Scala 无法使用Spark流媒体应用程序查看Twitter流

我正在尝试使用Scala编写一个Spark流媒体应用程序，它应该按照提供的说明每秒读取Twitter提要

我的代码是：

import org.apache.spark._
import org.apache.spark.SparkContext._
import org.apache.spark.streaming._
import org.apache.spark.streaming.twitter._
import org.apache.spark.streaming.StreamingContext._
import TutorialHelper._

object Tutorial {
  def main(args: Array[String]) {

    // Checkpoint directory
    val checkpointDir = TutorialHelper.getCheckpointDirectory()

    // Configure Twitter credentials
    val apiKey = "blabla"
    val apiSecret = "blabla"
    val accessToken = "blabla"
    val accessTokenSecret = "blabla"
    TutorialHelper.configureTwitterCredentials(apiKey, apiSecret, accessToken, accessTokenSecret)

    val ssc = new StreamingContext(new SparkConf(), Seconds(1))

    val tweets = TwitterUtils.createStream(ssc, None)

    val statuses = tweets.map(status => status.getText())
    statuses.print()

    ssc.checkpoint(checkpointDir)

    ssc.start()
    ssc.awaitTermination()
  }
}

当我尝试执行时，使用spark submit会得到以下日志：

Configuring Twitter OAuth
    Property twitter4j.oauth.consumerKey set as [blabla]
    Property twitter4j.oauth.accessToken set as [blabla]
    Property twitter4j.oauth.consumerSecret set as [blabla]
    Property twitter4j.oauth.accessTokenSecret set as [blabla]

Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
15/09/28 13:22:11 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/09/28 13:22:11 WARN Utils: Your hostname, ubuntu resolves to a loopback address: 127.0.1.1; using 192.168.163.145 instead (on interface eth0)
15/09/28 13:22:11 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
15/09/28 13:22:13 INFO Slf4jLogger: Slf4jLogger started
15/09/28 13:22:13 INFO Remoting: Starting remoting
15/09/28 13:22:13 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriver@192.168.163.145:59422]
15/09/28 13:22:15 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
15/09/28 13:22:17 INFO WriteAheadLogManager : Recovered 1 write ahead log files from file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata
-------------------------------------------
Time: 1443471738000 ms
-------------------------------------------

15/09/28 13:22:18 INFO WriteAheadLogManager : Attempting to clear 1 old log files in file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata older than 1443471737000: file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata/log-1443468716010-1443468776010
15/09/28 13:22:18 INFO WriteAheadLogManager : Cleared log files in file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata older than 1443471737000
-------------------------------------------
Time: 1443471739000 ms
-------------------------------------------

15/09/28 13:22:19 INFO WriteAheadLogManager : Attempting to clear 0 old log files in file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata older than 1443471738000: 
15/09/28 13:22:19 INFO WriteAheadLogManager : Cleared log files in file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata older than 1443471738000
-------------------------------------------
Time: 1443471740000 ms
-------------------------------------------

15/09/28 13:22:20 INFO WriteAheadLogManager : Attempting to clear 0 old log files in file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata older than 1443471739000: 
15/09/28 13:22:20 INFO WriteAheadLogManager : Cleared log files in file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata older than 1443471739000
-------------------------------------------
Time: 1443471741000 ms
-------------------------------------------

15/09/28 13:22:21 INFO WriteAheadLogManager : Attempting to clear 0 old log files in file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata older than 1443471740000: 
15/09/28 13:22:21 INFO WriteAheadLogManager : Cleared log files in file:/home/nikos/Desktop/spark-1.5.0-bin-hadoop2.6/streaming/scala/checkpoint/receivedBlockMetadata older than 1443471740000
15/09/28 13:22:21 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
java.lang.AbstractMethodError
    at org.apache.spark.Logging$class.log(Logging.scala:52)
    at org.apache.spark.streaming.twitter.TwitterReceiver.log(TwitterInputDStream.scala:60)
    at org.apache.spark.Logging$class.logInfo(Logging.scala:59)
    at org.apache.spark.streaming.twitter.TwitterReceiver.logInfo(TwitterInputDStream.scala:60)
    at org.apache.spark.streaming.twitter.TwitterReceiver.onStart(TwitterInputDStream.scala:93)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.startReceiver(ReceiverSupervisor.scala:148)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.start(ReceiverSupervisor.scala:130)
    at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:542)
    at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:532)
    at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1975)
    at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1975)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:88)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)
15/09/28 13:22:21 INFO TwitterStreamImpl: Establishing connection.
15/09/28 13:22:21 ERROR SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[Executor task launch worker-0,5,main]
java.lang.AbstractMethodError
    at org.apache.spark.Logging$class.log(Logging.scala:52)
    at org.apache.spark.streaming.twitter.TwitterReceiver.log(TwitterInputDStream.scala:60)
    at org.apache.spark.Logging$class.logInfo(Logging.scala:59)
    at org.apache.spark.streaming.twitter.TwitterReceiver.logInfo(TwitterInputDStream.scala:60)
    at org.apache.spark.streaming.twitter.TwitterReceiver.onStart(TwitterInputDStream.scala:93)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.startReceiver(ReceiverSupervisor.scala:148)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.start(ReceiverSupervisor.scala:130)
    at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:542)
    at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:532)
    at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1975)
    at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1975)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:88)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)
15/09/28 13:22:21 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.AbstractMethodError
    at org.apache.spark.Logging$class.log(Logging.scala:52)
    at org.apache.spark.streaming.twitter.TwitterReceiver.log(TwitterInputDStream.scala:60)
    at org.apache.spark.Logging$class.logInfo(Logging.scala:59)
    at org.apache.spark.streaming.twitter.TwitterReceiver.logInfo(TwitterInputDStream.scala:60)
    at org.apache.spark.streaming.twitter.TwitterReceiver.onStart(TwitterInputDStream.scala:93)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.startReceiver(ReceiverSupervisor.scala:148)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.start(ReceiverSupervisor.scala:130)
    at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:542)
    at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$9.apply(ReceiverTracker.scala:532)
    at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1975)
    at org.apache.spark.SparkContext$$anonfun$37.apply(SparkContext.scala:1975)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:88)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)

