使用Flink时遇到的问题（不断更新中）

1.启动不起来

查看JobManager日志：

WARN  org.apache.flink.runtime.webmonitor.JobManagerRetriever       - Failed to retrieve leader gateway and port.
akka.actor.ActorNotFound: Actor not found for: ActorSelection[Anchor(akka.tcp://flink@t-sha1-flk-01:6123/), Path(/user/jobmanager)]
at akka.actor.ActorSelection$$anonfun$resolveOne$1.apply(ActorSelection.scala:65)
at akka.actor.ActorSelection$$anonfun$resolveOne$1.apply(ActorSelection.scala:63)
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
at akka.dispatch.BatchingExecutor$AbstractBatch.processBatch(BatchingExecutor.scala:55)
at akka.dispatch.BatchingExecutor$Batch.run(BatchingExecutor.scala:73)
at akka.dispatch.ExecutionContexts$sameThreadExecutionContext$.unbatchedExecute(Future.scala:74)
at akka.dispatch.BatchingExecutor$class.execute(BatchingExecutor.scala:120)
at akka.dispatch.ExecutionContexts$sameThreadExecutionContext$.execute(Future.scala:73)
at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40)
at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248)
at akka.pattern.PromiseActorRef$$anonfun$1.apply$mcV$sp(AskSupport.scala:334)
at akka.actor.Scheduler$$anon$7.run(Scheduler.scala:117)
at scala.concurrent.Future$InternalCallbackExecutor$.unbatchedExecute(Future.scala:599)
at scala.concurrent.BatchingExecutor$class.execute(BatchingExecutor.scala:109)
at scala.concurrent.Future$InternalCallbackExecutor$.execute(Future.scala:597)
at akka.actor.LightArrayRevolverScheduler$TaskHolder.executeTask(Scheduler.scala:474)
at akka.actor.LightArrayRevolverScheduler$$anon$8.executeBucket$1(Scheduler.scala:425)
at akka.actor.LightArrayRevolverScheduler$$anon$8.nextTick(Scheduler.scala:429)
at akka.actor.LightArrayRevolverScheduler$$anon$8.run(Scheduler.scala:381)
at java.lang.Thread.run(Thread.java:748)

解决方案：/etc/hosts中配置的主机名都是小写，但是在Flink配置文件（flink-config.yaml、masters、slaves）中配置的都是大写的hostname，将flink配置文件中的hostname都改为小写或者IP地址

