spark创建外部表时报错

环境如下:

vi /hadoop/spark/conf/spark-env.sh
export SPARK_CLASSPATH="/hadoop/spark/lib/mysql-connector-java.jar:/hadoop/spark/lib/sequoiadb-driver-1.12.jar:/hadoop/spark/lib/spark-sequoiadb_2.10-1.12.0.jar"
复制代码

在创建外部临时表时报错如下:

scala> sqlContext.sql("CREATE temporary table foobar USING com.sequoiadb.spark OPTIONS ( host 'master:11810,node1:11810,node2:11810', collectionspace 'foo', collection 'bar')")
16/06/14 18:22:52 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
java.lang.RuntimeException: Failed to load class for data source: com.sequoiadb.spark
at scala.sys.package$.error(package.scala:27)
at org.apache.spark.sql.sources.ResolvedDataSource$.lookupDataSource(ddl.scala:220)
at org.apache.spark.sql.sources.ResolvedDataSource$.apply(ddl.scala:233)
at org.apache.spark.sql.sources.CreateTempTableUsing.run(ddl.scala:412)
at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:57)
at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:57)
at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:68)
at org.apache.spark.sql.execution.SparkPlan$anonfun$execute$1.apply(SparkPlan.scala:88)
at org.apache.spark.sql.execution.SparkPlan$anonfun$execute$1.apply(SparkPlan.scala:88)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:87)
at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:950)
at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:950)
at org.apache.spark.sql.DataFrame.(DataFrame.scala:144)
at org.apache.spark.sql.DataFrame.(DataFrame.scala:128)
at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:755)
at $iwC$iwC$iwC$iwC$iwC$iwC$iwC$iwC.(:20)
at $iwC$iwC$iwC$iwC$iwC$iwC$iwC.(:25)
at $iwC$iwC$iwC$iwC$iwC$iwC.(:27)
at $iwC$iwC$iwC$iwC$iwC.(:29)
at $iwC$iwC$iwC$iwC.(:31)
at $iwC$iwC$iwC.(:33)
at $iwC$iwC.(:35)
at $iwC.(:37)
at (:39)
at .(:43)
at .()
at .(:7)
at .()
at $print()
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$loop(SparkILoop.scala:670)
at org.apache.spark.repl.SparkILoop$anonfun$org$apache$spark$repl$SparkILoop$process$1.apply$mcZ$sp(SparkILoop.scala:997)
at org.apache.spark.repl.SparkILoop$anonfun$org$apache$spark$repl$SparkILoop$process$1.apply(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop$anonfun$org$apache$spark$repl$SparkILoop$process$1.apply(SparkILoop.scala:945)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$process(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$runMain(SparkSubmit.scala:665)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:170)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:193)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:112)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

2个回答

可能是scala驱动版本不匹配

恩恩,是的,就是scala版本不匹配

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在scala编写spark程序使用了sc.textFile("file:///home/hadoop/2.txt"), 竟然报错java.io.FileNotFoundException: File file:/home/hadoop/2.txt does not exist,之后又用spark-shell测试,依旧报这样错误 ``` scala> val rdd = sc.textFile("file:///home/hadoop/2.txt") rdd: org.apache.spark.rdd.RDD[String] = file:///home/hadoop/2.txt MapPartitionsRDD[5] at textFile at <console>:24 scala> rdd.take(1) 17/08/29 20:27:28 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 1.0 (TID 4, slaves3, executor 2): java.io.FileNotFoundException: File file:/home/hadoop/2.txt does not exist ``` 我cat文件是有输出的 ``` [hadoop@master ~]$ cat /home/hadoop/2.txt chen 001 {"phone":"187***","sex":"m","card":"123"} zhou 002 {"phone":"187***","sex":"f","educetion":"1"} qian 003 {"phone":"187***","sex":"f","book":"2"} li 004 {"phone":"187***","sex":"f"} wu 005 {"phone":"187***","sex":"f"} zhang 006 {"phone":"187***","sex":"f"} xia 007 {"phone":"187***","sex":"f"} wang 008 {"phone":"187***","sex":"f"} lv 009 {"phone":"187***","sex":"m"} ``` 之后我将文件放在hdfs上面,就能读取的到,这是怎么回事