15/09/28 13:22:21 ERROR ActorSystemImpl: Uncaught fatal error from thread [sparkDriver-akka.actor.default-dispatcher-7] shutting down ActorSystem [sparkDriver]
java.lang.AbstractMethodError
    at org.apache.spark.Logging$class.log(Logging.scala:52)
    at org.apache.spark.streaming.twitter.TwitterReceiver.log(TwitterInputDStream.scala:60)
    at org.apache.spark.Logging$class.logInfo(Logging.scala:59)
    at org.apache.spark.streaming.twitter.TwitterReceiver.logInfo(TwitterInputDStream.scala:60)
    at org.apache.spark.streaming.twitter.TwitterReceiver.onStop(TwitterInputDStream.scala:101)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.stopReceiver(ReceiverSupervisor.scala:169)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.stop(ReceiverSupervisor.scala:136)
    at org.apache.spark.streaming.receiver.ReceiverSupervisorImpl$$anon$2$$anonfun$receive$1.applyOrElse(ReceiverSupervisorImpl.scala:79)
    at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$processMessage(AkkaRpcEnv.scala:177)
    at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1$$anonfun$applyOrElse$4.apply$mcV$sp(AkkaRpcEnv.scala:126)
    at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$safelyCall(AkkaRpcEnv.scala:197)
    at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1.applyOrElse(AkkaRpcEnv.scala:125)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
    at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:59)
    at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:42)
    at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
    at org.apache.spark.util.ActorLogReceive$$anon$1.applyOrElse(ActorLogReceive.scala:42)
    at akka.actor.Actor$class.aroundReceive(Actor.scala:467)
    at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1.aroundReceive(AkkaRpcEnv.scala:92)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
    at akka.actor.ActorCell.invoke(ActorCell.scala:487)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
    at akka.dispatch.Mailbox.run(Mailbox.scala:220)
    at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
    at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
    at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
    at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
15/09/28 13:22:21 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
15/09/28 13:22:21 ERROR ErrorMonitor: Uncaught fatal error from thread [sparkDriver-akka.actor.default-dispatcher-7] shutting down ActorSystem [sparkDriver]
java.lang.AbstractMethodError
    at org.apache.spark.Logging$class.log(Logging.scala:52)
    at org.apache.spark.streaming.twitter.TwitterReceiver.log(TwitterInputDStream.scala:60)
    at org.apache.spark.Logging$class.logInfo(Logging.scala:59)
    at org.apache.spark.streaming.twitter.TwitterReceiver.logInfo(TwitterInputDStream.scala:60)
    at org.apache.spark.streaming.twitter.TwitterReceiver.onStop(TwitterInputDStream.scala:101)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.stopReceiver(ReceiverSupervisor.scala:169)
    at org.apache.spark.streaming.receiver.ReceiverSupervisor.stop(ReceiverSupervisor.scala:136)
    at org.apache.spark.streaming.receiver.ReceiverSupervisorImpl$$anon$2$$anonfun$receive$1.applyOrElse(ReceiverSupervisorImpl.scala:79)
    at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$processMessage(AkkaRpcEnv.scala:177)
    at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1$$anonfun$applyOrElse$4.apply$mcV$sp(AkkaRpcEnv.scala:126)
    at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$safelyCall(AkkaRpcEnv.scala:197)
    at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1.applyOrElse(AkkaRpcEnv.scala:125)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
    at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:59)
    at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:42)
    at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
    at org.apache.spark.util.ActorLogReceive$$anon$1.applyOrElse(ActorLogReceive.scala:42)
    at akka.actor.Actor$class.aroundReceive(Actor.scala:467)
    at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1.aroundReceive(AkkaRpcEnv.scala:92)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
    at akka.actor.ActorCell.invoke(ActorCell.scala:487)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
    at akka.dispatch.Mailbox.run(Mailbox.scala:220)
