Apache Spark流媒体简单应用程序无法正常工

Question

我在Apache Spark Streaming库上遇到以下问题。我已经重写了一个简单的“字数统计”独立应用程序来查看流式传输的工作方式，所以这里代码：

    SparkConf conf = new SparkConf().setMaster("local[2]").setAppName("NetworkWordCount");
    JavaStreamingContext jssc = new JavaStreamingContext(conf, new Duration(1000));

    // Create a DStream that will connect to hostname:port, like localhost:9999
    JavaReceiverInputDStream<String> lines = jssc.socketTextStream("localhost", 9999);

    // Split each line into words
    JavaDStream<String> words = lines.flatMap(
      new FlatMapFunction<String, String>() {
        @Override public Iterable<String> call(String x) {
          return Arrays.asList(x.split(" "));
        }
      });

    // Count each word in each batch
    JavaPairDStream<String, Integer> pairs = words.mapToPair(
      new PairFunction<String, String, Integer>() {
        @Override public Tuple2<String, Integer> call(String s) throws Exception {
          return new Tuple2<String, Integer>(s, 1);
        }
      });



    JavaPairDStream<String, Integer> wordCounts = pairs.reduceByKey(
      new Function2<Integer, Integer, Integer>() {
        @Override public Integer call(Integer i1, Integer i2) throws Exception {
          return i1 + i2;
        }
      });

    // Print the first ten elements of each RDD generated in this DStream to the console
    wordCounts.print();

    jssc.start();              // Start the computation
    jssc.awaitTermination();   // Wait for the computation to terminate

