• yarn 集群部署,遇到的问题小结


    版本号信息: hadoop 2.3.0  hive 0.11.0

    1. Application Master 无法訪问

        点击application mater 链接,出现 http 500 错误,java.lang.Connect.exception:
        问题是因为设定web ui时,50030 port相应的ip地址为0.0.0.0,导致application master 链接无法定位。

    解决的方法:
         yarn-site.xml 文件
        <property>
            <description>The address of the RM web application.</description>
            <name>yarn.resourcemanager.webapp.address</name>
            <value>xxxxxxxxxx:50030</value>
        </property>
        这是2.3.0 的里面的一个bug 1811 ,2.4.0已经修复

    2. History UI 无法訪问 和 container 打不开
         点击 Tracking URL:History无法訪问
           问题是 history service 没有启动
          
      解决的方法:
         配置:选择(xxxxxxxxxx: 作为history sever
       
        <property>
            <name>yarn.log-aggregation-enable</name>
            <value>true</value>
        </property>
       <property>
            <name>mapreduce.jobhistory.address</name>
            <value>xxxxxxxxxx::10020</value>
        </property>

        <property>
        <name>mapreduce.jobhistory.webapp.address</name>
            <value>xxxxxxxxxx:19888</value>
        </property>

      sbin/mr-jobhistory-daemon.sh   
    start historyserver

    3 yarn 平台的优化
     
    设置 虚拟cpu的个数
        <property>
            <name>yarn.nodemanager.resource.cpu-vcores</name>
            <value>23</value> 
        </property>
        设置使用的内存
        <property>
            <name>yarn.nodemanager.resource.memory-mb</name>
            <value>61440</value>
            <description>the amount of memory on the NodeManager in GB</description>
        </property>
    设置每一个任务最大使用的内存
        <property>
            <name>yarn.scheduler.maximum-allocation-mb</name>
            <value>49152</value>
            <source>yarn-default.xml</source>
        </property>

    4 执行任务 提示: Found interface org.apache.hadoop.mapreduce.Counter, but class was expected
    改动pom,又一次install
        <dependency>
               <groupId>org.apache.hadoop</groupId>
               <artifactId>hadoop-common</artifactId>
               <version>2.3.0</version>
       </dependency>    
     <dependency>
             <groupId>org.apache.hadoop</groupId>
             <artifactId>hadoop-mapreduce-client-core</artifactId>
             <version>2.3.0</version>
       </dependency>
       <dependency>
                    <groupId>org.apache.mrunit</groupId>
                    <artifactId>mrunit</artifactId>
                    <version>1.0.0</version>
                    <classifier>hadoop2</classifier>
                    <scope>test</scope>
                </dependency>
    jdk 换成1.7



    5 执行任务提示shuffle内存溢出Java heap space
    2014-05-14 16:44:22,010 FATAL [IPC Server handler 4 on 44508] org.apache.hadoop.mapred.TaskAttemptListenerImpl: Task: attempt_1400048775904_0006_r_000004_0 - exited : org.apache.hadoop.mapreduce.task.reduce.Shuffle$ShuffleError: error in shuffle in fetcher#3
        at org.apache.hadoop.mapreduce.task.reduce.Shuffle.run(Shuffle.java:134)
        at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:376)
        at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:168)
        at java.security.AccessController.doPrivileged(Native Method)
        at javax.security.auth.Subject.doAs(Subject.java:415)
        at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1548)
        at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:163)
    Caused by: java.lang.OutOfMemoryError: Java heap space
        at org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:56)
        at org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:46)
        at org.apache.hadoop.mapreduce.task.reduce.InMemoryMapOutput.<init>(InMemoryMapOutput.java:63)
        at org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl.unconditionalReserve(MergeManagerImpl.java:297)
        at org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl.reserve(MergeManagerImpl.java:287)
        at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyMapOutput(Fetcher.java:411)
        at org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:341)
        at org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:165)

    来源: <http:/xxxxxxxxxx:19888/jobhistory/logs/ST-L09-05-back-tj-yarn15:8034/container_1400048775904_0006_01_000001/job_1400048775904_0006/hadoop/syslog/?start=0>
     

