org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:156) > > at > > org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:711) > > at > > com.dtstack.flink.sql.source.kafka.KafkaConsumer011.run(KafkaConsumer011.java:66) > > at > > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:93) > > at > > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:57) > > at > > org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:97) > > at > > org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) > > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) > > at java.lang.Thread.run(Thread.java:748) > > > > Ada Luna 于2021年7月6日周二 上午10:13写道： > > > > > > 下面报错调大TaskManager内存即可解决，但是我不知道为什么Flink内存不够大会出现如下假死情况。申请内存卡住。整个任务状态为RUNNING但是不再消费数据。 > > > > > > > > > > > > "Map -> to: Tuple2 -> Map -> (from: (id, sid, item, val, unit, dt, > > > after_index, tablename, PROCTIME) -> where: (AND(=(tablename, > > > CONCAT(_UTF-16LE't_real', currtime2(dt, _UTF-16LE'MMdd'))), > > > OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, _UTF-16LE'7296'), > > > =(after_index, _UTF-16LE'2.10'))), LIKE(item, _UTF-16LE'??5%'), > > > =(MOD(getminutes(dt), 5), 0))), select: (id AS ID, sid AS STID, item > > > AS ITEM, val AS VAL, unit AS UNIT, dt AS DATATIME), from: (id, sid, > > &
Re: Flink 1.10 内存问题
反压会导致整个Flink任务假死吗？一条Kafka数据都不消费了。持续几天，不重启不恢复的 Yun Tang 于2021年7月6日周二 上午11:12写道： > > Hi, > > LocalBufferPool.requestMemorySegment > 这个方法并不是在申请内存，而是因为作业存在反压，因为下游没有及时消费，相关buffer被占用，所以上游会卡在requestMemorySegment上面。 > > 想要解决还是查一下为什么下游会反压。 > > > 祝好 > 唐云 > > From: Ada Luna > Sent: Tuesday, July 6, 2021 10:43 > To: user-zh@flink.apache.org > Subject: Re: Flink 1.10 内存问题 > > "Source: test_records (2/3)" #78 prio=5 os_prio=0 > tid=0x7fd4c4a24800 nid=0x21bf in Object.wait() > [0x7fd4d581a000] > java.lang.Thread.State: TIMED_WAITING (on object monitor) > at java.lang.Object.wait(Native Method) > at > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestMemorySegment(LocalBufferPool.java:251) > - locked <0x00074d8b0df0> (a java.util.ArrayDeque) > at > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestBufferBuilderBlocking(LocalBufferPool.java:218) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.requestNewBufferBuilder(RecordWriter.java:264) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.copyFromSerializerToTargetChannel(RecordWriter.java:192) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:162) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:128) > at > org.apache.flink.streaming.runtime.io.RecordWriterOutput.pushToRecordWriter(RecordWriterOutput.java:107) > at > org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:89) > at > org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:45) > at > org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718) > at > org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696) > at > org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collect(StreamSourceContexts.java:104) > - locked <0x00074cbd3be0> (a java.lang.Object) > at > org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collectWithTimestamp(StreamSourceContexts.java:111) > at > org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordWithTimestamp(AbstractFetcher.java:398) > - locked <0x00074cbd3be0> (a java.lang.Object) > at > org.apache.flink.streaming.connectors.kafka.internal.Kafka010Fetcher.emitRecord(Kafka010Fetcher.java:91) > at > org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:156) > at > org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:711) > at > com.dtstack.flink.sql.source.kafka.KafkaConsumer011.run(KafkaConsumer011.java:66) > at > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:93) > at > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:57) > at > org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:97) > at > org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) > at java.lang.Thread.run(Thread.java:748) > > Ada Luna 于2021年7月6日周二 上午10:13写道： > > > > 下面报错调大TaskManager内存即可解决，但是我不知道为什么Flink内存不够大会出现如下假死情况。申请内存卡住。整个任务状态为RUNNING但是不再消费数据。 > > > > > > > > "Map -> to: Tuple2 -> Map -> (from: (id, sid, item, val, unit, dt, > > after_index, tablename, PROCTIME) -> where: (AND(=(tablename, > > CONCAT(_UTF-16LE't_real', currtime2(dt, _UTF-16LE'MMdd'))), > > OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, _UTF-16LE'7296'), > > =(after_index, _UTF-16LE'2.10'))), LIKE(item, _UTF-16LE'??5%'), > > =(MOD(getminutes(dt), 5), 0))), select: (id AS ID, sid AS STID, item > > AS ITEM, val AS VAL, unit AS UNIT, dt AS DATATIME), from: (id, sid, > > item, val, unit, dt, after_index, tablename, PROCTIME) -> where: > > (AND(=(tablename, CONCAT(_UTF-16LE't_real', currtime2(dt, > > _UTF-16LE'MMdd'))), OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, > > _UTF-16LE'7296'), =(after_index, _UTF-16LE'2.10'))), LIKE(item, > > _UTF-16LE'??5%'), =(MOD(getminutes(dt), 5), 0))), select: (sid AS > > STID, val AS VAL, dt AS DATATIME)) (1/1)" #79 prio=5 os_prio=0 > > tid=0x7fd4c4a94000 nid=0x21c0 in Object.wait() > > [0x7fd4d5719000] > > java.lang.Thread.State: TIMED_WAITING (on object monitor) > > at java.lang.Object.wait(Native Method) > > at &g
