Hive on Spark预测性执行BUG一枚

栏目: 服务器 · 发布时间: 6年前

内容简介:Hive on Spark预测性执行BUG一枚

为了平复难以平复的痛苦,难以掩饰的激动,把这次遇到并解决的记录下。尽管最终解决的patch是官网的: Hive on Spark gives incorrect results when speculation is on

版本说明下: * hive-1.2.1 * spark-1.3.1

在没有启动spark.speculation前,有个别任务执行非常慢,非常之讨厌。而启用预测性执行后,时不时任务会有些会失败,让人很烦躁。但是吧,也不算故障,说来也奇怪,重启下后再次查询问题就不出现了,也就没太在意。

今天数据量比较大,并且是上头检查。妈蛋,搞成了故障,没得办法,必须把原因找出来了。下来就帖日志了:

应用 SQL 查询报错日志:啥也看不到,就知道Hive查询报错,只能拿着时间去查Hive日志

[ERROR] 14:19:56.685 [RMI TCP Connection(7)-192.168.31.11] c.e.z.h.s.BaseHiveQueryService | Error while processing statement: FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask
java.sql.SQLException: Error while processing statement: FAILED: Execution Error, return code 3 from org.apache.hadoop.hive.ql.exec.spark.SparkTask
        at org.apache.hive.jdbc.HiveStatement.execute(HiveStatement.java:296)
        at org.apache.hive.jdbc.HiveStatement.executeQuery(HiveStatement.java:392)
        at org.apache.hive.jdbc.HivePreparedStatement.executeQuery(HivePreparedStatement.java:109)
        at org.apache.commons.dbcp.DelegatingPreparedStatement.executeQuery(DelegatingPreparedStatement.java:96)
        at org.apache.commons.dbcp.DelegatingPreparedStatement.executeQuery(DelegatingPreparedStatement.java:96)
        at com.eshore.zhfx.hbase.service.BaseHiveQueryService.listIteratorInternal(BaseHiveQueryService.java:101)
        at com.eshore.zhfx.hbase.service.BaseHiveQueryService.listIterator(BaseHiveQueryService.java:80)
        at com.eshore.zhfx.hbase.QueryService.getAccessLogIterator(QueryService.java:140)
        at com.eshore.zhfx.hbase.QueryService$$FastClassByCGLIB$$a60bf6f7.invoke(<generated>)
        at net.sf.cglib.proxy.MethodProxy.invoke(MethodProxy.java:191)
        at org.springframework.aop.framework.Cglib2AopProxy$CglibMethodInvocation.invokeJoinpoint(Cglib2AopProxy.java:688)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:150)
        at org.springframework.aop.framework.adapter.AfterReturningAdviceInterceptor.invoke(AfterReturningAdviceInterceptor.java:50)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:172)
        at org.springframework.aop.framework.adapter.MethodBeforeAdviceInterceptor.invoke(MethodBeforeAdviceInterceptor.java:50)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:172)
        at org.springframework.aop.interceptor.ExposeInvocationInterceptor.invoke(ExposeInvocationInterceptor.java:89)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:172)
        at org.springframework.aop.framework.Cglib2AopProxy$DynamicAdvisedInterceptor.intercept(Cglib2AopProxy.java:621)
        at com.eshore.zhfx.hbase.QueryService$$EnhancerByCGLIB$$9a4ab584.getAccessLogIterator(<generated>)
        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:601)
        at org.springframework.aop.support.AopUtils.invokeJoinpointUsingReflection(AopUtils.java:309)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.invokeJoinpoint(ReflectiveMethodInvocation.java:183)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:150)
        at org.springframework.remoting.support.RemoteInvocationTraceInterceptor.invoke(RemoteInvocationTraceInterceptor.java:77)
        at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:172)
        at org.springframework.aop.framework.JdkDynamicAopProxy.invoke(JdkDynamicAopProxy.java:202)
        at com.sun.proxy.$Proxy22.getAccessLogIterator(Unknown Source)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)

