Apache spark 无法编写语句
我将spark与cassandra一起使用，我想将数据写入我的cassandra表：Apache spark 无法编写语句,apache-spark,cassandra-2.0,datastax,Apache Spark,Cassandra 2.0,Datastax,我将spark与cassandra一起使用，我想将数据写入我的cassandra表： CREATE TABLE IF NOT EXISTS MyTable( user TEXT, date TIMESTAMP, event TEXT, PRIMARY KEY((user ),date , event) ); 但我有一个错误： java.io.IOException: Failed to write statements to KeySpace.MyTable. at co
CREATE TABLE IF NOT EXISTS MyTable(
user TEXT,
date TIMESTAMP,
event TEXT,
PRIMARY KEY((user ),date , event)
);
java.io.IOException: Failed to write statements to KeySpace.MyTable.
at com.datastax.spark.connector.writer.TableWriter$$anonfun$write$1.apply(TableWriter.scala:145)
at com.datastax.spark.connector.writer.TableWriter$$anonfun$write$1.apply(TableWriter.scala:120)
at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$withSessionDo$1.apply(CassandraConnector.scala:100)
at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$withSessionDo$1.apply(CassandraConnector.scala:99)
at com.datastax.spark.connector.cql.CassandraConnector.closeResourceAfterUse(CassandraConnector.scala:151)
at com.datastax.spark.connector.cql.CassandraConnector.withSessionDo(CassandraConnector.scala:99)
at com.datastax.spark.connector.writer.TableWriter.write(TableWriter.scala:120)
at com.datastax.spark.connector.RDDFunctions$$anonfun$saveToCassandra$1.apply(RDDFunctions.scala:36)
at com.datastax.spark.connector.RDDFunctions$$anonfun$saveToCassandra$1.apply(RDDFunctions.scala:36)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)
at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)
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$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
15/04/28 17:57:47 WARN TaskSetManager: Lost task 13.2 in stage 1.0 (TID 43, dev2-cim.aid.fr): TaskKilled (killed intentionally)
Failed to execute:
com.datastax.spark.connector.writer.RichBatchStatement@67827d57
com.datastax.driver.core.exceptions.InvalidQueryException: Key may not be empty
at com.datastax.driver.core.Responses$Error.asException(Responses.java:103)
at com.datastax.driver.core.DefaultResultSetFuture.onSet(DefaultResultSetFuture.java:140)
at com.datastax.driver.core.RequestHandler.setFinalResult(RequestHandler.java:293)
at com.datastax.driver.core.RequestHandler.onSet(RequestHandler.java:455)
at com.datastax.driver.core.Connection$Dispatcher.messageReceived(Connection.java:734)
at org.jboss.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:70)
at org.jboss.netty.handler.timeout.IdleStateAwareChannelUpstreamHandler.handleUpstream(IdleStateAwareChannelUpstreamHandler.java:36)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.jboss.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
at org.jboss.netty.handler.timeout.IdleStateHandler.messageReceived(IdleStateHandler.java:294)
at org.jboss.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:70)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.jboss.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:296)
at org.jboss.netty.handler.codec.oneone.OneToOneDecoder.handleUpstream(OneToOneDecoder.java:70)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.jboss.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:296)
at org.jboss.netty.handler.codec.frame.FrameDecoder.unfoldAndFireMessageReceived(FrameDecoder.java:462)
at org.jboss.netty.handler.codec.frame.FrameDecoder.callDecode(FrameDecoder.java:443)
at org.jboss.netty.handler.codec.frame.FrameDecoder.messageReceived(FrameDecoder.java:303)
at org.jboss.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:70)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:559)
at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:268)
at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:255)
at org.jboss.netty.channel.socket.nio.NioWorker.read(NioWorker.java:88)
WARN [SharedPool-Worker-2] 2015-04-28 16:45:21,219 BatchStatement.java:243 - Batch of prepared statements for [*********] is of size 8158, exceeding specified threshold of 5120 by 3038
conf.set("spark.cassandra.output.batch.grouping.key", "None")
conf.set("spark.cassandra.output.batch.size.rows", "10")
conf.set("spark.cassandra.output.batch.size.bytes", "2048")
无法写入语句java.io.IOException: Failed to write statements to KeySpace.MyTable.