2.运行一段时间退出

AsynchronousException{java.lang.Exception: Could not materialize checkpoint 4 for operator Compute By Event Time (1/12).}
at org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.run(StreamTask.java:970)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.Exception: Could not materialize checkpoint 4 for operator Compute By Event Time (1/12).
... 6 more
Caused by: java.util.concurrent.ExecutionException: java.io.IOException: Size of the state is larger than the maximum permitted memory-backed state. Size=7061809 , maxSize=5242880 . Consider using a different state backend, like the File System State backend.
at java.util.concurrent.FutureTask.report(FutureTask.java:122)
at java.util.concurrent.FutureTask.get(FutureTask.java:192)
at org.apache.flink.util.FutureUtil.runIfNotDoneAndGet(FutureUtil.java:43)
at org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.run(StreamTask.java:897)
... 5 more
Suppressed: java.lang.Exception: Could not properly cancel managed keyed state future.
at org.apache.flink.streaming.api.operators.OperatorSnapshotResult.cancel(OperatorSnapshotResult.java:90)
at org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.cleanup(StreamTask.java:1023)
at org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.run(StreamTask.java:961)
... 5 more
Caused by: java.util.concurrent.ExecutionException: java.io.IOException: Size of the state is larger than the maximum permitted memory-backed state. Size=7061809 , maxSize=5242880 . Consider using a different state backend, like the File System State backend.
at java.util.concurrent.FutureTask.report(FutureTask.java:122)
at java.util.concurrent.FutureTask.get(FutureTask.java:192)
at org.apache.flink.util.FutureUtil.runIfNotDoneAndGet(FutureUtil.java:43)
at org.apache.flink.runtime.state.StateUtil.discardStateFuture(StateUtil.java:85)
at org.apache.flink.streaming.api.operators.OperatorSnapshotResult.cancel(OperatorSnapshotResult.java:88)
... 7 more
Caused by: java.io.IOException: Size of the state is larger than the maximum permitted memory-backed state. Size=7061809 , maxSize=5242880 . Consider using a different state backend, like the File System State backend.
at org.apache.flink.runtime.state.memory.MemCheckpointStreamFactory.checkSize(MemCheckpointStreamFactory.java:64)
at org.apache.flink.runtime.state.memory.MemCheckpointStreamFactory$MemoryCheckpointOutputStream.closeAndGetBytes(MemCheckpointStreamFactory.java:144)
at org.apache.flink.runtime.state.memory.MemCheckpointStreamFactory$MemoryCheckpointOutputStream.closeAndGetHandle(MemCheckpointStreamFactory.java:125)
at org.apache.flink.runtime.checkpoint.AbstractAsyncSnapshotIOCallable.closeStreamAndGetStateHandle(AbstractAsyncSnapshotIOCallable.java:100)
at org.apache.flink.runtime.state.heap.HeapKeyedStateBackend$1.performOperation(HeapKeyedStateBackend.java:351)
at org.apache.flink.runtime.state.heap.HeapKeyedStateBackend$1.performOperation(HeapKeyedStateBackend.java:329)
at org.apache.flink.runtime.io.async.AbstractAsyncIOCallable.call(AbstractAsyncIOCallable.java:72)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at org.apache.flink.runtime.state.heap.HeapKeyedStateBackend.snapshot(HeapKeyedStateBackend.java:372)
at org.apache.flink.streaming.api.operators.AbstractStreamOperator.snapshotState(AbstractStreamOperator.java:397)
at org.apache.flink.streaming.runtime.tasks.StreamTask$CheckpointingOperation.checkpointStreamOperator(StreamTask.java:1162)
at org.apache.flink.streaming.runtime.tasks.StreamTask$CheckpointingOperation.executeCheckpointing(StreamTask.java:1094)
at org.apache.flink.streaming.runtime.tasks.StreamTask.checkpointState(StreamTask.java:654)
at org.apache.flink.streaming.runtime.tasks.StreamTask.performCheckpoint(StreamTask.java:590)
at org.apache.flink.streaming.runtime.tasks.StreamTask.triggerCheckpointOnBarrier(StreamTask.java:543)
at org.apache.flink.streaming.runtime.io.BarrierBuffer.notifyCheckpoint(BarrierBuffer.java:378)
at org.apache.flink.streaming.runtime.io.BarrierBuffer.processBarrier(BarrierBuffer.java:281)
at org.apache.flink.streaming.runtime.io.BarrierBuffer.getNextNonBlocked(BarrierBuffer.java:183)
at org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:213)
at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:69)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:263)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702)
... 1 more
[CIRCULAR REFERENCE:java.io.IOException: Size of the state is larger than the maximum permitted memory-backed state. Size=7061809 , maxSize=5242880 . Consider using a different state backend, like the File System State backend.]

解决方案：

状态存储，默认是在内存中，改为存储到HDFS中：

state.backend.fs.checkpointdir: hdfs://t-sha1-flk-01:9000/flink-checkpoints

3.长时间运行后，多次重启

WARN  org.apache.hadoop.hdfs.DFSClient
- DataStreamer Exception
org.apache.hadoop.ipc.RemoteException(java.io.IOException):
File /flink-checkpoints/8c7bff5382a5158b7279bbe5de075c77/chk-238/30357bf3-807b-4458-9e19-e86fa101dbd1
could only be replicated to 0 nodes instead of minReplication (=1).
There are 3 datanode(s) running and no node(s) are excluded in this operation.
at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1571)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getNewBlockTargets(FSNamesystem.java:3107)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3031)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:725)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:492)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:616)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:982)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2049)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2045)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2043)

at org.apache.hadoop.ipc.Client.call(Client.java:1475)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy12.addBlock(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:418)
at sun.reflect.GeneratedMethodAccessor22.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy13.addBlock(Unknown Source)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:1459)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1255)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:449)

解决方案：曾经两次格式化过Namenode，查询了网上的一些文章，虽然异常大致一样，但是每个datanode是正常启动并运行正常，此外namenode中有namespaceID，从节点Datanode中并没有namespaceID，查询到的资料有：

老外的建议：https://stackoverflow.com/questions/5293446/hdfs-error-could-only-be-replicated-to-0-nodes-instead-of-1

stop all hadoop services
delete dfs/name and dfs/data directories
hadoop namenode -format # Answer with a capital Y
start hadoop services

