centos6.2 spark cluster問題（持續追加）

 

系統：centos6.2

節點數目：1個master，16個worker

spark版本：0.8.0

內核版本：2.6.32

如下是遇到的問題及解決辦法：

1. 執行完某一個任務後，某個節點沒法再次鏈接，在其上執行jps出現：StandaloneExecutorBackend進程，沒法結束。

緣由：不明

解決辦法：重啓，從新鏈接。

2. worker節點tasktracker沒法啓動

緣由：關閉集羣后的worker節點上tasktracker節點沒關掉。

解決辦法：關閉集羣后，手動找到worker節點上的tasktracker進程並殺死

3. 執行start-master.sh報錯：failed to launch org.apache.spark.deploy.master.Master

[root@hw024 spark-0.8.0-incubating]# ./bin/start-master.sh

starting org.apache.spark.deploy.master.Master, logging to /home/zhangqianlong/spark-0.8.0-incubating/bin/../logs/spark-root-org.apache.spark.deploy.master.Master-1-hw024.out

failed to launch org.apache.spark.deploy.master.Master:

Error: Could not find or load main class org.apache.spark.deploy.master.Master

full log in /home/zhangqianlong/spark-0.8.0-incubating/bin/../logs/spark-root-org.apache.spark.deploy.master.Master-1-hw024.out

解決辦法：執行sbt/sbt clean assembly

4. master執行結束後結果顯示正常，可是worker節點的/work/XX/stderr中報錯誤。

cd $SPARK_HOME 
./run-example org.apache.spark.examples.SparkPi spark://hw024:7077

標準輸出結果：

……

14/03/20 11:13:02 INFO scheduler.DAGScheduler: Stage 0 (reduce at SparkPi.scala:39) finished in 1.642 s

14/03/20 11:13:02 INFO cluster.ClusterScheduler: Remove TaskSet 0.0 from pool

14/03/20 11:13:02 INFO spark.SparkContext: Job finished: reduce at SparkPi.scala:39, took 1.708775428 s

Pi is roughly 3.13434

可是查看workernode的/home/zhangqianlong/spark-0.8.0-incubating-bin-hadoop1/work/app-20140320111300-0008/8/stderr內容以下：

Spark Executor Command: "java" "-cp" ":/home/zhangqianlong/spark-0.8.0-incubating-bin-hadoop1/conf:/home/zhangqianlong/spark-0.8.0-incubating-bin-hadoop1/assembly/target/scala-2.9.3/spark-assembly_2.9.3-0.8.0-incubating-hadoop1.0.4.jar" "-Xms512M" "-Xmx512M" "org.apache.spark.executor.StandaloneExecutorBackend" "akka://spark@hw024:60929/user/StandaloneScheduler" "8" "hw018" "24"

====================================

14/03/20 11:05:15 INFO slf4j.Slf4jEventHandler: Slf4jEventHandler started

14/03/20 11:05:15 INFO executor.StandaloneExecutorBackend: Connecting to driver: akka://spark@hw024:60929/user/StandaloneScheduler

14/03/20 11:05:15 INFO executor.StandaloneExecutorBackend: Successfully registered with driver

14/03/20 11:05:15 INFO slf4j.Slf4jEventHandler: Slf4jEventHandler started

14/03/20 11:05:15 INFO spark.SparkEnv: Connecting to BlockManagerMaster: akka://spark@hw024:60929/user/BlockManagerMaster

14/03/20 11:05:15 INFO storage.MemoryStore: MemoryStore started with capacity 323.9 MB.

