私はsparkとcassandraの新機能です。私は、データストアで提供されているspark-cassandra-connectorを使用して、新しい行をcassandraテーブルに追加しようとしている単純なjavaプログラムを試しています。ローカルのspark-cassandraコネクタがSparkクラスタを表示します
私はラップトップコンピュータでdseを実行しています。 Javaを使用して、私はスパークを介してデータをcassandra DBに保存しようとしています。され、次のコード：
：あなたはスパークの設定を修正する必要があるように私はこのコードを実行すると、私は次のよう
Map<String, String> extra = new HashMap<String, String>();
extra.put("city", "bangalore");
extra.put("dept", "software");
List<User> products = Arrays.asList(new User(1, "vamsi", extra));
JavaRDD<User> productsRDD = sc.parallelize(products);
javaFunctions(productsRDD, User.class).saveToCassandra("test", "users");
を取得していますエラー
16/03/26 20:57:31 INFO client.AppClient$ClientActor: Connecting to master spark://127.0.0.1:7077... 16/03/26 20:57:44 WARN scheduler.TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient memory 16/03/26 20:57:51 INFO client.AppClient$ClientActor: Connecting to master spark://127.0.0.1:7077... 16/03/26 20:57:59 WARN scheduler.TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient memory 16/03/26 20:58:11 ERROR client.AppClient$ClientActor: All masters are unresponsive! Giving up. 16/03/26 20:58:11 ERROR cluster.SparkDeploySchedulerBackend: Spark cluster looks dead, giving up. 16/03/26 20:58:11 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 16/03/26 20:58:11 INFO scheduler.DAGScheduler: Failed to run runJob at RDDFunctions.scala:48 Exception in thread "main" org.apache.spark.SparkException: Job aborted: Spark cluster looks down at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1020) at org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1018) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$abortStage(DAGScheduler.scala:1018) at org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:604) at org.apache.spark.scheduler.DAGScheduler$$anonfun$processEvent$10.apply(DAGScheduler.scala:604) at scala.Option.foreach(Option.scala:236) at org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:604) at org.apache.spark.scheduler.DAGScheduler$$anonfun$start$1$$anon$2$$anonfun$receive$1.applyOrElse(DAGScheduler.scala:190) at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498) at akka.actor.ActorCell.invoke(ActorCell.scala:456) at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237) at akka.dispatch.Mailbox.run(Mailbox.scala:219) at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386) 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)