    解决方法:
    调低mapreduce.reduce.shuffle.memory.limit.percent的值 默觉得0.25 如今调成0.10 


    參考:
    http://www.sqlparty.com/yarn%E5%9C%A8shuffle%E9%98%B6%E6%AE%B5%E5%86%85%E5%AD%98%E4%B8%8D%E8%B6%B3%E9%97%AE%E9%A2%98error-in-shuffle-in-fetcher/

    6 reduce 任务的log 中间发现:

    2014-05-14 17:51:21,835 WARN [Readahead Thread #2] org.apache.hadoop.io.ReadaheadPool: Failed readahead on ifile
    EINVAL: Invalid argument
        at org.apache.hadoop.io.nativeio.NativeIO$POSIX.posix_fadvise(Native Method)
        at org.apache.hadoop.io.nativeio.NativeIO$POSIX.posixFadviseIfPossible(NativeIO.java:263)
        at org.apache.hadoop.io.nativeio.NativeIO$POSIX$CacheManipulator.posixFadviseIfPossible(NativeIO.java:142)
        at org.apache.hadoop.io.ReadaheadPool$ReadaheadRequestImpl.run(ReadaheadPool.java:206)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)

    来源: <http://xxxxxxxxxx:8042/node/containerlogs/container_1400060792764_0001_01_000726/hadoop/syslog/?start=-4096>
     
    ps: 错误没有再现,暂无解决方法


    7 hive 任务

    java.lang.InstantiationException: org.antlr.runtime.CommonToken
    Continuing ...
    java.lang.RuntimeException: failed to evaluate: <unbound>=Class.new();
    參考:https://issues.apache.org/jira/browse/HIVE-4222s

    8 hive 任务自己主动把join装换mapjoin时内存溢出,解决方法:关闭自己主动装换,11前的版本号默认值为false,后面的为true;
    在任务脚本里面加上:set hive.auto.convert.join=false;
    或者在hive-site.xml 配上为false;
    出错日志:
    SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
    2014-05-15 02:40:58     Starting to launch local task to process map join;      maximum memory = 1011351552
    2014-05-15 02:41:00     Processing rows:        200000  Hashtable size: 199999  Memory usage:   110092544       rate:   0.109
    2014-05-15 02:41:01     Processing rows:        300000  Hashtable size: 299999  Memory usage:   229345424       rate:   0.227
    2014-05-15 02:41:01     Processing rows:        400000  Hashtable size: 399999  Memory usage:   170296368       rate:   0.168
    2014-05-15 02:41:01     Processing rows:        500000  Hashtable size: 499999  Memory usage:   285961568       rate:   0.283
    2014-05-15 02:41:02     Processing rows:        600000  Hashtable size: 599999  Memory usage:   408727616       rate:   0.404
    2014-05-15 02:41:02     Processing rows:        700000  Hashtable size: 699999  Memory usage:   333867920       rate:   0.33
    2014-05-15 02:41:02     Processing rows:        800000  Hashtable size: 799999  Memory usage:   459541208       rate:   0.454
    2014-05-15 02:41:03     Processing rows:        900000  Hashtable size: 899999  Memory usage:   391524456       rate:   0.387
    2014-05-15 02:41:03     Processing rows:        1000000 Hashtable size: 999999  Memory usage:   514140152       rate:   0.508
    2014-05-15 02:41:03     Processing rows:        1029052 Hashtable size: 1029052 Memory usage:   546126888       rate:   0.54
    2014-05-15 02:41:03     Dump the hashtable into file: file:/tmp/hadoop/hive_2014-05-15_14-40-53_413_3806680380261480764/-local-10002/HashTable-Stage-4/MapJoin-mapfile01--.hashtable
    2014-05-15 02:41:06     Upload 1 File to: file:/tmp/hadoop/hive_2014-05-15_14-40-53_413_3806680380261480764/-local-10002/HashTable-Stage-4/MapJoin-mapfile01--.hashtable File size: 68300588
    2014-05-15 02:41:06     End of local task; Time Taken: 8.301 sec.
    Execution completed successfully
    Mapred Local Task Succeeded . Convert the Join into MapJoin
    Mapred Local Task Succeeded . Convert the Join into MapJoin
    Launching Job 2 out of 2

