I checked the ports using netstat and don't see any connections established on that port. Logs show only this:
15/03/27 13:50:48 INFO Master: Registering app NetworkWordCount 15/03/27 13:50:48 INFO Master: Registered app NetworkWordCount with ID app-20150327135048-0002 Spark ui shows: Running Applications IDNameCoresMemory per NodeSubmitted TimeUserStateDuration app-20150327135048-0002 <http://54.69.225.94:8080/app?appId=app-20150327135048-0002>NetworkWordCount <http://ip-10-241-251-232.us-west-2.compute.internal:4040/>0512.0 MB2015/03/27 13:50:48ec2-userWAITING33 s Code looks like is being executed: java -cp .:* org.spark.test.WordCount spark://ip-10-241-251-232:7077 *public* *static* *void* doWork(String masterUrl){ SparkConf conf = *new* SparkConf().setMaster(masterUrl).setAppName( "NetworkWordCount"); JavaStreamingContext *jssc* = *new* JavaStreamingContext(conf, Durations. *seconds*(1)); JavaReceiverInputDStream<String> lines = jssc.socketTextStream("localhost", 9999); System.*out*.println("Successfully created connection"); *mapAndReduce*(lines); jssc.start(); // Start the computation jssc.awaitTermination(); // Wait for the computation to terminate } *public* *static* *void* main(String ...args){ *doWork*(args[0]); } And output of the java program after submitting the task: java -cp .:* org.spark.test.WordCount spark://ip-10-241-251-232:7077 Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties 15/03/27 13:50:46 INFO SecurityManager: Changing view acls to: ec2-user 15/03/27 13:50:46 INFO SecurityManager: Changing modify acls to: ec2-user 15/03/27 13:50:46 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(ec2-user); users with modify permissions: Set(ec2-user) 15/03/27 13:50:46 INFO Slf4jLogger: Slf4jLogger started 15/03/27 13:50:46 INFO Remoting: Starting remoting 15/03/27 13:50:47 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkdri...@ip-10-241-251-232.us-west-2.compute.internal:60184] 15/03/27 13:50:47 INFO Utils: Successfully started service 'sparkDriver' on port 60184. 15/03/27 13:50:47 INFO SparkEnv: Registering MapOutputTracker 15/03/27 13:50:47 INFO SparkEnv: Registering BlockManagerMaster 15/03/27 13:50:47 INFO DiskBlockManager: Created local directory at /tmp/spark-local-20150327135047-5399 15/03/27 13:50:47 INFO MemoryStore: MemoryStore started with capacity 3.5 GB 15/03/27 13:50:47 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 15/03/27 13:50:47 INFO HttpFileServer: HTTP File server directory is /tmp/spark-7e26df49-1520-4c77-b411-c837da59fa5b 15/03/27 13:50:47 INFO HttpServer: Starting HTTP Server 15/03/27 13:50:47 INFO Utils: Successfully started service 'HTTP file server' on port 57955. 15/03/27 13:50:47 INFO Utils: Successfully started service 'SparkUI' on port 4040. 15/03/27 13:50:47 INFO SparkUI: Started SparkUI at http://ip-10-241-251-232.us-west-2.compute.internal:4040 15/03/27 13:50:47 INFO AppClient$ClientActor: Connecting to master spark://ip-10-241-251-232:7077... 15/03/27 13:50:48 INFO SparkDeploySchedulerBackend: Connected to Spark cluster with app ID app-20150327135048-0002 15/03/27 13:50:48 INFO NettyBlockTransferService: Server created on 58358 15/03/27 13:50:48 INFO BlockManagerMaster: Trying to register BlockManager 15/03/27 13:50:48 INFO BlockManagerMasterActor: Registering block manager ip-10-241-251-232.us-west-2.compute.internal:58358 with 3.5 GB RAM, BlockManagerId(<driver>, ip-10-241-251-232.us-west-2.compute.internal, 58358) 15/03/27 13:50:48 INFO BlockManagerMaster: Registered BlockManager 15/03/27 13:50:48 INFO SparkDeploySchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.0 15/03/27 13:50:48 INFO ReceiverTracker: ReceiverTracker started 15/03/27 13:50:48 INFO ForEachDStream: metadataCleanupDelay = -1 15/03/27 13:50:48 INFO ShuffledDStream: metadataCleanupDelay = -1 15/03/27 13:50:48 INFO MappedDStream: metadataCleanupDelay = -1 15/03/27 13:50:48 INFO