我想使用foreachpartition在我的数据库中保存数据，但我注意到这个功能不起作用
RDD2.foreachRDD(new VoidFunction<JavaRDD<Object>>() {
@Override
public void call(JavaRDD<Object> t) throws Exception {
t.foreachPartition(new VoidFunction<Iterator<Object>>() {
@Override
public void call(Iterator<Object> t) throws Exception {
System.out.println("test");
} }
);
}});
当我运行此示例时，我的火花程序将在这些步骤中被阻止，而不显示其他RDD甚至打印测试
6/05/30 10:18:41 INFO SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:1006
16/05/30 10:18:41 INFO TaskSchedulerImpl: Adding task set 0.0 with 1 tasks
16/05/30 10:18:41 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, localhost, partition 0,PROCESS_LOCAL, 2946 bytes)
16/05/30 10:18:41 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
16/05/30 10:18:41 INFO SparkContext: Starting job: foreachPartition at BrokerSpout.java:265
16/05/30 10:18:41 INFO RecurringTimer: Started timer for BlockGenerator at time 1464596321600
-------------------------------------------
Time: 1464596321500 ms
-------------------------------------------
16/05/30 10:18:41 INFO ReceivedBlockTracker: Deleting batches ArrayBuffer()
16/05/30 10:18:41 INFO ReceiverTracker: Registered receiver for stream 0 from 10.25.30.41:59407
16/05/30 10:18:41 INFO InputInfoTracker: remove old batch metadata:
16/05/30 10:18:41 INFO ReceiverSupervisorImpl: Starting receiver
16/05/30 10:18:41 INFO ReceiverSupervisorImpl: Called receiver onStart
16/05/30 10:18:41 INFO ReceiverSupervisorImpl: Waiting for receiver to be stopped
16/05/30 10:18:42 INFO SparkContext: Starting job: foreachPartition at BrokerSpout.java:265
16/05/30 10:18:42 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1006
16/05/30 10:18:42 INFO TaskSchedulerImpl: Adding task set 1.0 with 2 tasks
正如你在我的记录中所看到的，它说我的火花正在等待接收器停止，但我的接收器一定不能停止，如果不是，如果我们必须停止发送器，火花流的目的是什么。