当我运行此独立应用程序时，日志会循环以下行：

14/10/08 13:16:44 INFO JobScheduler: Finished job streaming job 1412767004000 ms.0 from job set of time 1412767004000 ms
14/10/08 13:16:44 INFO JobScheduler: Total delay: 0.023 s for time 1412767004000 ms (execution: 0.019 s)
14/10/08 13:16:44 INFO ShuffledRDD: Removing RDD 428 from persistence list
14/10/08 13:16:44 INFO BlockManager: Removing RDD 428
14/10/08 13:16:44 INFO MappedRDD: Removing RDD 427 from persistence list
14/10/08 13:16:44 INFO BlockManager: Removing RDD 427
14/10/08 13:16:44 INFO FlatMappedRDD: Removing RDD 426 from persistence list
14/10/08 13:16:44 INFO BlockManager: Removing RDD 426
14/10/08 13:16:44 INFO BlockRDD: Removing RDD 425 from persistence list
14/10/08 13:16:44 INFO SocketInputDStream: Removing blocks of RDD BlockRDD[425] at BlockRDD at ReceiverInputDStream.scala:69 of time 1412767004000 ms
14/10/08 13:16:44 INFO BlockManager: Removing RDD 425
14/10/08 13:16:44 INFO SocketReceiver: Stopped receiving
14/10/08 13:16:44 INFO SocketReceiver: Closed socket to localhost:9999
14/10/08 13:16:44 WARN ReceiverSupervisorImpl: Restarting receiver with delay 2000 ms: Retrying connecting to localhost:9999
14/10/08 13:16:44 INFO ReceiverSupervisorImpl: Stopping receiver with message: Restarting receiver with delay 2000ms: Retrying connecting to localhost:9999: 
14/10/08 13:16:44 INFO ReceiverSupervisorImpl: Called receiver onStop
14/10/08 13:16:44 INFO ReceiverSupervisorImpl: Deregistering receiver 0
14/10/08 13:16:44 ERROR ReceiverTracker: Deregistered receiver for stream 0: Restarting receiver with delay 2000ms: Retrying connecting to localhost:9999
14/10/08 13:16:44 INFO ReceiverSupervisorImpl: Stopped receiver 0
14/10/08 13:16:45 INFO ReceiverTracker: Stream 0 received 0 blocks
14/10/08 13:16:45 INFO JobScheduler: Added jobs for time 1412767005000 ms
14/10/08 13:16:45 INFO JobScheduler: Starting job streaming job 1412767005000 ms.0 from job set of time 1412767005000 ms
14/10/08 13:16:45 INFO SparkContext: Starting job: take at DStream.scala:608
14/10/08 13:16:45 INFO DAGScheduler: Registering RDD 435 (map at MappedDStream.scala:35)
14/10/08 13:16:45 INFO DAGScheduler: Got job 217 (take at DStream.scala:608) with 1 output partitions (allowLocal=true)
14/10/08 13:16:45 INFO DAGScheduler: Final stage: Stage 433(take at DStream.scala:608)
14/10/08 13:16:45 INFO DAGScheduler: Parents of final stage: List(Stage 434)
14/10/08 13:16:45 INFO DAGScheduler: Missing parents: List()
14/10/08 13:16:45 INFO DAGScheduler: Submitting Stage 433 (ShuffledRDD[436] at combineByKey at ShuffledDStream.scala:42), which has no missing parents
14/10/08 13:16:45 INFO MemoryStore: ensureFreeSpace(2256) called with curMem=23776, maxMem=277842493
14/10/08 13:16:45 INFO MemoryStore: Block broadcast_217 stored as values in memory (estimated size 2.2 KB, free 264.9 MB)
14/10/08 13:16:45 INFO DAGScheduler: Submitting 1 missing tasks from Stage 433 (ShuffledRDD[436] at combineByKey at ShuffledDStream.scala:42)
14/10/08 13:16:45 INFO TaskSchedulerImpl: Adding task set 433.0 with 1 tasks
14/10/08 13:16:45 INFO TaskSetManager: Starting task 0.0 in stage 433.0 (TID 217, localhost, PROCESS_LOCAL, 1008 bytes)
14/10/08 13:16:45 INFO Executor: Running task 0.0 in stage 433.0 (TID 217)
14/10/08 13:16:45 INFO BlockFetcherIterator$BasicBlockFetcherIterator: maxBytesInFlight: 50331648, targetRequestSize: 10066329
14/10/08 13:16:45 INFO BlockFetcherIterator$BasicBlockFetcherIterator: Getting 0 non-empty blocks out of 0 blocks
14/10/08 13:16:45 INFO BlockFetcherIterator$BasicBlockFetcherIterator: Started 0 remote fetches in 0 ms
14/10/08 13:16:45 INFO Executor: Finished task 0.0 in stage 433.0 (TID 217). 822 bytes result sent to driver
14/10/08 13:16:45 INFO TaskSetManager: Finished task 0.0 in stage 433.0 (TID 217) in 4 ms on localhost (1/1)
14/10/08 13:16:45 INFO DAGScheduler: Stage 433 (take at DStream.scala:608) finished in 0.006 s
14/10/08 13:16:45 INFO TaskSchedulerImpl: Removed TaskSet 433.0, whose tasks have all completed, from pool 
14/10/08 13:16:45 INFO SparkContext: Job finished: take at DStream.scala:608, took 0.009386933 s
14/10/08 13:16:45 INFO SparkContext: Starting job: take at DStream.scala:608
14/10/08 13:16:45 INFO MapOutputTrackerMaster: Size of output statuses for shuffle 108 is 82 bytes
14/10/08 13:16:45 INFO DAGScheduler: Got job 218 (take at DStream.scala:608) with 1 output partitions (allowLocal=true)
14/10/08 13:16:45 INFO DAGScheduler: Final stage: Stage 435(take at DStream.scala:608)
14/10/08 13:16:45 INFO DAGScheduler: Parents of final stage: List(Stage 436)
14/10/08 13:16:45 INFO DAGScheduler: Missing parents: List()
14/10/08 13:16:45 INFO DAGScheduler: Submitting Stage 435 (ShuffledRDD[436] at combineByKey at ShuffledDStream.scala:42), which has no missing parents
14/10/08 13:16:45 INFO MemoryStore: ensureFreeSpace(2256) called with curMem=26032, maxMem=277842493
14/10/08 13:16:45 INFO MemoryStore: Block broadcast_218 stored as values in memory (estimated size 2.2 KB, free 264.9 MB)
14/10/08 13:16:45 INFO DAGScheduler: Submitting 1 missing tasks from Stage 435 (ShuffledRDD[436] at combineByKey at ShuffledDStream.scala:42)
14/10/08 13:16:45 INFO TaskSchedulerImpl: Adding task set 435.0 with 1 tasks
14/10/08 13:16:45 INFO TaskSetManager: Starting task 0.0 in stage 435.0 (TID 218, localhost, PROCESS_LOCAL, 1008 bytes)
14/10/08 13:16:45 INFO Executor: Running task 0.0 in stage 435.0 (TID 218)
14/10/08 13:16:45 INFO BlockFetcherIterator$BasicBlockFetcherIterator: maxBytesInFlight: 50331648, targetRequestSize: 10066329
14/10/08 13:16:45 INFO BlockFetcherIterator$BasicBlockFetcherIterator: Getting 0 non-empty blocks out of 0 blocks
14/10/08 13:16:45 INFO BlockFetcherIterator$BasicBlockFetcherIterator: Started 0 remote fetches in 1 ms
14/10/08 13:16:45 INFO Executor: Finished task 0.0 in stage 435.0 (TID 218). 822 bytes result sent to driver
14/10/08 13:16:45 INFO TaskSetManager: Finished task 0.0 in stage 435.0 (TID 218) in 3 ms on localhost (1/1)
14/10/08 13:16:45 INFO TaskSchedulerImpl: Removed TaskSet 435.0, whose tasks have all completed, from pool 
14/10/08 13:16:45 INFO DAGScheduler: Stage 435 (take at DStream.scala:608) finished in 0.003 s
14/10/08 13:16:45 INFO SparkContext: Job finished: take at DStream.scala:608, took 0.008348754 s
-------------------------------------------
Time: 1412767005000 ms
-------------------------------------------

在网页用户界面上，我可以看到以下屏幕截图：

显然，当我写一些示例单词时，netcat -lk 9999没有做任何事情。

有人可以帮我弄清楚这个例子是如何运作的吗？

感谢

Answer 1

如评论中所述

运行

nc -lk 9999 in console 

然后在spark文件夹

中运行以下命令

bin/run-example org.apache.spark.examples.streaming.JavaNetworkWordCount localhost 9999

现在在运行nc

的控制台的选项卡中添加单词

It is working! Life is beautiful!

并检查spark文件夹中的输出

(beautiful!,1)
(working!,1)
(is,2)
(It,1)
(Life,1)

如果你继续添加，它的程序将继续巩固.. 希望这有帮助

Answer 2

您需要使用此命令打开一个端口以在本地系统中进行通信

nc -lk 9999

然后在spark之后从控制台（端口9999）获取所有文本作为流。