（转）yarn 集群部署，遇到的问题小结

link：http://blog.csdn.net/uniquechao/article/details/26449761

 

版本信息： hadoop 2.3.0  hive 0.11.0

 

1. Application Master 无法访问

 

    点击application mater 链接，出现 http 500 错误，java.lang.Connect.exception：

    问题是由于设定web ui时，50030 端口对应的ip地址为0.0.0.0，导致application master 链接无法定位。

 

解决办法:

     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 无法访问 和 container 打不开

     点击 Tracking URL:History无法访问

       问题是 history service 没有启动

      

  解决办法:

     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

相关链接:http://www.iteblog.com/archives/936

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 运行任务 提示： Found interface org.apache.hadoop.mapreduce.Counter, but class was expected

修改pom，重新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 运行任务提示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 默认为0.25 现在调成0.10 

 

参考：

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();

 

参考:https://issues.apache.org/jira/browse/HIVE-4222s

8 hive 任务自动把join装换mapjoin时内存溢出，解决方法：关闭自动装换，11前的版本默认值为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运行时 提示：
failed to evaluate: <unbound>=Class.new(); ，升级到0.13.0

参考https://issues.apache.org/jira/browse/HIVE-4222

https://issues.apache.org/jira/browse/HIVE-3739

 

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，不过不知道为什么我升级12.0 和13.0 ，一运行就报错fileNotfundHIVE_PLANxxxxxxxxx
。ps （参考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：这个是因为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，运行任务报错提示：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 (没有那个文件或目录)

    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 (没有那个文件或目录)

    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很小空间的时候发生的，是一种保护机制。解决方案是，关闭该功能，可以添加JVM的启动参数来限制使用内存： -XX:-UseGCOverheadLimit 
添加位置是：mapred-site.xml 里新增项：mapred.child.java.opts 内容：-XX:-UseGCOverheadLimit

来源： <http://www.cnblogs.com/niocai/archive/2012/07/31/2616252.html>

参考14

 

13hive   hive 0.10.0为了执行效率考虑，简单的查询，就是只是select，不带count,sum,group by这样的，都不走map/reduce，直接读取hdfs文件进行filter过滤。这样做的好处就是不新开mr任务，执行效率要提高不少，但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很长时间，但是又没有任何返回。

改这个很简单，在hive-site.xml里面有个配置参数叫

hive.fetch.task.conversion

将这个参数设置为more，简单查询就不走map/reduce了，设置为minimal，就任何简单select都会走map/reduce。

来源： <http://slaytanic.blog.51cto.com/2057708/1170431>

参考14

14 运行mr 任务的时候提示：

错误日志

1. 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

来源： <http://xxxxxxxxxx:50030/proxy/application_1400229396615_0011/mapreduce/attempts/job_1400229396615_0011/m/FAILED>

解决方法：

 

下面的参数是关于mapreduce任务运行时的内存设置，如果有的任务需要可单独配置，就统一配置了。如果有container被kill 可以适当调高

mapreduce.map.memory.mb    map任务的最大内存

mapreduce.map.java.opts -Xmx1024M map任务jvm的参数

mapreduce.reduce.memory.mb  reduce任务的最大内存

mapreduce.reduce.java.opts -Xmx2560M reduce任务jvm的参数

mapreduce.task.io.sort.mb 512 Higher memory-limit while sorting data for efficiency.

 

摘自：http://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-common/ClusterSetup.html#Configuring_the_Hadoop_Daemons_in_Non-Secure_Mode

 

关闭内存检测进程：

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，估计内存检测进程有问题，而且我有的任务是需要大内存的，为了进度，索性关了，一下子解决所有内存问题。

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
 

或者源码包里面：/hadoop-yarn-project/hadoop-yarn/hadoop-yarn-common/src/main/resources/webapps/static/yarn.dt.plugins.js

添加代码：

1. Date.prototype.Format = function (fmt) { //author: meizz
2. var o = {
3. "M+": this.getMonth() + 1, //月份
4. "d+": this.getDate(), //日
5. "h+": this.getHours(), //小时
6. "m+": this.getMinutes(), //分
7. "s+": this.getSeconds(), //秒
8. "q+": Math.floor((this.getMonth() + 3) / 3), //季度
9. "S": this.getMilliseconds() //毫秒
10. };
11. if (/(y+)/.test(fmt)) fmt = fmt.replace(RegExp.$1, (this.getFullYear() + "").substr(4 - RegExp.$1.length));
12. for (var k in o)
13. if (new RegExp("(" + k + ")").test(fmt)) fmt = fmt.replace(RegExp.$1, (RegExp.$1.length == 1) ? (o[k]) : (("00" + o[k]).substr(("" + o[k]).length)));
14. return fmt;
15. };

同时按下面修改下的代码

1. function renderHadoopDate(data, type, full)
2. { if (type === 'display' || type === 'filter') { if(data === '0') { return "N/A"; }
3. 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区分不同的缓存文件，MR2里面分发文件以后只保留的文件名如：

1. application_xxxxxxx/container_14xxxx/part-m-00000
2. application_xxxxxxx/container_14xxxx/part-m-00001
3. application_xxxxxxx/container_14xxxx/00000_0

解决方法：每个缓存文件添加符号链接，链接为 父级名字+文件名

1. DistributedCache.addCacheFile(new URI(path.toString() + "#"+ path.getParent().getName() + "_" + path.getName()),
2. configuration);

这样就会生成带有文件名的缓存文件