    log出错日志:
    2014-05-15 13:52:54,007 FATAL [main] org.apache.hadoop.mapred.YarnChild: Error running child : java.lang.OutOfMemoryError: Java heap space
        at java.io.ObjectInputStream$HandleTable.grow(ObjectInputStream.java:3465)
        at java.io.ObjectInputStream$HandleTable.assign(ObjectInputStream.java:3271)
        at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1789)
        at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
        at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
        at java.util.HashMap.readObject(HashMap.java:1183)
        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 java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)
        at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893)
        at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
        at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
        at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
        at org.apache.hadoop.hive.ql.exec.persistence.HashMapWrapper.initilizePersistentHash(HashMapWrapper.java:128)
        at org.apache.hadoop.hive.ql.exec.MapJoinOperator.loadHashTable(MapJoinOperator.java:194)
        at org.apache.hadoop.hive.ql.exec.MapJoinOperator.cleanUpInputFileChangedOp(MapJoinOperator.java:212)
        at org.apache.hadoop.hive.ql.exec.Operator.cleanUpInputFileChanged(Operator.java:1377)
        at org.apache.hadoop.hive.ql.exec.Operator.cleanUpInputFileChanged(Operator.java:1381)

    来源: <http://xxxxxxxxxx:19888/jobhistory/logs/ST-L09-10-back-tj-yarn21:8034/container_1400064445468_0013_01_000002/attempt_1400064445468_0013_m_000000_0/hadoop/syslog/?start=0>
     



    9 hive执行时 提示: failed to evaluate: <unbound>=Class.new(); ,升级到0.13.0
    SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]OKTime taken: 2.28 secondsjava.lang.InstantiationException: org.antlr.runtime.CommonTokenContinuing ...java.lang.RuntimeException: failed to evaluate: <unbound>=Class.new();Continuing ...java.lang.InstantiationException: org.antlr.runtime.CommonTokenContinuing ...java.lang.RuntimeException: failed to evaluate: <unbound>=Class.new();Continuing ...java.lang.InstantiationException: org.antlr.runtime.CommonTokenContinuing ...java.lang.RuntimeException: failed to evaluate: <unbound>=Class.new();Continuing ...java.lang.InstantiationException: org.antlr.runtime.CommonTokenContinuing ...java.lang.RuntimeException: failed to evaluate: <unbound>=Class.new();Continuing ...java.lang.InstantiationException: org.antlr.runtime.CommonTokenContinuing ...

    这个应该升级后能解决,只是不知道为什么我升级12.0 和13.0 ,一执行就报错fileNotfundHIVE_PLANxxxxxxxxx 。ps (參考11)应该是我配置有问题,暂无解决方法。