CDH 集群安装kafka和spark2后重启后报错 Connection refused to https://archive.cloudera.com/cdh5/parcels/5.16/manifest.json

CDH 集群安装kafka和spark2后重启后报错如下: 020-05-12 18:33:55,318 ERROR ParcelUpdateService:com.cloudera.parcel.components.ParcelDownloaderImpl: Unable to retrieve remote parcel repository manifest java.util.concurrent.ExecutionException: java.net.ConnectException: Connection refused to https://archive.cloudera.com/cdh5/parcels/5.16/manifest.json at com.ning.http.client.providers.netty.NettyResponseFuture.abort(NettyResponseFuture.java:297) at com.ning.http.client.providers.netty.NettyConnectListener.operationComplete(NettyConnectListener.java:104) at org.jboss.netty.channel.DefaultChannelFuture.notifyListener(DefaultChannelFuture.java:399) at org.jboss.netty.channel.DefaultChannelFuture.notifyListeners(DefaultChannelFuture.java:390) at org.jboss.netty.channel.DefaultChannelFuture.setFailure(DefaultChannelFuture.java:352) at org.jboss.netty.channel.socket.nio.NioClientSocketPipelineSink$Boss.connect(NioClientSocketPipelineSink.java:409) at org.jboss.netty.channel.socket.nio.NioClientSocketPipelineSink$Boss.processSelectedKeys(NioClientSocketPipelineSink.java:366) at org.jboss.netty.channel.socket.nio.NioClientSocketPipelineSink$Boss.run(NioClientSocketPipelineSink.java:282) at org.jboss.netty.util.ThreadRenamingRunnable.run(ThreadRenamingRunnable.java:102) at org.jboss.netty.util.internal.DeadLockProofWorker$1.run(DeadLockProofWorker.java:42) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Caused by: java.net.ConnectException: Connection refused to https://archive.cloudera.com/cdh5/parcels/5.16/manifest.json at com.ning.http.client.providers.netty.NettyConnectListener.operationComplete(NettyConnectListener.java:100) ... 11 more Caused by: java.net.ConnectException: Connection refused at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method) at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717) at org.jboss.netty.channel.socket.nio.NioClientSocketPipelineSink$Boss.connect(NioClientSocketPipelineSink.java:404) at org.jboss.netty.channel.socket.nio.NioClientSocketPipelineSink$Boss.processSelectedKeys(NioClientSocketPipelineSink.java:366) at org.jboss.netty.channel.socket.nio.NioClientSocketPipelineSink$Boss.run(NioClientSocketPipelineSink.java:282) ... 3 more 求大神指点