    at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
    at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
    at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
    at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
15/09/28 13:22:21 WARN ReceiverTracker: Receiver 0 exited but didn't deregister
15/09/28 13:22:21 INFO WriteAheadLogManager : Stopped write ahead log manager
15/09/28 13:22:22 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
15/09/28 13:22:22 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
15/09/28 13:22:22 WARN AkkaRpcEndpointRef: Error sending message [message = RemoveBroadcast(0,true)] in 1 attempts
org.apache.spark.rpc.RpcTimeoutException: Recipient[Actor[akka://sparkDriver/user/BlockManagerMaster#1080029491]] had already been terminated.. This timeout is controlled by spark.rpc.askTimeout
    at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcEnv.scala:214)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcEnv.scala:229)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcEnv.scala:225)
    at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
    at scala.util.Failure$$anonfun$recover$1.apply(Try.scala:185)
    at scala.util.Try$.apply(Try.scala:161)
    at scala.util.Failure.recover(Try.scala:185)
    at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324)
    at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324)
    at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
    at org.spark-project.guava.util.concurrent.MoreExecutors$SameThreadExecutorService.execute(MoreExecutors.java:293)
    at scala.concurrent.impl.ExecutionContextImpl$$anon$1.execute(ExecutionContextImpl.scala:133)
    at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40)
    at scala.concurrent.impl.Promise$DefaultPromise.scala$concurrent$impl$Promise$DefaultPromise$$dispatchOrAddCallback(Promise.scala:280)
    at scala.concurrent.impl.Promise$DefaultPromise.onComplete(Promise.scala:270)
    at scala.concurrent.Future$class.recover(Future.scala:324)
    at scala.concurrent.impl.Promise$DefaultPromise.recover(Promise.scala:153)
    at org.apache.spark.rpc.akka.AkkaRpcEndpointRef.ask(AkkaRpcEnv.scala:319)
    at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:100)
    at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:77)
    at org.apache.spark.storage.BlockManagerMaster.removeBroadcast(BlockManagerMaster.scala:128)
    at org.apache.spark.broadcast.TorrentBroadcast$.unpersist(TorrentBroadcast.scala:228)
    at org.apache.spark.broadcast.TorrentBroadcastFactory.unbroadcast(TorrentBroadcastFactory.scala:45)
    at org.apache.spark.broadcast.BroadcastManager.unbroadcast(BroadcastManager.scala:67)
    at org.apache.spark.ContextCleaner.doCleanupBroadcast(ContextCleaner.scala:214)
    at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1$$anonfun$apply$mcV$sp$2.apply(ContextCleaner.scala:170)
    at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1$$anonfun$apply$mcV$sp$2.apply(ContextCleaner.scala:161)
    at scala.Option.foreach(Option.scala:236)
    at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply$mcV$sp(ContextCleaner.scala:161)
    at org.apache.spark.util.Utils$.tryOrStopSparkContext(Utils.scala:1136)
    at org.apache.spark.ContextCleaner.org$apache$spark$ContextCleaner$$keepCleaning(ContextCleaner.scala:154)
    at org.apache.spark.ContextCleaner$$anon$3.run(ContextCleaner.scala:67)
Caused by: akka.pattern.AskTimeoutException: Recipient[Actor[akka://sparkDriver/user/BlockManagerMaster#1080029491]] had already been terminated.
    at akka.pattern.AskableActorRef$.ask$extension(AskSupport.scala:132)
    at org.apache.spark.rpc.akka.AkkaRpcEndpointRef.ask(AkkaRpcEnv.scala:307)
    ... 14 more

---

这一问题也得到了以下答复：

可以通过更改build.sbt中的ScalarAversion和libraryDependencies来解决此问题，以匹配Spark版本

e、 g:

确保使用新生成的scala-2.11类，例如：

。/../../../../../spark-1.6.1/bin/spark-submit——课堂教程/用户/mendezr/development/spark/exercises\u spark\u submit\u 2014/usb/streaming/scala/target/scala-2.11/Tutorial-assembly-0.1-SNAPSHOT.jar

• 对于spark 1.6.x，请使用scala2.10.6版本，并确保已在build.sbt文件中设置该版本

• 确保您的主机名链接到linux中的当前IP 主机在/etc/hosts文件中解析

---

同样的错误，@nikos，您解决了这个问题吗？

scalaVersion := "2.11.8"

libraryDependencies ++= Seq(
  "org.apache.spark" %% "spark-streaming" % "1.6.1" % "provided",
  "org.apache.spark" %% "spark-streaming-twitter" % "1.6.1"
 )