at com.datastax.spark.connector.writer.TableWriter$$anonfun$write$1.apply(TableWriter.scala:145)
at com.datastax.spark.connector.writer.TableWriter$$anonfun$write$1.apply(TableWriter.scala:120)
at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$withSessionDo$1.apply(CassandraConnector.scala:100)
at com.datastax.spark.connector.cql.CassandraConnector$$anonfun$withSessionDo$1.apply(CassandraConnector.scala:99)
at com.datastax.spark.connector.cql.CassandraConnector.closeResourceAfterUse(CassandraConnector.scala:151)
at com.datastax.spark.connector.cql.CassandraConnector.withSessionDo(CassandraConnector.scala:99)
at com.datastax.spark.connector.writer.TableWriter.write(TableWriter.scala:120)
at com.datastax.spark.connector.RDDFunctions$$anonfun$saveToCassandra$1.apply(RDDFunctions.scala:36)
at com.datastax.spark.connector.RDDFunctions$$anonfun$saveToCassandra$1.apply(RDDFunctions.scala:36)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)
at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)
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$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
15/04/28 17:57:47 WARN TaskSetManager: Lost task 13.2 in stage 1.0 (TID 43, dev2-cim.aid.fr): TaskKilled (killed intentionally)
Failed to execute:
com.datastax.spark.connector.writer.RichBatchStatement@67827d57
com.datastax.driver.core.exceptions.InvalidQueryException: Key may not be empty
at com.datastax.driver.core.Responses$Error.asException(Responses.java:103)
at com.datastax.driver.core.DefaultResultSetFuture.onSet(DefaultResultSetFuture.java:140)
at com.datastax.driver.core.RequestHandler.setFinalResult(RequestHandler.java:293)
at com.datastax.driver.core.RequestHandler.onSet(RequestHandler.java:455)
at com.datastax.driver.core.Connection$Dispatcher.messageReceived(Connection.java:734)
at org.jboss.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:70)
at org.jboss.netty.handler.timeout.IdleStateAwareChannelUpstreamHandler.handleUpstream(IdleStateAwareChannelUpstreamHandler.java:36)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.jboss.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
at org.jboss.netty.handler.timeout.IdleStateHandler.messageReceived(IdleStateHandler.java:294)
at org.jboss.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:70)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.jboss.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:296)
at org.jboss.netty.handler.codec.oneone.OneToOneDecoder.handleUpstream(OneToOneDecoder.java:70)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.jboss.netty.channel.DefaultChannelPipeline$DefaultChannelHandlerContext.sendUpstream(DefaultChannelPipeline.java:791)
at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:296)
at org.jboss.netty.handler.codec.frame.FrameDecoder.unfoldAndFireMessageReceived(FrameDecoder.java:462)
at org.jboss.netty.handler.codec.frame.FrameDecoder.callDecode(FrameDecoder.java:443)
at org.jboss.netty.handler.codec.frame.FrameDecoder.messageReceived(FrameDecoder.java:303)
at org.jboss.netty.channel.SimpleChannelUpstreamHandler.handleUpstream(SimpleChannelUpstreamHandler.java:70)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:564)
at org.jboss.netty.channel.DefaultChannelPipeline.sendUpstream(DefaultChannelPipeline.java:559)
at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:268)
at org.jboss.netty.channel.Channels.fireMessageReceived(Channels.java:255)
at org.jboss.netty.channel.socket.nio.NioWorker.read(NioWorker.java:88)
我通过重新启动集群作为节点解决了这个问题。 以下是我尝试过的事情。 我也面临同样的问题，我尝试了你在博客中提到的所有选项，但没有成功。 我的数据大小是174gb。总共174 Gb数据，我的群集有3个节点，每个节点有16个核心和48 Gb ram。 我试图在一次拍摄中获得174gb的空间，当时我也遇到了同样的问题。 在那之后，我将109个文件中的174 gb分隔为每个1.6 gb，并尝试隐藏，这次在加载100个文件（每个1.6 gb）后，我再次面临同样的问题。 我想可能是101文件中的数据有问题。我尝试加载第一个文件，尝试将第一个文件放入新表中，并尝试将新数据放入新表中，但所有这些情况都存在问题。 然后我认为这是cassandra集群的问题，并重新启动了集群和节点。
然后问题消失了。我也遇到了同样的问题，并在上面的评论中找到了解决方案（Amine CHERIFI和maasg） 与主键对应的列并不总是用正确的值填充（在我的例子中是空字符串“”） 这触发了错误
ERROR QueryExecutor: Failed to execute: \
com.datastax.spark.connector.writer.RichBatchStatement@26ad2668 \
com.datastax.driver.core.exceptions.InvalidQueryException: Key may not be empty
在我的例子中，我的键空间的复制系数是2，但我只有一个处于活动状态。如果您在纱线集群模式下运行，请不要忘记使用
纱线日志-applicationId--appOwner检查整个纱线登录。
这给了我比webUI上的日志更多的失败原因
Caused by: com.datastax.driver.core.exceptions.UnavailableException: Not enough replicas available for query at consistency LOCAL_QUORUM (2 required but only 1 alive)
at com.datastax.driver.core.Responses$Error$1.decode(Responses.java:50)
at com.datastax.driver.core.Responses$Error$1.decode(Responses.java:37)
at com.datastax.driver.core.Message$ProtocolDecoder.decode(Message.java:266)
at com.datastax.driver.core.Message$ProtocolDecoder.decode(Message.java:246)
at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:89)
... 11 more
解决方案是在故障留下的堆栈跟踪中，在spark defaults.conf中设置spark.cassandra.output.consistency.level=ANY
，您看到原因了吗？警告可能与此无关。我只是编辑了我的帖子以显示堆栈跟踪。但是我在堆栈跟踪中没有看到原因。我在spark:InvalidQueryException:Key可能不是空的日志文件中找到了这个原因。这更具体、更明确：批处理中的某些行包含无效数据。你能显示代码吗？是的，谢谢。这只是我的错，我有6行，用户为空/空。感谢您的帮助理想的spark.cassandra.output.batch.grouping.buffer.size应该是什么？如何计算呢？