FlatMappedDStream: metadataCleanupDelay = -1 15/03/27 13:50:48 INFO SocketInputDStream: metadataCleanupDelay = -1 15/03/27 13:50:48 INFO SocketInputDStream: Slide time = 1000 ms 15/03/27 13:50:48 INFO SocketInputDStream: Storage level = StorageLevel(false, false, false, false, 1) 15/03/27 13:50:48 INFO SocketInputDStream: Checkpoint interval = null 15/03/27 13:50:48 INFO SocketInputDStream: Remember duration = 1000 ms 15/03/27 13:50:48 INFO SocketInputDStream: Initialized and validated org.apache.spark.streaming.dstream.SocketInputDStream@75efa13d 15/03/27 13:50:48 INFO FlatMappedDStream: Slide time = 1000 ms 15/03/27 13:50:48 INFO FlatMappedDStream: Storage level = StorageLevel(false, false, false, false, 1) 15/03/27 13:50:48 INFO FlatMappedDStream: Checkpoint interval = null 15/03/27 13:50:48 INFO FlatMappedDStream: Remember duration = 1000 ms 15/03/27 13:50:48 INFO FlatMappedDStream: Initialized and validated org.apache.spark.streaming.dstream.FlatMappedDStream@65ce9dc5 15/03/27 13:50:48 INFO MappedDStream: Slide time = 1000 ms 15/03/27 13:50:48 INFO MappedDStream: Storage level = StorageLevel(false, false, false, false, 1) 15/03/27 13:50:48 INFO MappedDStream: Checkpoint interval = null 15/03/27 13:50:48 INFO MappedDStream: Remember duration = 1000 ms 15/03/27 13:50:48 INFO MappedDStream: Initialized and validated org.apache.spark.streaming.dstream.MappedDStream@5ae2740f 15/03/27 13:50:48 INFO ShuffledDStream: Slide time = 1000 ms 15/03/27 13:50:48 INFO ShuffledDStream: Storage level = StorageLevel(false, false, false, false, 1) 15/03/27 13:50:48 INFO ShuffledDStream: Checkpoint interval = null 15/03/27 13:50:48 INFO ShuffledDStream: Remember duration = 1000 ms 15/03/27 13:50:48 INFO ShuffledDStream: Initialized and validated org.apache.spark.streaming.dstream.ShuffledDStream@4931b366 15/03/27 13:50:48 INFO ForEachDStream: Slide time = 1000 ms 15/03/27 13:50:48 INFO ForEachDStream: Storage level = StorageLevel(false, false, false, false, 1) 15/03/27 13:50:48 INFO ForEachDStream: Checkpoint interval = null 15/03/27 13:50:48 INFO ForEachDStream: Remember duration = 1000 ms 15/03/27 13:50:48 INFO ForEachDStream: Initialized and validated org.apache.spark.streaming.dstream.ForEachDStream@5df91314 15/03/27 13:50:48 INFO SparkContext: Starting job: start at WordCount.java:26 15/03/27 13:50:48 INFO RecurringTimer: Started timer for JobGenerator at time 1427478649000 15/03/27 13:50:48 INFO JobGenerator: Started JobGenerator at 1427478649000 ms 15/03/27 13:50:48 INFO JobScheduler: Started JobScheduler 15/03/27 13:50:48 INFO DAGScheduler: Registering RDD 2 (start at WordCount.java:26) 15/03/27 13:50:48 INFO DAGScheduler: Got job 0 (start at WordCount.java:26) with 20 output partitions (allowLocal=false) 15/03/27 13:50:48 INFO DAGScheduler: Final stage: Stage 1(start at WordCount.java:26) 15/03/27 13:50:48 INFO DAGScheduler: Parents of final stage: List(Stage 0) 15/03/27 13:50:48 INFO DAGScheduler: Missing parents: List(Stage 0) 15/03/27 13:50:48 INFO DAGScheduler: Submitting Stage 0 (MappedRDD[2] at start at WordCount.java:26), which has no missing parents 15/03/27 13:50:48 INFO MemoryStore: ensureFreeSpace(2720) called with curMem=0, maxMem=3771948072 15/03/27 13:50:48 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 2.7 KB, free 3.5 GB) 15/03/27 13:50:48 INFO MemoryStore: ensureFreeSpace(1943) called with curMem=2720, maxMem=3771948072 15/03/27 13:50:48 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 1943.0 B, free 3.5 GB) 15/03/27 13:50:48 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on ip-10-241-251-232.us-west-2.compute.internal:58358 (size: 1943.0 B, free: 3.5 GB) 15/03/27 13:50:48 INFO BlockManagerMaster: Updated info of block broadcast_0_piece0 15/03/27 13:50:48 INFO SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:838 15/03/27 13:50:48 INFO DAGScheduler: Submitting 50 missing tasks from Stage 0 (MappedRDD[2] at