spark jdbc连接impala报错Method not supported

各位好 我的spark是2.1.0,用的hive-jdbc 2.1.0,现在写入impala的时候报以下错: java.sql.SQLException: Method not supported at org.apache.hive.jdbc.HivePreparedStatement.addBatch(HivePreparedStatement.java:75) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:589) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:670) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:670) at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:925) at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:925) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322) 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$$failJobAndIndependentStages(DAGScheduler.scala:1435) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944) at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958) at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:925) at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:923) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:362) at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:923) at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply$mcV$sp(Dataset.scala:2305) at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply(Dataset.scala:2305) at org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply(Dataset.scala:2305) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765) at org.apache.spark.sql.Dataset.foreachPartition(Dataset.scala:2304) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.saveTable(JdbcUtils.scala:670) at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:77) at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:518) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:215) at org.apache.spark.sql.DataFrameWriter.jdbc(DataFrameWriter.scala:446) at com.aoyou.data.CustomerVisitProduct$.saveToHive(CustomerVisitProduct.scala:281) at com.aoyou.data.CustomerVisitProduct$.main(CustomerVisitProduct.scala:221) at com.aoyou.data.CustomerVisitProduct.main(CustomerVisitProduct.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:497) at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:738) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) Caused by: java.sql.SQLException: Method not supported at org.apache.hive.jdbc.HivePreparedStatement.addBatch(HivePreparedStatement.java:75) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:589) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:670) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:670) at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:925) at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$29.apply(RDD.scala:925) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1944) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322) 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) 以下是代码实现 val sparkConf = new SparkConf().setAppName("save").set("spark.sql.crossJoin.enabled", "true"); val sparkSession = SparkSession .builder() .enableHiveSupport() .getOrCreate(); val dataframe = sparkSession.createDataFrame(rddSchema, new Row().getClass()) val property = new Properties(); property.put("user", "xxxxx") property.put("password", "xxxxx") dataframe.write.mode(SaveMode.Append).option("driver", "org.apache.hive.jdbc.HiveDriver").jdbc("jdbc:hive2://xxxx:21050/rawdata;auth=noSasl", "tablename", property) 请问这是怎么回事啊?感觉是驱动版本问题

