编写语句失败

时间：2015-04-28 16:09:47

标签： apache-spark cassandra-2.0 datastax

我正在使用带cassandra的spark，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)
);

但我收到了这个错误：

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)

并在我的Cassandra日志文件中发出此警告：

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

在互联网上进行一些搜索后，我发现这个链接解释了他如何解决同样的问题： http://progexc.blogspot.fr/2015/03/write-batch-size-error-spark-cassandra.html

所以，现在我修改了我的火花算法来添加：

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")

此值删除我在cassandra Logs中收到的警告消息，但我仍然有同样的错误：Failed to write statements。

在我的火花日志失败中，我发现了这个错误：

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)

4 个答案:

答案 0 :(得分：3)

我遇到了同样的问题，并在上​​面的评论中找到了解决方案（由Amine CHERIFI和maasg提供）。

与主键对应的列并不总是填充适当的值（在我的情况下使用空字符串＆＃34;＆＃34;）。

这触发了ERROR 

ERROR QueryExecutor: Failed to execute: \
com.datastax.spark.connector.writer.RichBatchStatement@26ad2668 \
com.datastax.driver.core.exceptions.InvalidQueryException: Key may not be empty

解决方案是提供默认的非空字符串。

答案 1 :(得分：3)

如果您在纱线群集模式下运行，请不要忘记使用yarn logs -applicationId <appId> --appOwner <appOwner>检查整个登录纱线。 这给了我更多的失败原因，而不是纱线webUI上的日志

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spark-defaults.conf中设置spark.cassandra.output.consistency.level=ANY

答案 2 :(得分：0)

我通过重新启动我的群集解决了这个问题。 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。 我的数据大小为174gb。总共174 Gb数据，我的集群有3个节点，每个节点有16个核心和48 GB RAM。 当时我试图在一次拍摄中使用174gb，我有同样的问题。 之后，我在每个1.6 Gb的109个文件中隔离了174 gb并尝试了lode，这次我在加载100个文件（每个1.6 gb）后再次面临同样的问题。 我认为可能是101文件中的数据有问题。我试图加载第一个文件并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，但所有这些情况都有问题。 然后我认为这是cassandra集群的问题，并重新启动集群和节点。 然后问题消失了。

答案 3 :(得分：0)

在＆＃34; com / datastax / spark / connector / writer / AsyncExecutor.scala：45＆＃34;中添加断点，您可以获得真正的异常。

就我而言，我的键空间的replication_factor是2，但我只有一个活着。

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