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Apache spark Spark/Thread-连接错误重试BlockFetcher尝试从随机端口提取块_Apache Spark_Hadoop_Apache Spark Sql_Hdfs_Yarn - Fatal编程技术网

Apache spark Spark/Thread-连接错误重试BlockFetcher尝试从随机端口提取块

Apache spark Spark/Thread-连接错误重试BlockFetcher尝试从随机端口提取块,apache-spark,hadoop,apache-spark-sql,hdfs,yarn,Apache Spark,Hadoop,Apache Spark Sql,Hdfs,Yarn,我试图在AWS机器上设置纱线火花。我的spark.driver.port是32975。我在纱线容器日志中看到以下错误。它正在尝试连接到主资源管理器端口35653。我不确定它试图从35653端口获取哪个块。有人能帮忙吗 火花指令 spark提交--部署模式客户端--类org.apache.spark.examples.SparkPi$spark_HOME/examples/jars/spark-examples_2.11-2.4.4.jar 10 Hadoop版本:3.x spark版本:2.4.

我试图在AWS机器上设置纱线火花。我的spark.driver.port是32975。我在纱线容器日志中看到以下错误。它正在尝试连接到主资源管理器端口35653。我不确定它试图从35653端口获取哪个块。有人能帮忙吗

火花指令

spark提交--部署模式客户端--类org.apache.spark.examples.SparkPi$spark_HOME/examples/jars/spark-examples_2.11-2.4.4.jar 10

Hadoop版本:3.x spark版本:2.4.4

2019-12-01 19:09:54590 shuffle.RetryingBlockFetcher错误:开始提取1个未完成的块时出现异常 java.io.IOException:连接到xyz.com/xx.xx.xx.xx:35653超时(120000毫秒) 位于org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:243) 位于org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:187) 位于org.apache.spark.network.netty.NettyBlockTransferService$$anon$2.createAndStart(NettyBlockTransferService.scala:114) 位于org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:141) 位于org.apache.spark.network.shuffle.RetryingBlockFetcher.start(RetryingBlockFetcher.java:121) 位于org.apache.spark.network.netty.NettyBlockTransferService.fetchBlocks(NettyBlockTransferService.scala:124) 位于org.apache.spark.network.BlockTransferService.fetchBlockSync(BlockTransferService.scala:98) 位于org.apache.spark.storage.BlockManager.getRemoteBytes(BlockManager.scala:757) 在org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply$mcVI$sp(TorrentBroadcast.scala:162) 在org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:151) 在org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:151) 位于scala.collection.immutable.List.foreach(List.scala:392) 位于org.apache.spark.broadcast.TorrentBroadcast.org$apache$spark$broadcast$TorrentBroadcast$$readBlocks(TorrentBroadcast.scala:151) 在org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1$$anonfun$apply$2.apply(TorrentBroadcast.scala:231) 位于scala.Option.getOrElse(Option.scala:121) 在org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:211)上 位于org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1326) 位于org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:207) 在org.apache.spark.broadcast.TorrentBroadcast.\u value$lzycompute(TorrentBroadcast.scala:66) 在org.apache.spark.broadcast.TorrentBroadcast.\u值(TorrentBroadcast.scala:66) 位于org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:96) 位于org.apache.spark.broadcast.broadcast.value(broadcast.scala:70) 位于org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:84) 位于org.apache.spark.scheduler.Task.run(Task.scala:123) 位于org.apache.spark.executor.executor$TaskRunner$$anonfun$10.apply(executor.scala:408) 位于org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) 位于org.apache.spark.executor.executor$TaskRunner.run(executor.scala:414) 位于java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) 位于java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) 运行(Thread.java:748)


请检查hadoop/纱线是否正常工作。 您应该首先启动hadoop,然后检查hadoop是否正在运行,而不仅仅是在终端中执行jps

hadoop start-all.sh
jps

每次此端口不断更改时。因此,我怀疑这是否与任何hadoop进程的宕机有关。您是在集群上运行还是在独立模式下运行?作业提交到集群。部署模式是否为clientHave以尝试设置spark驱动程序端口?spark submit--master Thread client--conf spark.driver.port=xxxxx确保HADOOP_conf_DIR或Thread_conf_DIR指向包含HADOOP集群(客户端)配置文件的目录。这些配置用于写入HDFS并连接到Thread ResourceManager。此目录中包含的配置将分发到纱线集群,以便应用程序使用的所有容器都使用相同的配置。如果配置引用的Java系统属性或环境变量不是由Thread管理的,那么它们也应该在Spark应用程序的配置中设置。除此之外,不应存在任何问题。是否有不使用电子病历的具体原因?