急!!!!CM配置hive on spark后执行总是报错

急求大神抬一手。。。。。 2017-11-10 14:50:13,485 INFO [main]: ql.Driver (SessionState.java:printInfo(986)) - Launching Job 3 out of 5 2017-11-10 14:50:13,485 INFO [main]: ql.Driver (Driver.java:launchTask(1977)) - Starting task [Stage-1:MAPRED] in serial mode 2017-11-10 14:50:13,485 INFO [main]: exec.Task (SessionState.java:printInfo(986)) - In order to change the average load for a reducer (in bytes): 2017-11-10 14:50:13,486 INFO [main]: exec.Task (SessionState.java:printInfo(986)) - set hive.exec.reducers.bytes.per.reducer=<number> 2017-11-10 14:50:13,486 INFO [main]: exec.Task (SessionState.java:printInfo(986)) - In order to limit the maximum number of reducers: 2017-11-10 14:50:13,486 INFO [main]: exec.Task (SessionState.java:printInfo(986)) - set hive.exec.reducers.max=<number> 2017-11-10 14:50:13,486 INFO [main]: exec.Task (SessionState.java:printInfo(986)) - In order to set a constant number of reducers: 2017-11-10 14:50:13,486 INFO [main]: exec.Task (SessionState.java:printInfo(986)) - set mapreduce.job.reduces=<number> 2017-11-10 14:50:13,676 INFO [main]: exec.Task (SessionState.java:printInfo(986)) - Starting Spark Job = d2163859-72ee-4a25-8e27-e566d8ab548c 2017-11-10 14:51:06,982 WARN [RPC-Handler-3]: client.SparkClientImpl (SparkClientImpl.java:rpcClosed(131)) - Client RPC channel closed unexpectedly. 2017-11-10 14:52:06,901 ```**WARN [main]: impl.RemoteSparkJobStatus (RemoteSparkJobStatus.java:getSparkJobInfo(152)) - Failed to get job info. java.util.concurrent.TimeoutException** at io.netty.util.concurrent.AbstractFuture.get(AbstractFuture.java:49)``` at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobStatus.getSparkJobInfo(RemoteSparkJobStatus.java:150) at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobStatus.getState(RemoteSparkJobStatus.java:82) at org.apache.hadoop.hive.ql.exec.spark.status.RemoteSparkJobMonitor.startMonitor(RemoteSparkJobMonitor.java:80) at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobRef.monitorJob(RemoteSparkJobRef.java:60) at org.apache.hadoop.hive.ql.exec.spark.SparkTask.execute(SparkTask.java:109) at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:214) at org.apache.hadoop.hive.ql.exec.TaskRunner.runSequential(TaskRunner.java:100) at org.apache.hadoop.hive.ql.Driver.launchTask(Driver.java:1979) at org.apache.hadoop.hive.ql.Driver.execute(Driver.java:1692) at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1424) at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1208) at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1198) at org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:220) at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:172) at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:383) at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:318) at org.apache.hadoop.hive.cli.CliDriver.executeDriver(CliDriver.java:720) at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:693) at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:628) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at org.apache.hadoop.util.RunJar.run(RunJar.java:221) at org.apache.hadoop.util.RunJar.main(RunJar.java:136) 2017-11-10 14:52:06,915 ERROR [main]: status.SparkJobMonitor (RemoteSparkJobMonitor.java:startMonitor(132)) - Failed to monitor Job[ 2] with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(java.util.concurrent.TimeoutException)' org.apache.hadoop.hive.ql.metadata.HiveException: java.util.concurrent.TimeoutException at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobStatus.getSparkJobInfo(RemoteSparkJobStatus.java:153) at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobStatus.getState(RemoteSparkJobStatus.java:82) at org.apache.hadoop.hive.ql.exec.spark.status.RemoteSparkJobMonitor.startMonitor(RemoteSparkJobMonitor.java:80) at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobRef.monitorJob(RemoteSparkJobRef.java:60) at org.apache.hadoop.hive.ql.exec.spark.SparkTask.execute(SparkTask.java:109) at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:214) at org.apache.hadoop.hive.ql.exec.TaskRunner.runSequential(TaskRunner.java:100) at org.apache.hadoop.hive.ql.Driver.launchTask(Driver.java:1979) at org.apache.hadoop.hive.ql.Driver.execute(Driver.java:1692) at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1424) at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1208) at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1198) at org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:220) at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:172) at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:383) at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:318) at org.apache.hadoop.hive.cli.CliDriver.executeDriver(CliDriver.java:720) at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:693) at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:628) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at org.apache.hadoop.util.RunJar.run(RunJar.java:221) at org.apache.hadoop.util.RunJar.main(RunJar.java:136) Caused by: java.util.concurrent.TimeoutException at io.netty.util.concurrent.AbstractFuture.get(AbstractFuture.java:49) at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobStatus.getSparkJobInfo(RemoteSparkJobStatus.java:150) ... 24 more ```2017-11-10 14:52:06,915 ERROR [main]: status.SparkJobMonitor (SessionState.java:printError(995)) - Failed to monitor Job[ 2] with exception 'org.apache.hadoop.hive.ql.metadata.HiveException(java.util.concurrent.TimeoutException)' org.apache.hadoop.hive.ql.metadata.HiveException: java.util.concurrent.TimeoutException``` at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobStatus.getSparkJobInfo(RemoteSparkJobStatus.java:153)``` at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobStatus.getState(RemoteSparkJobStatus.java:82) at org.apache.hadoop.hive.ql.exec.spark.status.RemoteSparkJobMonitor.startMonitor(RemoteSparkJobMonitor.java:80) at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobRef.monitorJob(RemoteSparkJobRef.java:60) at org.apache.hadoop.hive.ql.exec.spark.SparkTask.execute(SparkTask.java:109) at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:214) at org.apache.hadoop.hive.ql.exec.TaskRunner.runSequential(TaskRunner.java:100) at org.apache.hadoop.hive.ql.Driver.launchTask(Driver.java:1979) at org.apache.hadoop.hive.ql.Driver.execute(Driver.java:1692) at org.apache.hadoop.hive.ql.Driver.runInternal(Driver.java:1424) at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1208) at org.apache.hadoop.hive.ql.Driver.run(Driver.java:1198) at org.apache.hadoop.hive.cli.CliDriver.processLocalCmd(CliDriver.java:220) at org.apache.hadoop.hive.cli.CliDriver.processCmd(CliDriver.java:172) at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:383) at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:318) at org.apache.hadoop.hive.cli.CliDriver.executeDriver(CliDriver.java:720) at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:693) at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:628) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at org.apache.hadoop.util.RunJar.run(RunJar.java:221) at org.apache.hadoop.util.RunJar.main(RunJar.java:136) Caused by: java.util.concurrent.TimeoutException at io.netty.util.concurrent.AbstractFuture.get(AbstractFuture.java:49) at org.apache.hadoop.hive.ql.exec.spark.status.impl.RemoteSparkJobStatus.getSparkJobInfo(RemoteSparkJobStatus.java:150) ... 24 more ``` 2017-11-10 14:52:06,931 ERROR [main]: ql.Driver (SessionState.java:printError(995)) - FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.spark.SparkTask```

