1.啟動不起來
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$8.run(Scheduler.scala:381) at java.lang.Thread.run(Thread.java:748)
解決方案：/etc/hosts中配置的主機名都是小寫，但是在Flink配置文件（flink-config.yaml、masters、slaves）中配置的都是大寫的hostname，將flink配置文件中的hostname都改為小寫或者IP地址
2.運行一段時間退出
AsynchronousException{java.lang.Exception: Could not materialize checkpoint 4 for operator Compute By Event Time (1/12).}
at org.apache.flink.streaming.runtime.tasks.StreamTask$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$CheckpointingOperation.executeCheckpointing(StreamTask.java:1094)
at org.apache.flink.streaming.runtime.tasks.StreamTask.checkpointState(StreamTask.java:654)
at org.apache.flink.streaming.runtime.tasks.StreamTask.performCheckpoint(StreamTask.java:590)
at org.apache.flink.streaming.runtime.tasks.StreamTask.triggerCheckpointOnBarrier(StreamTask.java:543)
at org.apache.flink.streaming.runtime.io.BarrierBuffer.notifyCheckpoint(BarrierBuffer.java:378)
at org.apache.flink.streaming.runtime.io.BarrierBuffer.processBarrier(BarrierBuffer.java:281)
at org.apache.flink.streaming.runtime.io.BarrierBuffer.getNextNonBlocked(BarrierBuffer.java:183)
at org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:213)
at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:69)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:263)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702)
... 1 more
[CIRCULAR REFERENCE:java.io.IOException: Size of the state is larger than the maximum permitted memory-backed state. Size=7061809 , maxSize=5242880 . Consider using a different state backend, like the File System State backend.]
解決方案：
狀態存儲，默認是在內存中，改為存儲到HDFS中：
state.backend.fs.checkpointdir: hdfs://t-sha1-flk-01:9000/flink-checkpoints
3.長時間運行后，多次重啟
AsynchronousException{java.lang.Exception: Could not materialize checkpoint 1488 for operator Compute By Event Time -> (MonitorData, MonitorDataMapping, MonitorSamplingData) (6/6).}
at org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.run(StreamTask.java:948)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$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.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$1.run(Server.java:2217)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2213)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1746)
at org.apache.hadoop.ipc.Server$Handler.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作為CheckPoint的存儲，當flink重啟時，原來的checkpoint沒有用了，我就手動給刪了，不知道和這個有沒有關系，為了不繼續報異常，便重啟了Flink、HDFS，重啟后不再有異常信息了。
但是查看HDFS日志時，發現如下警告（不合規范的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
原來是配置錯了，hdfs-site.xml中的
<property>
<name>dfs.namenode.name.dir</name>
<value>/mnt/hadoop/dfs/name</value>
</property>
應該改為：
<property>
<name>dfs.namenode.name.dir</name>
<value>file:/mnt/hadoop/dfs/name</value>
</property>
至此問題解決，根上的問題應該是hdfs-site.xml配置的不對導致的。
4.Unable to load native-hadoop library for your platform
Flink啟動時，有時會有如下警告信息：
WARN org.apache.hadoop.util.NativeCodeLoader
- Unable to load native-hadoop library for your platform...
using builtin-java classes where applicable
參考資料1：http://blog.csdn.net/jack85986370/article/details/51902871
解決方案：編輯/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"
未能解決該問題
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
參考資料：http://blog.csdn.net/zhangzhaokun/article/details/50951238
解決方案
cd /usr/lib64/ ln -s libcrypto.so.1.0.1e libcrypto.so
6.TaskManager退出
Flink運行一段時間后，出現TaskManager退出情況，通過jvisualvm抓取TaskManager的Dump，使用MAT進行分析，結果如下：
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
發現是網絡緩沖池不足，查到一篇文章：
https://issues.apache.org/jira/browse/FLINK-4536
和我遇到的情況差不多，也是使用了InfluxDB作為Sink，最后在Close里進行關閉，問題解決。
另外，在$FLINK_HOME/conf/flink-conf.yaml中，也有關於TaskManager網絡棧的配置，暫時未調整
# The number of buffers for the network stack. # # taskmanager.network.numberOfBuffers: 2048
7.Kafka partition leader切換導致Flink重啟
現象：
7.1 Flink重啟，查看日志，顯示：
java.lang.Exception: Failed to send data to Kafka: This server is not the leader for that topic-partition. at org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducerBase.checkErroneous(FlinkKafkaProducerBase.java:373) at org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducerBase.invoke(FlinkKafkaProducerBase.java:280) at org.apache.flink.streaming.api.operators.StreamSink.processElement(StreamSink.java:41) at org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:206) at org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:69) at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:263) at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.kafka.common.errors.NotLeaderForPartitionException: This server is not the leader for that topic-partition.
7.2 查看Kafka的Controller日志，顯示：
INFO [SessionExpirationListener on 10], ZK expired; shut down all controller components and
try to re-elect (kafka.controller.KafkaController$SessionExpirationListener)
7.3 設置retries參數
參考：http://colabug.com/122248.html 以及 Kafka官方文檔（http://kafka.apache.org/082/documentation.html#producerconfigs），關於producer參數設置
設置了retries參數，可以在Kafka的Partition發生leader切換時，Flink不重啟，而是做3次嘗試：
kafkaProducerConfig { "bootstrap.servers": "192.169.2.20:9093,192.169.2.21:9093,192.169.2.22:9093" "retries":3 }