Re: Flink 1.10 内存问题
Hi, LocalBufferPool.requestMemorySegment 这个方法并不是在申请内存，而是因为作业存在反压，因为下游没有及时消费，相关buffer被占用，所以上游会卡在requestMemorySegment上面。 想要解决还是查一下为什么下游会反压。 祝好 唐云 From: Ada Luna Sent: Tuesday, July 6, 2021 10:43 To: user-zh@flink.apache.org Subject: Re: Flink 1.10 内存问题 "Source: test_records (2/3)" #78 prio=5 os_prio=0 tid=0x7fd4c4a24800 nid=0x21bf in Object.wait() [0x7fd4d581a000] java.lang.Thread.State: TIMED_WAITING (on object monitor) at java.lang.Object.wait(Native Method) at org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestMemorySegment(LocalBufferPool.java:251) - locked <0x00074d8b0df0> (a java.util.ArrayDeque) at org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestBufferBuilderBlocking(LocalBufferPool.java:218) at org.apache.flink.runtime.io.network.api.writer.RecordWriter.requestNewBufferBuilder(RecordWriter.java:264) at org.apache.flink.runtime.io.network.api.writer.RecordWriter.copyFromSerializerToTargetChannel(RecordWriter.java:192) at org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:162) at org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:128) at org.apache.flink.streaming.runtime.io.RecordWriterOutput.pushToRecordWriter(RecordWriterOutput.java:107) at org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:89) at org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:45) at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718) at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696) at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collect(StreamSourceContexts.java:104) - locked <0x00074cbd3be0> (a java.lang.Object) at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collectWithTimestamp(StreamSourceContexts.java:111) at org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordWithTimestamp(AbstractFetcher.java:398) - locked <0x00074cbd3be0> (a java.lang.Object) at org.apache.flink.streaming.connectors.kafka.internal.Kafka010Fetcher.emitRecord(Kafka010Fetcher.java:91) at org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:156) at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:711) at com.dtstack.flink.sql.source.kafka.KafkaConsumer011.run(KafkaConsumer011.java:66) at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:93) at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:57) at org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:97) at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) at java.lang.Thread.run(Thread.java:748) Ada Luna 于2021年7月6日周二 上午10:13写道： > > 下面报错调大TaskManager内存即可解决，但是我不知道为什么Flink内存不够大会出现如下假死情况。申请内存卡住。整个任务状态为RUNNING但是不再消费数据。 > > > > "Map -> to: Tuple2 -> Map -> (from: (id, sid, item, val, unit, dt, > after_index, tablename, PROCTIME) -> where: (AND(=(tablename, > CONCAT(_UTF-16LE't_real', currtime2(dt, _UTF-16LE'MMdd'))), > OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, _UTF-16LE'7296'), > =(after_index, _UTF-16LE'2.10'))), LIKE(item, _UTF-16LE'??5%'), > =(MOD(getminutes(dt), 5), 0))), select: (id AS ID, sid AS STID, item > AS ITEM, val AS VAL, unit AS UNIT, dt AS DATATIME), from: (id, sid, > item, val, unit, dt, after_index, tablename, PROCTIME) -> where: > (AND(=(tablename, CONCAT(_UTF-16LE't_real', currtime2(dt, > _UTF-16LE'MMdd'))), OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, > _UTF-16LE'7296'), =(after_index, _UTF-16LE'2.10'))), LIKE(item, > _UTF-16LE'??5%'), =(MOD(getminutes(dt), 5), 0))), select: (sid AS > STID, val AS VAL, dt AS DATATIME)) (1/1)" #79 prio=5 os_prio=0 > tid=0x7fd4c4a94000 nid=0x21c0 in Object.wait() > [0x7fd4d5719000] > java.lang.Thread.State: TIMED_WAITING (on object monitor) > at java.lang.Object.wait(Native Method) > at > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestMemorySegment(LocalBufferPool.java:251) > - locked <0x00074e6c8b98> (a java.util.ArrayDeque) > at > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestBufferBuilderBlocking(LocalBufferPool.java:218) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.requestNewBufferBuilder(RecordWriter.java:264) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.copyFromSerializerToTargetChannel(RecordWriter.java:192) > at > or