    10 hive 创建表或者数据库的时候 Couldnt obtain a new sequence (unique id) : You have an error in your SQL syntax
    解决方法:这个是由于hive元数据库的名字是yarn-hive, sql中中划线是关键词,所以sql错误。把数据库名去掉中划线,问题解决。
    错误日志:
    FAILED: Error in metadata: MetaException(message:javax.jdo.JDOException: Couldnt obtain a new sequence (unique id) : You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near '-hive.`SEQUENCE_TABLE` WHERE `SEQUENCE_NAME`='org.apache.hadoop.hive.metastore.m' at line 1
            at org.datanucleus.api.jdo.NucleusJDOHelper.getJDOExceptionForNucleusException(NucleusJDOHelper.java:596)
            at org.datanucleus.api.jdo.JDOPersistenceManager.jdoMakePersistent(JDOPersistenceManager.java:732)
            at org.datanucleus.api.jdo.JDOPersistenceManager.makePersistent(JDOPersistenceManager.java:752)
            at org.apache.hadoop.hive.metastore.ObjectStore.createTable(ObjectStore.java:643)
            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.hive.metastore.RetryingRawStore.invoke(RetryingRawStore.java:111)
            at com.sun.proxy.$Proxy14.createTable(Unknown Source)
            at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.create_table_core(HiveMetaStore.java:1070)
            at org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.create_table_with_environment_context(HiveMetaStore.java:1103)
            at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
            at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
            at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
            at java.lang.reflect.Method.invoke(Method.java:606)
            at org.apache.hadoop.hive.metastore.RetryingHMSHandler.invoke(RetryingHMSHandler.java:103)
            at com.sun.proxy.$Proxy15.create_table_with_environment_context(Unknown Source)
            at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.createTable(HiveMetaStoreClient.java:466)
            at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.createTable(HiveMetaStoreClient.java:455)
            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.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:74)
            at com.sun.proxy.$Proxy16.createTable(Unknown Source)
            at org.apache.hadoop.hive.ql.metadata.Hive.createTable(Hive.java:597)
            at org.apache.hadoop.hive.ql.exec.DDLTask.createTable(DDLTask.java:3777)
            at org.apache.hadoop.hive.ql.exec.DDLTask.execute(DDLTask.java:256)
            at org.apache.hadoop.hive.ql.exec.Task.executeTask(Task.java:144)
            at org.apache.hadoop.hive.ql.exec.TaskRunner.runSequential(TaskRunner.java:57)
            at org.apache.hadoop.hive.ql.Driver.launchTask(Driver.java:1362)
            at org.apache.hadoop.hive.ql.Driver.execute(Driver.java:1146)
            at org.apache.hadoop.hive.ql.Driver.run(Driver.java:952)
            at shark.SharkCliDriver.processCmd(SharkCliDriver.scala:338)
            at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:413)
            at shark.SharkCliDriver$.main(SharkCliDriver.scala:235)
            at shark.SharkCliDriver.main(SharkCliDriver.scala)
    NestedThrowablesStackTrace:
    com.mysql.jdbc.exceptions.jdbc4.MySQLSyntaxErrorException: You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near '-hive.`SEQUENCE_TABLE` WHERE `SEQUENCE_NAME`='org.apache.hadoop.hive.metastore.m' at line 1
            at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
            at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
            at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
            at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
            at com.mysql.jdbc.Util.handleNewInstance(Util.java:406)
            at com.mysql.jdbc.Util.getInstance(Util.java:381)
            at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:1030)
            at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:956)
            at com.mysql.jdbc.MysqlIO.checkErrorPacket(MysqlIO.java:3558)
            at com.mysql.jdbc.MysqlIO.checkErrorPacket(MysqlIO.java:3490)
            at com.mysql.jdbc.MysqlIO.sendCommand(MysqlIO.java:1959)
            at com.mysql.jdbc.MysqlIO.sqlQueryDirect(MysqlIO.java:2109)
            at com.mysql.jdbc.ConnectionImpl.execSQL(ConnectionImpl.java:2648)
            at com.mysql.jdbc.PreparedStatement.executeInternal(PreparedStatement.java:2077)
            at com.mysql.jdbc.PreparedStatement.executeQuery(PreparedStatement.java:2228)
            at org.apache.commons.dbcp.DelegatingPreparedStatement.executeQuery(DelegatingPreparedStatement.java:96)
            at org.apache.commons.dbcp.DelegatingPreparedStatement.executeQuery(DelegatingPreparedStatement.java:96)
            at org.datanucleus.store.rdbms.ParamLoggingPreparedStatement.executeQuery(ParamLoggingPreparedStatement.java:381)
            at org.datanucleus.store.rdbms.SQLController.executeStatementQuery(SQLController.java:504)
            at org.datanucleus.store.rdbms.valuegenerator.SequenceTable.getNextVal(SequenceTable.java:197)
            at org.datanucleus.store.rdbms.valuegenerator.TableGenerator.reserveBlock(TableGenerator.java:190)
            at org.datanucleus.store.valuegenerator.AbstractGenerator.reserveBlock(AbstractGenerator.java:305)
            at org.datanucleus.store.rdbms.valuegenerator.AbstractRDBMSGenerator.obtainGenerationBlock(AbstractRDBMSGenerator.java:170)
            at org.datanucleus.store.valuegenerator.AbstractGenerator.obtainGenerationBlock(AbstractGenerator.java:197)
            at org.datanucleus.store.valuegenerator.AbstractGenerator.next(AbstractGenerator.java:105)
            at org.datanucleus.store.rdbms.RDBMSStoreManager.getStrategyValueForGenerator(RDBMSStoreManager.java:2019)
            at org.datanucleus.store.AbstractStoreManager.getStrategyValue(AbstractStoreManager.java:1385)
            at org.datanucleus.ExecutionContextImpl.newObjectId(ExecutionContextImpl.java:3727)
            at org.datanucleus.state.JDOStateManager.setIdentity(JDOStateManager.java:2574)
            at org.datanucleus.state.JDOStateManager.initialiseForPersistentNew(JDOStateManager.java:526)
            at org.datanucleus.state.ObjectProviderFactoryImpl.newForPersistentNew(ObjectProviderFactoryImpl.java:202)
            at org.datanucleus.ExecutionContextImpl.newObjectProviderForPersistentNew(ExecutionContextImpl.java:1326)
            at org.datanucleus.ExecutionContextImpl.persistObjectInternal(ExecutionContextImpl.java:2123)
            at org.datanucleus.ExecutionContextImpl.persistObjectWork(ExecutionContextImpl.java:1972)
            at org.datanucleus.ExecutionContextImpl.persistObject(ExecutionContextImpl.java:1820)
            at org.datanucleus.ExecutionContextThreadedImpl.persistObject(ExecutionContextThreadedImpl.java:217)
            at org.datanucleus.api.jdo.JDOPersistenceManager.jdoMakePersistent(JDOPersistenceManager.java:727)
            at org.datanucleus.api.jdo.JDOPersistenceManager.makePersistent(JDOPersistenceManager.java:752)
            at org.apache.hadoop.hive.metastore.ObjectStore.createTable(ObjectStore.java:643)