start at WordCount.java:26) 15/03/27 13:50:48 INFO TaskSchedulerImpl: Adding task set 0.0 with 50 tasks 15/03/27 13:50:49 INFO JobScheduler: Added jobs for time 1427478649000 ms 15/03/27 13:50:49 INFO JobScheduler: Starting job streaming job 1427478649000 ms.0 from job set of time 1427478649000 ms 15/03/27 13:50:49 INFO SparkContext: Starting job: print at WordCount.java:53 15/03/27 13:50:49 INFO DAGScheduler: Registering RDD 6 (mapToPair at WordCount.java:39) 15/03/27 13:50:49 INFO DAGScheduler: Got job 1 (print at WordCount.java:53) with 1 output partitions (allowLocal=true) 15/03/27 13:50:49 INFO DAGScheduler: Final stage: Stage 3(print at WordCount.java:53) 15/03/27 13:50:49 INFO DAGScheduler: Parents of final stage: List(Stage 2) 15/03/27 13:50:49 INFO DAGScheduler: Missing parents: List() 15/03/27 13:50:49 INFO DAGScheduler: Submitting Stage 3 (ShuffledRDD[7] at reduceByKey at WordCount.java:46), which has no missing parents 15/03/27 13:50:49 INFO MemoryStore: ensureFreeSpace(2264) called with curMem=4663, maxMem=3771948072 15/03/27 13:50:49 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 2.2 KB, free 3.5 GB) 15/03/27 13:50:49 INFO MemoryStore: ensureFreeSpace(1688) called with curMem=6927, maxMem=3771948072 15/03/27 13:50:49 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 1688.0 B, free 3.5 GB) 15/03/27 13:50:49 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on ip-10-241-251-232.us-west-2.compute.internal:58358 (size: 1688.0 B, free: 3.5 GB) 15/03/27 13:50:49 INFO BlockManagerMaster: Updated info of block broadcast_1_piece0 15/03/27 13:50:49 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:838 15/03/27 13:50:49 INFO DAGScheduler: Submitting 1 missing tasks from Stage 3 (ShuffledRDD[7] at reduceByKey at WordCount.java:46) 15/03/27 13:50:49 INFO TaskSchedulerImpl: Adding task set 3.0 with 1 tasks 15/03/27 13:50:50 INFO JobScheduler: Added jobs for time 1427478650000 ms 15/03/27 13:50:51 INFO JobScheduler: Added jobs for time 1427478651000 ms 15/03/27 13:50:52 INFO JobScheduler: Added jobs for time 1427478652000 ms 15/03/27 13:50:53 IN On Thu, Mar 26, 2015 at 6:50 PM, Saisai Shao <sai.sai.s...@gmail.com> wrote: > Hi, > > Did you run the word count example in Spark local mode or other mode, in > local mode you have to set Local[n], where n >=2. For other mode, make sure > available cores larger than 1. Because the receiver inside Spark Streaming > wraps as a long-running task, which will at least occupy one core. > > Besides using lsof -p <pid> or netstat to make sure Spark executor backend > is connected to the nc process. Also grep the executor's log to see if > there's log like "Connecting to <host> <port>" and "Connected to <host> > <port>" which shows that receiver is correctly connected to nc process. > > Thanks > Jerry > > 2015-03-27 8:45 GMT+08:00 Mohit Anchlia <mohitanch...@gmail.com>: > >> What's the best way to troubleshoot inside spark to see why Spark is not >> connecting to nc on port 9999? I don't see any errors either. >> >> On Thu, Mar 26, 2015 at 2:38 PM, Mohit Anchlia <mohitanch...@gmail.com> >> wrote: >> >>> I am trying to run the word count example but for some reason it's not >>> working as expected. I start "nc" server on port 9999 and then submit the >>> spark job to the cluster. Spark job gets successfully submitting but I >>> never see any connection from spark getting established. I also tried to >>> type words on the console where "nc" is listening and waiting on the >>> prompt, however I don't see any output. I also don't see any errors. >>> >>> Here is the conf: >>> >>> SparkConf conf = *new* SparkConf().setMaster(masterUrl).setAppName( >>> "NetworkWordCount"); >>> >>> JavaStreamingContext *jssc* = *new* JavaStreamingContext(conf, >>> Durations.*seconds*(1)); >>> >>> JavaReceiverInputDStream<String> lines = jssc.socketTextStream( >>> "localhost", 9999); >>> >> >> >