HIVE服务日志:rename错了,但是也好像看不到啥。知道那个节点有问题了,去查节点日志

2017-05-23 14:19:20,509 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) - 2017-05-23 14:19:20,508 WARN  [task-result-getter-1] scheduler.TaskSetManager: Lost task 2199.1 in stage 2.0 (TID 4517, hadoop-slaver41): java.lang.IllegalStateException: Hit error while closing operators - failing tree: org.apache.hadoop.hive.ql.metadata.HiveException: Unable to rename output from: hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0 to: hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_tmp.-ext-10001/002199_0.snappy
2017-05-23 14:19:20,509 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.close(SparkMapRecordHandler.java:195)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.closeRecordProcessor(HiveMapFunctionResultList.java:58)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList$ResultIterator.hasNext(HiveBaseFunctionResultList.java:106)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:41)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at scala.collection.Iterator$class.foreach(Iterator.scala:727)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$2.apply(AsyncRDDActions.scala:114)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$2.apply(AsyncRDDActions.scala:114)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1576)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1576)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.spark.scheduler.Task.run(Task.scala:64)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at java.lang.Thread.run(Thread.java:722)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) - Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Unable to rename output from: hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0 to: hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_tmp.-ext-10001/002199_0.snappy
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.FileSinkOperator$FSPaths.commit(FileSinkOperator.java:237)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.FileSinkOperator$FSPaths.access$200(FileSinkOperator.java:143)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.FileSinkOperator.closeOp(FileSinkOperator.java:1051)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:616)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:630)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:630)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:630)
2017-05-23 14:19:20,510 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:630)
2017-05-23 14:19:20,511 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  at org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.close(SparkMapRecordHandler.java:172)
2017-05-23 14:19:20,511 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) -  ... 15 more
2017-05-23 14:19:20,511 INFO  client.SparkClientImpl (SparkClientImpl.java:run(569)) - 

Task错误节点错误日志:这日志没查。重名,那名称去namenode的日志是啥子呢?

17/05/23 14:19:18 INFO exec.FileSinkOperator: FS[24]: records written - 0
17/05/23 14:19:18 INFO exec.FileSinkOperator: Final Path: FS hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_tmp.-ext-10001/002199_0
17/05/23 14:19:18 INFO exec.FileSinkOperator: Writing to temp file: FS hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0
17/05/23 14:19:18 INFO exec.FileSinkOperator: New Final Path: FS hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_tmp.-ext-10001/002199_0.snappy
17/05/23 14:19:19 INFO compress.CodecPool: Got brand-new compressor [.snappy]
org.apache.hadoop.hive.ql.metadata.HiveException: Unable to rename output from: hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0 to: hdfs://zfcluster/hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_tmp.-ext-10001/002199_0.snappy
        at org.apache.hadoop.hive.ql.exec.FileSinkOperator$FSPaths.commit(FileSinkOperator.java:237)
        at org.apache.hadoop.hive.ql.exec.FileSinkOperator$FSPaths.access$200(FileSinkOperator.java:143)
        at org.apache.hadoop.hive.ql.exec.FileSinkOperator.closeOp(FileSinkOperator.java:1051)
        at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:616)
        at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:630)
        at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:630)
        at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:630)
        at org.apache.hadoop.hive.ql.exec.Operator.close(Operator.java:630)
        at org.apache.hadoop.hive.ql.exec.spark.SparkMapRecordHandler.close(SparkMapRecordHandler.java:172)
        at org.apache.hadoop.hive.ql.exec.spark.HiveMapFunctionResultList.closeRecordProcessor(HiveMapFunctionResultList.java:58)
        at org.apache.hadoop.hive.ql.exec.spark.HiveBaseFunctionResultList$ResultIterator.hasNext(HiveBaseFunctionResultList.java:106)
        at scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:41)
        at scala.collection.Iterator$class.foreach(Iterator.scala:727)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
        at org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$2.apply(AsyncRDDActions.scala:114)
        at org.apache.spark.rdd.AsyncRDDActions$$anonfun$foreachAsync$2.apply(AsyncRDDActions.scala:114)
        at org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1576)
        at org.apache.spark.SparkContext$$anonfun$33.apply(SparkContext.scala:1576)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
        at org.apache.spark.scheduler.Task.run(Task.scala:64)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
        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:722)

Namenode日志:有点点线索了,分配了两次,导致了第二个任务写入的时刻报错!

[hadoop@hadoop-master2 ~]$ grep '_tmp.002199' hadoop/logs/hadoop-hadoop-namenode-hadoop-master2.log.1
2017-05-23 14:19:01,591 INFO org.apache.hadoop.hdfs.StateChange: BLOCK* allocateBlock: /hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0. BP-1414312971-192.168.32.11-1392479369615 blk_1219124858_145508182{blockUCState=UNDER_CONSTRUCTION, primaryNodeIndex=-1, replicas=[ReplicaUnderConstruction[[DISK]DS-ad2eac59-1e38-4019-a5ac-64c465366186:NORMAL:192.168.32.93:50010|RBW], ReplicaUnderConstruction[[DISK]DS-90c8cbe3-fd70-4ad7-938a-4248b4435df7:NORMAL:192.168.32.136:50010|RBW], ReplicaUnderConstruction[[DISK]DS-9da76df9-47f0-4e25-b375-e1bf32f4cf52:NORMAL:192.168.36.58:50010|RBW]]}
2017-05-23 14:19:14,939 INFO org.apache.hadoop.hdfs.StateChange: DIR* completeFile: /hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0 is closed by DFSClient_attempt_201705231411_0000_m_001585_0_1316598676_51
2017-05-23 14:19:20,368 INFO org.apache.hadoop.hdfs.StateChange: BLOCK* allocateBlock: /hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0. BP-1414312971-192.168.32.11-1392479369615 blk_1219125517_145508841{blockUCState=UNDER_CONSTRUCTION, primaryNodeIndex=-1, replicas=[ReplicaUnderConstruction[[DISK]DS-4d4c90f0-1ddf-4800-b33a-e776e58dc744:NORMAL:192.168.32.61:50010|RBW], ReplicaUnderConstruction[[DISK]DS-948cd823-5a4c-4673-8ace-99f02a26522b:NORMAL:192.168.32.52:50010|RBW], ReplicaUnderConstruction[[DISK]DS-7818addb-3881-446e-abb3-2c178be6bb63:NORMAL:192.168.32.176:50010|RBW]]}
2017-05-23 14:19:20,478 INFO org.apache.hadoop.hdfs.StateChange: DIR* completeFile: /hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0 is closed by DFSClient_attempt_201705231411_0000_m_001345_1_1292482540_51
2017-05-23 14:19:20,480 WARN org.apache.hadoop.hdfs.StateChange: DIR* FSDirectory.unprotectedRenameTo: failed to rename /hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_task_tmp.-ext-10001/_tmp.002199_0 to /hive/scratchdir/hadoop/64801461-94aa-4e17-afee-494e77b49998/hive_2017-05-23_14-18-38_278_4858034238266422677-2/-mr-10000/.hive-staging_hive_2017-05-23_14-18-38_278_4858034238266422677-2/_tmp.-ext-10001/002199_0.snappy because destination exists