    11 安装hive 12 和13 后,执行任务报错提示:FileNotFoundException: HIVE_PLAN
    解决方法:可能是hive一个bug,也可能那里配置错了 ,待解决

    错误日志

    2014-05-16 10:27:07,896 INFO [main] org.apache.hadoop.mapred.MapTask: Processing split: Paths:/user/hive/warehouse/game_predata.db/game_login_log/dt=0000-00-00/000000_0:201326592+60792998,/user/hive/warehouse/game_predata.db/game_login_log/dt=0000-00-00/000001_0_copy_1:201326592+58503492,/user/hive/warehouse/game_predata.db/game_login_log/dt=0000-00-00/000001_0_copy_2:67108864+67108864,/user/hive/warehouse/game_predata.db/game_login_log/dt=0000-00-00/000001_0_copy_2:134217728+67108864,/user/hive/warehouse/game_predata.db/game_login_log/dt=0000-00-00/000002_0_copy_1:67108864+67108864InputFormatClass: org.apache.hadoop.mapred.TextInputFormat
     
    2014-05-16 10:27:07,954 WARN [main] org.apache.hadoop.mapred.YarnChild: Exception running child : java.lang.RuntimeException: java.io.FileNotFoundException: HIVE_PLAN14c8af69-0156-4633-9273-6a812eb91a4c (没有那个文件或文件夹)
        at org.apache.hadoop.hive.ql.exec.Utilities.getMapRedWork(Utilities.java:230)
        at org.apache.hadoop.hive.ql.io.HiveInputFormat.init(HiveInputFormat.java:255)
        at org.apache.hadoop.hive.ql.io.HiveInputFormat.pushProjectionsAndFilters(HiveInputFormat.java:381)
        at org.apache.hadoop.hive.ql.io.HiveInputFormat.pushProjectionsAndFilters(HiveInputFormat.java:374)
        at org.apache.hadoop.hive.ql.io.CombineHiveInputFormat.getRecordReader(CombineHiveInputFormat.java:540)
        at org.apache.hadoop.mapred.MapTask$TrackedRecordReader.<init>(MapTask.java:168)
        at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:409)
        at org.apache.hadoop.mapred.MapTask.run(MapTask.java:342)
        at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:168)
        at java.security.AccessController.doPrivileged(Native Method)
        at javax.security.auth.Subject.doAs(Subject.java:415)
        at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1548)
        at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:163)
    Caused by: java.io.FileNotFoundException: HIVE_PLAN14c8af69-0156-4633-9273-6a812eb91a4c (没有那个文件或文件夹)
        at java.io.FileInputStream.open(Native Method)
        at java.io.FileInputStream.<init>(FileInputStream.java:146)
        at java.io.FileInputStream.<init>(FileInputStream.java:101)
        at org.apache.hadoop.hive.ql.exec.Utilities.getMapRedWork(Utilities.java:221)
        ... 12 more
     
