我的集群:1个主节点,11个从节点,每个节点都有6GB的内存。
我的设置:
spark.executor.memory=4g, Dspark.akka.frameSize=512
问题如下:
首先,我从HDFS中读取了一些数据(2.19 GB)到RDD中:
val imageBundleRDD = sc.newAPIHadoopFile(...)
其次,对这个RDD执行一些操作:
val res = imageBundleRDD.map(data => {
val desPoints = threeDReconstruction(data._2, bg)
(data._1, desPoints)
})
最后,输出到HDFS:
res.saveAsNewAPIHadoopFile(...)
当我运行我的程序时,它会显示:
.....
14/01/15 21:42:27 INFO cluster.ClusterTaskSetManager: Starting task 1.0:24 as TID 33 on executor 9: Salve7.Hadoop (NODE_LOCAL)
14/01/15 21:42:27 INFO cluster.ClusterTaskSetManager: Serialized task 1.0:24 as 30618515 bytes in 210 ms
14/01/15 21:42:27 INFO cluster.ClusterTaskSetManager: Starting task 1.0:36 as TID 34 on executor 2: Salve11.Hadoop (NODE_LOCAL)
14/01/15 21:42:28 INFO cluster.ClusterTaskSetManager: Serialized task 1.0:36 as 30618515 bytes in 449 ms
14/01/15 21:42:28 INFO cluster.ClusterTaskSetManager: Starting task 1.0:32 as TID 35 on executor 7: Salve4.Hadoop (NODE_LOCAL)
Uncaught error from thread [spark-akka.actor.default-dispatcher-3] shutting down JVM since 'akka.jvm-exit-on-fatal-error' is enabled for ActorSystem[spark]
java.lang.OutOfMemoryError: Java heap space
任务太多了吗?
PS:当输入数据约为225MB时,一切正常。
我该如何解决这个问题?