百度到的建议：http://blog.sina.com.cn/s/blog_4c248c5801014nd1.html

第一种方法是删除DataNode的所有资料（及将集群中每个datanode的/hdfs/data/current中的VERSION删掉，然后执行hadoop namenode -format重启集群，错误消失。<推荐>）；

第二种方法是修改每个DataNode的namespaceID（位于/hdfs/data/current/VERSION文件中）<优先>或修改NameNode的namespaceID（位于/hdfs/name/current/VERSION文件中），使其一致。

因为运行时间不长，为了能彻底解决问题，采用了方法一。

4.Unable to load native-hadoop library for your platform

Flink启动时，有时会有如下警告信息：

WARN  org.apache.hadoop.util.NativeCodeLoader

- Unable to load native-hadoop library for your platform...

using builtin-java classes where applicable

参考资料1：http://blog.csdn.net/jack85986370/article/details/51902871

解决方案：编辑/etc/profile文件，增加

export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native

export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib"

未能解决该问题

5.hadoop checknative -a

WARN bzip2.Bzip2Factory: Failed to load/initialize native-bzip2 library system-native, will use pure-Java version
INFO zlib.ZlibFactory: Successfully loaded & initialized native-zlib library
Native library checking:
hadoop:  true /usr/hadoop-2.7.3/lib/native/libhadoop.so.1.0.0
zlib:    true /lib64/libz.so.1
snappy:  false
lz4:     true revision:99
bzip2:   false
openssl: false Cannot load libcrypto.so (libcrypto.so: cannot open shared object file: No such file or directory)!
INFO util.ExitUtil: Exiting with status 1

参考资料：http://blog.csdn.net/zhangzhaokun/article/details/50951238

解决方案

cd /usr/lib64/
ln -s libcrypto.so.1.0.1e libcrypto.so

6.TaskManager退出

Flink运行一段时间后，出现TaskManager退出情况，通过jvisualvm抓取TaskManager的Dump，使用MAT进行分析，结果如下：

One instance of "org.apache.flink.runtime.io.network.buffer.NetworkBufferPool"
loaded by "sun.misc.Launcher$AppClassLoader @ 0x6c01de310" occupies 403,429,704 (76.24%) bytes.
The memory is accumulated in one instance of "java.lang.Object[]" loaded by "<system class loader>".

Keywords
sun.misc.Launcher$AppClassLoader @ 0x6c01de310
java.lang.Object[]
org.apache.flink.runtime.io.network.buffer.NetworkBufferPool

发现是网络缓冲池不足，查到一篇文章：
https://issues.apache.org/jira/browse/FLINK-4536
和我遇到的情况差不多，也是使用了InfluxDB作为Sink，最后在Close里进行关闭，问题解决。

另外，在$FLINK_HOME/conf/flink-conf.yaml中，也有关于TaskManager网络栈的配置，暂时未调整

# The number of buffers for the network stack.
#
# taskmanager.network.numberOfBuffers: 2048

7.Kafka partition leader切换导致Flink重启

现象：

7.1 Flink重启，查看日志，显示：

java.lang.Exception: Failed to send data to Kafka: This server is not the leader for that topic-partition.
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducerBase.checkErroneous(FlinkKafkaProducerBase.java:373)
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducerBase.invoke(FlinkKafkaProducerBase.java:280)
at org.apache.flink.streaming.api.operators.StreamSink.processElement(StreamSink.java:41)
at org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:206)
at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:69)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:263)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.kafka.common.errors.NotLeaderForPartitionException: This server is not the leader for that topic-partition.

7.2 查看Kafka的Controller日志，显示：

INFO [SessionExpirationListener on 10], ZK expired; shut down all controller components and

try to re-elect (kafka.controller.KafkaController$SessionExpirationListener)

7.3 设置retries参数

参考：http://colabug.com/122248.html 以及 Kafka官方文档（http://kafka.apache.org/082/documentation.html#producerconfigs），关于producer参数设置

设置了retries参数，可以在Kafka的Partition发生leader切换时，Flink不重启，而是做3次尝试：

kafkaProducerConfig
{
"bootstrap.servers": "192.169.2.20:9093,192.169.2.21:9093,192.169.2.22:9093"
"retries":3
}