14/03/20 11:05:15 INFO storage.DiskStore: Created local directory at /tmp/spark-local-20140320110515-9151

14/03/20 11:05:15 INFO network.ConnectionManager: Bound socket to port 59511 with id = ConnectionManagerId(hw018,59511)

14/03/20 11:05:15 INFO storage.BlockManagerMaster: Trying to register BlockManager

14/03/20 11:05:15 INFO storage.BlockManagerMaster: Registered BlockManager

14/03/20 11:05:15 INFO spark.SparkEnv: Connecting to MapOutputTracker: akka://spark@hw024:60929/user/MapOutputTracker

14/03/20 11:05:15 INFO spark.HttpFileServer: HTTP File server directory is /tmp/spark-81a80beb-fd56-4573-9afe-ca9310d3ea8d

14/03/20 11:05:15 INFO server.Server: jetty-7.x.y-SNAPSHOT

14/03/20 11:05:15 INFO server.AbstractConnector: Started SocketConnector@0.0.0.0:56230

14/03/20 11:05:16 ERROR executor.StandaloneExecutorBackend: Driver terminated or disconnected! Shutting down.

這個問題困擾我一週了，F**K！

通過屢次與其餘攻城獅討論，該問題不用理會，只要正常運行結束，而且hadoop fs -cat /XX/part-XXX有輸出結果，結果是想要的就行。我猜是由於延時配置問題。

5.運行時報錯：filenotfoundexception： too many open files

緣由：迭代計算時打開太多臨時文件

解決辦法：修改全部節點的系統打開文件上限設置：/etc/security/limits.conf（注意，不能用ssh遠程登錄後先刪除再拷貝，會致使系統沒法登錄）

重啓spark後生效就能夠解決

6. 因爲在spark上運行的程序，輸入數據太大（當輸入小的時候能夠成功運行）形成程序掛掉。

報錯信息以下：

14/04/15 16:14:33 INFO cluster.ClusterTaskSetManager: Starting task 2.0:92 as TID 594 on executor 24: hw028 (ANY)
14/04/15 16:14:33 INFO cluster.ClusterTaskSetManager: Serialized task 2.0:92 as 2119 bytes in 0 ms
14/04/15 16:14:33 INFO client.Client$ClientActor: Executor updated: app-20140415151451-0000/23 is now FAILED (Command exited with code 137)
14/04/15 16:14:33 INFO cluster.SparkDeploySchedulerBackend: Executor app-20140415151451-0000/23 removed: Command exited with code 137
14/04/15 16:14:33 ERROR client.Client$ClientActor: Master removed our application: FAILED; stopping client
14/04/15 16:14:33 ERROR cluster.SparkDeploySchedulerBackend: Disconnected from Spark cluster!
14/04/15 16:14:33 INFO cluster.ClusterScheduler: Remove TaskSet 2.0 from pool 
14/04/15 16:14:33 INFO cluster.ClusterScheduler: Ignoring update from TID 590 because its task set is gone
14/04/15 16:14:33 INFO cluster.ClusterScheduler: Ignoring update from TID 593 because its task set is gone
14/04/15 16:14:33 INFO scheduler.DAGScheduler: Failed to run count at PageRank.scala:43
Exception in thread "main" org.apache.spark.SparkException: Job failed: Error: Disconnected from Spark cluster
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:760)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:758)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:60)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:758)
at org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:379)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$run(DAGScheduler.scala:441)
at org.apache.spark.scheduler.DAGScheduler$$anon$1.run(DAGScheduler.scala:149)

緣由：RDD太大了，每一個節點好多RDD，致使內存不夠。

解決辦法：修改運行命令或者sprak-env.sh，添加參數 -Dspark.akka.frameSize=10000（以M爲單位的）。

7. 因爲輸入數據太大或者網絡太差致使的woker節點「no recent heart beats」。

現象： WARN storage.BlockManagerMasterActor: Removing BlockManager BlockManagerId(0, hw032, 39782, 0) with no recent heart beats: 46910ms exceeds 45000ms

緣由：因爲網絡差或者數據量太大，worker節點在必定的時間內（默認45s）沒有給master信號，master覺得它掛了。

解決辦法：修改運行命令或者sprak-env.sh，添加參數 -Dspark.storage.blockManagerHeartBeatMs=60000（以ms爲單位，即6分鐘）。