Re: Flink 1.10 内存问题
"Source: test_records (2/3)" #78 prio=5 os_prio=0 tid=0x7fd4c4a24800 nid=0x21bf in Object.wait() [0x7fd4d581a000] java.lang.Thread.State: TIMED_WAITING (on object monitor) at java.lang.Object.wait(Native Method) at org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestMemorySegment(LocalBufferPool.java:251) - locked <0x00074d8b0df0> (a java.util.ArrayDeque) at org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestBufferBuilderBlocking(LocalBufferPool.java:218) at org.apache.flink.runtime.io.network.api.writer.RecordWriter.requestNewBufferBuilder(RecordWriter.java:264) at org.apache.flink.runtime.io.network.api.writer.RecordWriter.copyFromSerializerToTargetChannel(RecordWriter.java:192) at org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:162) at org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:128) at org.apache.flink.streaming.runtime.io.RecordWriterOutput.pushToRecordWriter(RecordWriterOutput.java:107) at org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:89) at org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:45) at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718) at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696) at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collect(StreamSourceContexts.java:104) - locked <0x00074cbd3be0> (a java.lang.Object) at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collectWithTimestamp(StreamSourceContexts.java:111) at org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordWithTimestamp(AbstractFetcher.java:398) - locked <0x00074cbd3be0> (a java.lang.Object) at org.apache.flink.streaming.connectors.kafka.internal.Kafka010Fetcher.emitRecord(Kafka010Fetcher.java:91) at org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:156) at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:711) at com.dtstack.flink.sql.source.kafka.KafkaConsumer011.run(KafkaConsumer011.java:66) at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:93) at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:57) at org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:97) at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:302) at org.apache.flink.runtime.taskmanager.Task.run(Task.java:711) at java.lang.Thread.run(Thread.java:748) Ada Luna 于2021年7月6日周二 上午10:13写道： > > 下面报错调大TaskManager内存即可解决，但是我不知道为什么Flink内存不够大会出现如下假死情况。申请内存卡住。整个任务状态为RUNNING但是不再消费数据。 > > > > "Map -> to: Tuple2 -> Map -> (from: (id, sid, item, val, unit, dt, > after_index, tablename, PROCTIME) -> where: (AND(=(tablename, > CONCAT(_UTF-16LE't_real', currtime2(dt, _UTF-16LE'MMdd'))), > OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, _UTF-16LE'7296'), > =(after_index, _UTF-16LE'2.10'))), LIKE(item, _UTF-16LE'??5%'), > =(MOD(getminutes(dt), 5), 0))), select: (id AS ID, sid AS STID, item > AS ITEM, val AS VAL, unit AS UNIT, dt AS DATATIME), from: (id, sid, > item, val, unit, dt, after_index, tablename, PROCTIME) -> where: > (AND(=(tablename, CONCAT(_UTF-16LE't_real', currtime2(dt, > _UTF-16LE'MMdd'))), OR(=(after_index, _UTF-16LE'2.6'), AND(=(sid, > _UTF-16LE'7296'), =(after_index, _UTF-16LE'2.10'))), LIKE(item, > _UTF-16LE'??5%'), =(MOD(getminutes(dt), 5), 0))), select: (sid AS > STID, val AS VAL, dt AS DATATIME)) (1/1)" #79 prio=5 os_prio=0 > tid=0x7fd4c4a94000 nid=0x21c0 in Object.wait() > [0x7fd4d5719000] > java.lang.Thread.State: TIMED_WAITING (on object monitor) > at java.lang.Object.wait(Native Method) > at > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestMemorySegment(LocalBufferPool.java:251) > - locked <0x00074e6c8b98> (a java.util.ArrayDeque) > at > org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestBufferBuilderBlocking(LocalBufferPool.java:218) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.requestNewBufferBuilder(RecordWriter.java:264) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.copyFromSerializerToTargetChannel(RecordWriter.java:192) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:162) > at > org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:128) > at > org.apache.flink.streaming.runtime.io.RecordWriterOutput.pushToRecordWriter(RecordWriterOutput.java:107) > at > org.apache.flink.streaming.runtime.io.RecordWriterOutput.collect(RecordWriterOutput.java:89) > at >