    2014-05-16 10:27:07,957 INFO [main] org.apache.hadoop.mapred.Task: Runnning cleanup for the task

    来源: <http://sxxxxxxxxxx:19888/jobhistory/logs/ST-L10-10-back-tj-yarn10:8034/container_1400136017046_0026_01_000030/attempt_1400136017046_0026_m_000000_0/hadoop>
     

    12java.lang.OutOfMemoryError: GC overhead limit exceeded 
    分析:这个是JDK6新添的错误类型。是发生在GC占用大量时间为释放非常小空间的时候发生的,是一种保护机制。解决方式是,关闭该功能,能够加入JVM的启动參数来限制使用内存: -XX:-UseGCOverheadLimit 
    加入位置是:mapred-site.xml 里新增项:mapred.child.java.opts 内容:-XX:-UseGCOverheadLimit
    參考14 


    13hive   hive 0.10.0为了运行效率考虑,简单的查询,就是仅仅是select,不带count,sum,group by这种,都不走map/reduce,直接读取hdfs文件进行filter过滤。这样做的优点就是不新开mr任务,运行效率要提高不少,可是不好的地方就是用户界面不友好,有时候数据量大还是要等非常长时间,可是又没有不论什么返回。

    改这个非常easy,在hive-site.xml里面有个配置參数叫

    hive.fetch.task.conversion

    将这个參数设置为more,简单查询就不走map/reduce了,设置为minimal,就不论什么简单select都会走map/reduce。


     參考14 

    14 执行mr 任务的时候提示:

    错误日志
    Container [pid=30486,containerID=container_1400229396615_0011_01_000012] is running beyond physical memory limits. Current usage: 1.0 GB of 1 GB physical memory used; 1.7 GB of 2.1 GB virtual memory used. Killing container. Dump of the process-tree for container_1400229396615_0011_01_000012 : |- PID PPID PGRPID SESSID CMD_NAME USER_MODE_TIME(MILLIS) SYSTEM_TIME(MILLIS) VMEM_USAGE(BYTES) RSSMEM_USAGE(PAGES) FULL_CMD_LINE |- 30501 30486 30486 30486 (java) 3924 322 1720471552 262096 /opt/jdk1.7.0_55/bin/java -Djava.net.preferIPv4Stack=true -Dhadoop.metrics.log.level=WARN -Xmx1024m -XX:-UseGCOverheadLimit -Djava.io.tmpdir=/home/nodemanager/local/usercache/hadoop/appcache/application_1400229396615_0011/container_1400229396615_0011_01_000012/tmp -Dlog4j.configuration=container-log4j.properties -Dyarn.app.container.log.dir=/home/hadoop/logs/nodemanager/logs/application_1400229396615_0011/container_1400229396615_0011_01_000012 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA org.apache.hadoop.mapred.YarnChild 30.30.30.39 47925 attempt_1400229396615_0011_m_000000_0 12 |- 30486 12812 30486 30486 (bash) 0 0 108642304 302 /bin/bash -c /opt/jdk1.7.0_55/bin/java -Djava.net.preferIPv4Stack=true -Dhadoop.metrics.log.level=WARN -Xmx1024m -XX:-UseGCOverheadLimit -Djava.io.tmpdir=/home/nodemanager/local/usercache/hadoop/appcache/application_1400229396615_0011/container_1400229396615_0011_01_000012/tmp -Dlog4j.configuration=container-log4j.properties -Dyarn.app.container.log.dir=/home/hadoop/logs/nodemanager/logs/application_1400229396615_0011/container_1400229396615_0011_01_000012 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA org.apache.hadoop.mapred.YarnChild 30.30.30.39 47925 attempt_1400229396615_0011_m_000000_0 12 1>/home/hadoop/logs/nodemanager/logs/application_1400229396615_0011/container_1400229396615_0011_01_000012/stdout 2>/home/hadoop/logs/nodemanager/logs/application_1400229396615_0011/container_1400229396615_0011_01_000012/stderr Container killed on request. Exit code is 143 Container exited with a non-zero exit code 143
    