当jar在hdfs的时候提交spark job报错

(一)jar不在hdfs上的时候提交spark任务成功,使用的命令: spark-submit --master spark://192.168.244.130:7077 --class cn.com.cnpc.klmy.common.WordCount2 --executor-memory 1G --total-executor-cores 2 /root/modelcall-2.0.jar (二)而当jar在hdfs上的时候提交spark任务报错:classNotFoundException呢?,命令如下: spark-submit --master spark://192.168.244.130:7077 --class cn.com.cnpc.klmy.common.WordCount2 --executor-memory 1G --total-executor-cores 2 hdfs://192.168.244.130:9000/mdjar/modelcall-2.0.jar 请教各位大咖这到底是什么原因造成的?望各位大咖不吝赐教!跪谢!!! 注:hdfs能够正常访问,代码里面产生的结果存在hdfs上(第一情况正常运行,在hdfs上能够查看到结果)

Spark没报错,但是停在某一个地方不动了

在一个foreach函数中调用一个把数据写进hbase的函数(函数也是通过spark实现的),每次程序运行到这里,都停在这里不动了,并且这时在监控界面上除了之前运行的作业,还出现了一个新的作业,这个新作业处于waiting状态。问问各位大神,这是什么原因?

spark-shell --master spark://ip:7337 的方式运行 报错

spark-shell --master spark://ip:7337 的方式运行 报错 readerIndex(5) + length(799024) exceeds writerIndex(176) : UNpooledUnsafeDir![图片说明](https://img-ask.csdn.net/upload/201902/20/1550655590_823550.png) (cdh集群的端口是7337没毛病,经常用的7077报错拒绝连接,可以排除端口问题) 现在提交spark-submit脚本运行standalone模式也是报同样的错,yarn模式没问题,百度谷歌无果,望大神们帮忙解决下!

spark通过jdbc读取hive的表报错,我是在zeppelin里运行的

## 代码: import org.apache.spark.sql.hive.HiveContext val pro = new java.util.Properties() pro.setProperty("user", "****") pro.setProperty("password", "*****") val driverName = "org.apache.hadoop.hive.jdbc.HiveDriver"; Class.forName(driverName); val hiveContext = new HiveContext(sc) val hivetable = hiveContext.read.jdbc("jdbc:hive://*****/default", "*****", pro); ## 错误: import org.apache.spark.sql.hive.HiveContext pro: java.util.Properties = {} res15: Object = null res16: Object = null driverName: String = org.apache.hadoop.hive.jdbc.HiveDriver res17: Class[_] = class org.apache.hadoop.hive.jdbc.HiveDriver warning: there was one deprecation warning; re-run with -deprecation for details hiveContext: org.apache.spark.sql.hive.HiveContext = org.apache.spark.sql.hive.HiveContext@14f9cc13 java.sql.SQLException: Method not supported at org.apache.hadoop.hive.jdbc.HiveResultSetMetaData.isSigned(Unknown Source) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.getSchema(JdbcUtils.scala:232) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:64) at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation.<init>(JDBCRelation.scala:113) at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:45) at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:330) at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152) at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125) at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:166) ... 46 elided

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