好了,看到这里,驴脑袋还没怀疑到是预测性执行导致的问题。当时想为啥会出现同一个文件名呢:

MAP太多了000000又循环了一轮?看了执行的map数也就2600啊,不应该啊。

哪这个文件名是哪里产生的呢?然后就搞了下远程调试:没啥用,错误是在task上发生了,调试hive-driver没啥用,但是有意外收获

[hadoop@hadoop-master2 hive]$ DEBUG=true bin/hive
Listening for transport dt_socket at address: 8000

Logging initialized using configuration in file:/home/hadoop/apache-hive-1.2.1-bin/conf/hive-log4j.properties
hive> set hive.execution.engine=spark; '查询之前需要设置下引擎,故障得先处理。搞成默认的mr跑是成功的
hive> SQLSQLSQL...执行刚报错的SQL
Query ID = hadoop_20170523173748_7660d9fb-9683-4792-8315-a51f6dcc270b
Total jobs = 1
Launching Job 1 out of 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Starting Spark Job = 48a8668b-1c59-4cbf-b1e2-e19612ee77d0

Query Hive on Spark job[0] stages:
0

Status: Running (Hive on Spark job[0])
Job Progress Format
CurrentTime StageId_StageAttemptId: SucceededTasksCount(+RunningTasksCount-FailedTasksCount)/TotalTasksCount [StageCost]
2017-05-23 17:38:15,730 Stage-0_0: 0/2609
2017-05-23 17:38:16,739 Stage-0_0: 0(+159)/2609
...
2017-05-23 17:39:23,182 Stage-0_0: 2162(+447)/2609
2017-05-23 17:39:24,188 Stage-0_0: 2167(+608)/2609
2017-05-23 17:39:25,195 Stage-0_0: 2201(+836,-1)/2609
2017-05-23 17:39:26,201 Stage-0_0: 2215(+832,-2)/2609
2017-05-23 17:39:27,207 Stage-0_0: 2227(+820,-2)/2609
2017-05-23 17:39:28,213 Stage-0_0: 2250(+797,-2)/2609
2017-05-23 17:39:29,219 Stage-0_0: 2280(+767,-2)/2609
2017-05-23 17:39:30,224 Stage-0_0: 2338(+709,-2)/2609
2017-05-23 17:39:31,230 Stage-0_0: 2350(+696,-3)/2609
2017-05-23 17:39:32,236 Stage-0_0: 2359(+684,-6)/2609
2017-05-23 17:39:33,243 Stage-0_0: 2363(+676,-10)/2609
2017-05-23 17:39:34,249 Stage-0_0: 2365(+673,-12)/2609
...

有报错了,赶紧去web页面看了下结果,好家伙,全部是Speculation的报错:

Hive on Spark预测性执行BUG一枚

在结合前面的namenode的日志,基本就走到正道上面。然后 hive spark speculation 一股沟,没错第一条就是hive官网的bug啊。

然后就是打patch修改HivePairFlatMapFunction,验证是OK的。至少原来出错的语句完美跑完。

总结下

就是前段集成攻城狮把网络回环的问题处理了,导致网络状态好的不要不要的啊!把那些有备用10M网卡全部停了,集群的机器的网络好了N倍。第二个就是数据量实在大,其实speculation有启动,但是最先完成的还是先启动的,又没有把预测执行kill掉并且还运行完了最终还保存到同名文件。最后让我又一次体验了一把找开源软件BUG激情四射的半天。

记录聊以慰藉!!

–END


以上所述就是小编给大家介绍的《Hive on Spark预测性执行BUG一枚》,希望对大家有所帮助,如果大家有任何疑问请给我留言,小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持!

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