Flink提交运行中常见问题总结，Flink开发问题汇总

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Flink提交运行中常见问题总结，Flink开发问题汇总
Flink开发问题汇总

https://blog.csdn.net/circle2015/article/details/102768820

一、flink里面能调用图算法吗？
二、Cannot instantiate user function
三、本地idea开发flink程序并本地运行读取HDFS文件
四、The assigned slot container_e08_1539148828017_15937_01_003564_0 was removed
五、java.util.concurrent.TimeoutException: Heartbeat of TaskManager with id container_e03_1553154249286_347659_01_000011 timed out.
六、could not find implicit value for evidence parameter of type org.apache.flink.api.common.typeinfo.TypeInformation[Int]
七、flink中使用event事件以及process处理状态数据
八、flink读取多个权限topic（>=1）
九、flink内部使用一个外部类调用其接口报错未初始化
十、The end timestamp of an event-time window cannot become earlier than the current watermark by merging
————————————————
版权声明：本文为CSDN博主「明日韭菜」的原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/circle2015/article/details/102768820

Flink提交运行中常见问题总结

一、提交jar到Flink集群时候出现异常

提交jar到Flink集群时候出现：
java.util.ServiceConfigurationError: org.apache.hadoop.fs.FileSystem: Provider org.apache.hadoop.fs.viewfs.ViewFileSystem could not be instantiated

可能原因解释：

出现该问题，往往是由于没有争取读取到hadoop中配置信息，

解决方法：

HADOOP_HOME=/hadoop/hadoop-2.7.2

HADOOP_CONF_DIR=/hadoop/hadoop-2.7.2/etc/hadoop/

FLINK_HOME=/home/flink-1.4.2

同时建议使用Flink提供的官方flink-hadoop依赖包，自身提供的hadoop的jar包坑不全
在maven中pom.xml中加入如下依赖
使用不同的flink官方包：如果要做checkpoint功能，需要此时需要配置



<dependency>

<groupId>org.apache.flink</groupId>

<artifactId>flink-shaded-hadoop2</artifactId>

<version>1.4.2</version>

</dependency>

ps:其他的maven中的依赖项，见我的另外一篇博客：
https://blog.csdn.net/fct2001140269/article/details/84864151

二、提交执行Flink的jar包时候，出现错误[Flink JobExecutionException: akka.client.timeout]

提交执行Flink的jar包时候，出现错误[Flink JobExecutionException: akka.client.timeout]

问题分析：

表面来看就是你的工程没有在规定的时间内（Flink集群默认配置中是60s），可能是你的工程项目比较大，jobManager进程难以在规定的短时间内完成Flink的逻辑topology图的构建，或者难以在规定的时间内，完成各个算子（例如：richMapFunction()）的初始化等工作；

解决办法：

建议在集群中配置如下选型：增加job作业提交允许的构建和初始化读取资源的时间。

-akka.client.timeout:600s

-akka.ask.timeout:600s

重新提交jar包到集群中，等待一段时间可以在web-ui上查看到任务提交情况。（如果失败，可能还有其他原因导致到异常！）

三、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。

四、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

五、长时间运行后，多次重启

AsynchronousException{java.lang.Exception: Could not materialize checkpoint 1488 for operator Compute By Event Time -> (MonitorData, MonitorDataMapping, MonitorSamplingData) (6/6).}

at org.apache.flink.streaming.runtime.tasks.StreamTaskAsyncCheckpointRunnable.run(StreamTask.java:948)atjava.util.concurrent.Executors'>[Math Processing Error]AsyncCheckpointRunnable.run(StreamTask.java:948)atjava.util.concurrent.ExecutorsAsyncCheckpointRunnable.run(StreamTask.java:948) at java.util.concurrent.ExecutorsRunnableAdapter.call(Executors.java:511)

at java.util.concurrent.FutureTask.run(FutureTask.java:266)

at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)

at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)

at java.lang.Thread.run(Thread.java:748)

Caused by: java.lang.Exception: Could not materialize checkpoint 1488 for operator Compute By Event Time -> (MonitorData, MonitorDataMapping, MonitorSamplingData) (6/6).