     
    解决方法:
     
    以下的參数是关于mapreduce任务执行时的内存设置,假设有的任务须要可单独配置,就统一配置了。假设有container被kill 能够适当调高
    mapreduce.map.memory.mb    map任务的最大内存
    mapreduce.map.java.opts -Xmx1024M map任务jvm的參数
    mapreduce.reduce.memory.mb  reduce任务的最大内存
    mapreduce.reduce.java.opts -Xmx2560M reduce任务jvm的參数
    mapreduce.task.io.sort.mb 512 Higher memory-limit while sorting data for efficiency.

     
    关闭内存检測进程:
    是在搞不清楚 问什么有的任务就物理内存200多MB ,虚拟内存就飙到2.7G了,预计内存检測进程有问题,并且我有的任务是须要大内存的,为了进度,索性关了,一下子解决全部内存问题。
    yarn.nodemanager.pmem-check-enabled false
    yarn.nodemanager.vmem-check-enabled false


    15 yarn 的webUI 有关的调整:


    1 cluser 页面 application的starttime 和finishtime 都是 UTC格式,改成 +8区时间也就是北京时间。

    ./share/hadoop/yarn/hadoop-yarn-common-2.3.0.jar 里面的webapps.static.yarn.dt.plugins.js
     
    或者源代码包里面:/hadoop-yarn-project/hadoop-yarn/hadoop-yarn-common/src/main/resources/webapps/static/yarn.dt.plugins.js

    加入代码:
    Date.prototype.Format = function (fmt) { //author: meizz 
        var o = {
            "M+": this.getMonth() + 1, //月份 
            "d+": this.getDate(), //日 
            "h+": this.getHours(), //小时 
            "m+": this.getMinutes(), //分 
            "s+": this.getSeconds(), //秒 
            "q+": Math.floor((this.getMonth() + 3) / 3), //季度 
            "S": this.getMilliseconds() //毫秒 
        };
        if (/(y+)/.test(fmt)) fmt = fmt.replace(RegExp.$1, (this.getFullYear() + "").substr(4 - RegExp.$1.length));
        for (var k in o)
        if (new RegExp("(" + k + ")").test(fmt)) fmt = fmt.replace(RegExp.$1, (RegExp.$1.length == 1) ? (o[k]) : (("00" + o[k]).substr(("" + o[k]).length)));
        return fmt;
    };



    同一时候按以下改动下的代码
    function renderHadoopDate(data, type, full) 
    { if (type === 'display' || type === 'filter') { if(data === '0') { return "N/A"; } 
    return new Date(parseInt(data)).Format("yyyy-MM-dd hh:mm:ss"); }




    16  MR1的任务用到DistributedCache 的任务迁移到MR2上出错。原来我里面使用文件名称区分不同的缓存文件,MR2里面分发文件以后仅仅保留的文件名称如:
    application_xxxxxxx/container_14xxxx/part-m-00000
    application_xxxxxxx/container_14xxxx/part-m-00001
    application_xxxxxxx/container_14xxxx/00000_0



    解决方法:每一个缓存文件加入符号链接,链接为 父级名字+文件名称
    DistributedCache.addCacheFile(new URI(path.toString() + "#"+ path.getParent().getName() + "_" + path.getName()),
    configuration);


    这样就会生成带有文件名称的缓存文件





    未完待续

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  • 原文地址:https://www.cnblogs.com/mfrbuaa/p/3780791.html
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