如果你能帮助我，我将不胜感激。
在执行从kafka到hbase的火花串流（代码附加）期间，我们遇到了一个问题“java.io.IOException：Connection reset by peer”（附带完整日志）。
如果我们使用hbase并且在spark设置中启用了动态分配选项，则会出现此问题。如果我们在hdfs（hive表）而不是hbase中写入数据，或者如果关闭动态分配选项，则不会发现错误。
我们尝试更改zookeeper连接，spark执行器空闲超时，网络超时。我们已经尝试改变shuffle块传输服务（NIO），但错误仍然存在。如果我们为动态分配设置最小/最大执行者（少于80），那么也没有问题。
问题可能是什么？在Jira和堆栈溢出中存在许多几乎相同的问题，但没有任何帮助。
版本：
HBase 1.2.0-cdh5.14.0
Kafka 3.0.0-1.3.0.0.p0.40
SPARK2 2.2.0.cloudera2-1.cdh5.12.0.p0.232957
hbase-client/hbase-spark(org.apache.hbase) 1.2.0-cdh5.11.1
Spark设置：
--num-executors=80
--conf spark.sql.shuffle.partitions=200
--conf spark.driver.memory=32g
--conf spark.executor.memory=32g
--conf spark.executor.cores=4
集群： 1 + 8个节点，70个CPU，755Gb RAM，x10 HDD，
日志：
18/04/09 13:51:56 INFO cluster.YarnClusterScheduler: Executor 717 on lang32.ca.sbrf.ru killed by driver.
18/04/09 13:51:56 INFO storage.BlockManagerMaster: Removed 717 successfully in removeExecutor
18/04/09 13:51:56 INFO spark.ExecutorAllocationManager: Existing executor 717 has been removed (new total is 26)
18/04/09 13:51:56 INFO cluster.YarnSchedulerBackend$YarnDriverEndpoint: Disabling executor 705.
18/04/09 13:51:56 INFO scheduler.DAGScheduler: Executor lost: 705 (epoch 45)
18/04/09 13:51:56 INFO storage.BlockManagerMasterEndpoint: Trying to remove executor 705 from BlockManagerMaster.
18/04/09 13:51:56 INFO cluster.YarnClusterScheduler: Executor 705 on lang32.ca.sbrf.ru killed by driver.
18/04/09 13:51:56 INFO storage.BlockManagerMasterEndpoint: Removing block manager BlockManagerId(705, lang32.ca.sbrf.ru, 22805, None)
18/04/09 13:51:56 INFO spark.ExecutorAllocationManager: Existing executor 705 has been removed (new total is 25)
18/04/09 13:51:56 INFO storage.BlockManagerMaster: Removed 705 successfully in removeExecutor
18/04/09 13:51:56 INFO cluster.YarnSchedulerBackend$YarnDriverEndpoint: Disabling executor 716.
18/04/09 13:51:56 INFO scheduler.DAGScheduler: Executor lost: 716 (epoch 45)
18/04/09 13:51:56 INFO storage.BlockManagerMasterEndpoint: Trying to remove executor 716 from BlockManagerMaster.
18/04/09 13:51:56 INFO cluster.YarnClusterScheduler: Executor 716 on lang32.ca.sbrf.ru killed by driver.
18/04/09 13:51:56 INFO storage.BlockManagerMasterEndpoint: Removing block manager BlockManagerId(716, lang32.ca.sbrf.ru, 28678, None)
18/04/09 13:51:56 INFO spark.ExecutorAllocationManager: Existing executor 716 has been removed (new total is 24)
18/04/09 13:51:56 INFO storage.BlockManagerMaster: Removed 716 successfully in removeExecutor
18/04/09 13:51:56 WARN server.TransportChannelHandler: Exception in connection from /10.116.173.65:57542
java.io.IOException: Connection reset by peer
at sun.nio.ch.FileDispatcherImpl.read0(Native Method)
at sun.nio.ch.SocketDispatcher.read(SocketDispatcher.java:39)
at sun.nio.ch.IOUtil.readIntoNativeBuffer(IOUtil.java:223)
at sun.nio.ch.IOUtil.read(IOUtil.java:192)
at sun.nio.ch.SocketChannelImpl.read(SocketChannelImpl.java:380)
at io.netty.buffer.PooledUnsafeDirectByteBuf.setBytes(PooledUnsafeDirectByteBuf.java:221)
at io.netty.buffer.AbstractByteBuf.writeBytes(AbstractByteBuf.java:899)
at io.netty.channel.socket.nio.NioSocketChannel.doReadBytes(NioSocketChannel.java:275)
at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:119)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:643)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:566)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:480)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:442)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
at java.lang.Thread.run(Thread.java:748)
18/04/09 13:51:56 ERROR client.TransportResponseHandler: Still have 1 requests outstanding when connection from /10.116.173.65:57542 is closed
18/04/09 13:51:56 INFO cluster.YarnSchedulerBackend$YarnDriverEndpoint: Disabling executor 548.
答案 0 :(得分：0)
请在此处查看我的相关答案：What are possible reasons for receiving TimeoutException: Futures timed out after [n seconds] when working with Spark
我还花了一些时间来理解为什么Cloudera会说明以下内容：
动态分配和Spark Streaming
如果您使用Spark Streaming，Cloudera建议您禁用 通过将spark.dynamicAllocation.enabled设置为false来进行动态分配 在运行流媒体应用程序时。
答案 1 :(得分：0)
尝试设置这两个参数。在写入HBase之前，请尝试缓存 pa_foobar。
Dataframe
spark.network.timeout