... 6 more

Caused by: java.util.concurrent.ExecutionException: org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /flink-checkpoints/8c274785f1ab027e6146a59364be645f/chk-1488/2c612f30-c57d-4ede-9025-9554ca11fd12 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:1628)

at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getNewBlockTargets(FSNamesystem.java:3121)

at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3045)

at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:725)

at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:493)

at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtosClientNamenodeProtocol'>[Math Processing Error]ClientNamenodeProtocolClientNamenodeProtocol2.callBlockingMethod(ClientNamenodeProtocolProtos.java)

at org.apache.hadoop.ipc.ProtobufRpcEngineServer'>[Math Processing Error]ServerServerProtoBufRpcInvoker.call(ProtobufRpcEngine.java:616)

at org.apache.hadoop.ipc.RPCServer.call(RPC.java:982)atorg.apache.hadoop.ipc.Server'>[Math Processing Error]Server.call(RPC.java:982)atorg.apache.hadoop.ipc.ServerServer.call(RPC.java:982) at org.apache.hadoop.ipc.ServerHandler1.run(Server.java:2217)atorg.apache.hadoop.ipc.Server'>[Math Processing Error]1.run(Server.java:2217)atorg.apache.hadoop.ipc.Server1.run(Server.java:2217) at org.apache.hadoop.ipc.ServerHandler1.run(Server.java:2213)atjava.security.AccessController.doPrivileged(NativeMethod)atjavax.security.auth.Subject.doAs(Subject.java:422)atorg.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1746)atorg.apache.hadoop.ipc.Server'>[Math Processing Error]1.run(Server.java:2213)atjava.security.AccessController.doPrivileged(NativeMethod)atjavax.security.auth.Subject.doAs(Subject.java:422)atorg.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1746)atorg.apache.hadoop.ipc.Server1.run(Server.java:2213) 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:1746) at org.apache.hadoop.ipc.ServerHandler.run(Server.java:2213)

查看hdfs日志：

WARN org.apache.hadoop.hdfs.protocol.BlockStoragePolicy:

Failed to place enough replicas: expected size is 2 but only 0 storage types can be selected

(replication=3, selected=[], unavailable=[DISK], removed=[DISK, DISK],

policy=BlockStoragePolicy{HOT:7, storageTypes=[DISK], creationFallbacks=[], replicationFallbacks=[ARCHIVE]})

搭建的Flink使用HDFS作为CheckPoint的存储，当flink重启时，原来的checkpoint没有用了，我就手动给删了，不知道和这个有没有关系，为了不继续报异常，便重启了Flink、HDFS，重启后不再有异常信息了。

但是查看HDFS日志时，发现如下警告（不合规范的URI格式）：

WARN org.apache.hadoop.hdfs.server.common.Util:

Path /mnt/hadoop/dfs/name should be specified as a URI in configuration files.

Please update hdfs configuration

原来是配置错了，hdfs-site.xml中的

<property>

<name>dfs.namenode.name.dir</name>

<value>/mnt/hadoop/dfs/name</value>

</property>

应该改为：

<property>

<name>dfs.namenode.name.dir</name>

<value>file:/mnt/hadoop/dfs/name</value>

</property>

至此问题解决，根上的问题应该是hdfs-site.xml配置的不对导致的。

六、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

 七、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

八、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

九、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

}
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原文地址：https://www.cnblogs.com/timssd/p/6275281.html

Flink提交运行中常见问题总结，Flink开发问题汇总

Flink提交运行中常见问题总结

一、提交jar到Flink集群时候出现异常

提交jar到Flink集群时候出现：java.util.ServiceConfigurationError: org.apache.hadoop.fs.FileSystem: Provider org.apache.hadoop.fs.viewfs.ViewFileSystem could not be instantiated

可能原因解释：

解决方法：

二、提交执行Flink的jar包时候，出现错误[Flink JobExecutionException: akka.client.timeout]

问题分析：

解决办法：

三、启动不起来

解决方案：

四、运行一段时间退出

解决方案：

五、长时间运行后，多次重启

应该改为：

六、Unable to load native-hadoop library for your platform

解决方案：

七、hadoop checknative -a

解决方案：

八、TaskManager退出

九、Kafka partition leader切换导致Flink重启

7.1 Flink重启，查看日志，显示：

7.2 查看Kafka的Controller日志，显示：

7.3 设置retries参数

提交jar到Flink集群时候出现：
java.util.ServiceConfigurationError: org.apache.hadoop.fs.FileSystem: Provider org.apache.hadoop.fs.viewfs.ViewFileSystem could not be instantiated