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大数据套件Hermes-MR索引插件该怎么使用

发表于:2025-01-23 作者:千家信息网编辑
千家信息网最后更新 2025年01月23日,大数据套件Hermes-MR索引插件该怎么使用,相信很多没有经验的人对此束手无策,为此本文总结了问题出现的原因和解决方法,通过这篇文章希望你能解决这个问题。Hermes是多维分析利器,使用步骤分为索引
千家信息网最后更新 2025年01月23日大数据套件Hermes-MR索引插件该怎么使用

大数据套件Hermes-MR索引插件该怎么使用,相信很多没有经验的人对此束手无策,为此本文总结了问题出现的原因和解决方法,通过这篇文章希望你能解决这个问题。

Hermes是多维分析利器,使用步骤分为索引创建和数据分发两个步骤。

Hermes目前尚未集成到TBDS套件(3.0版本)中且外部有客户需要在自己部署的集群上使用Hermes组件,这里就遇到了Hermes与外部Hadoop集群的适配问题。

Hermes与某客户外部集群集成后,一次压测时(2T数据量,445604010行,477字段全索引)使用单机版的Hermes索引创建插件由于数据量过大,出现Out of Memory等异常现象导致索引插件程序崩溃,实际产生的数据索引量和实际数据量差距很大。基于以上考虑,数平提供了基于MR的索引创建插件,提升索引创建效率。

以下记录了基于hadoop2.2版本的MR索引插件和外部集群的适配过程。

一.集群相关组件版本

Hermes版本:hermes-2.1.0-1.x86_64
Hadoop集群版本:Hadoop 2.7.1.2.3.0.0-2557
Hermes-index-MR插件使用的Hadoop-common:hadoop-common-2.2.0.jar

二.Hermes-MR插件使用方法

1.需修改配置:(以$HERMES_INDEX_MR_HOME表示插件主目录)
  • $HERMES_INDEX_MR_HOME/conf/hermes.properties
    修改内容:hermes.zkConnectionString更改为本集群的zookeeper地址;hermes.hadoop.conf.dir修改为本集群的hadoop配置目录;hermes.hadoop.home修改为本集群的hadoop安装主目录。

  • $HERMES_INDEX_MR_HOME/conf/hermes_index.properties
    修改内容:hermes.hadoop.conf更改为本集群的hadoop配置目录;hermes.index.user.conf更改为hermes-MR-index插件的用户配置文件绝对地址。

  • $HERMES_INDEX_MR_HOME/conf/user_conf.xml
    修改内容:该配置即hermes-MR-index插件的用户配置文件,一般默认配置项即可。需要注意的是插件支持指定被索引文件的字段分隔符。配置项为higo.input.record.split和higo.input.record.ascii.split。其中higo.input.record.ascii.split的优先级高于前者,指定higo.input.record.ascii.split后第一个配置将无效。其中higo.input.record.split的value项直接指定分隔符内容(如|,\,;等);higo.input.record.ascii.split指定分隔符对应的ascii码数字。

2.运行插件
  • 执行命令:在插件主目录下(其中labcluster为HDFS的nn通过做HA的名称):

    sh bin/submit_index_job.sh \clk_tag_info_test_500 \20160722 \hdfs://labcluster/apps/hive/market_mid/clk_tag_info_test/ \hdfs://labcluster/user/hermes/demo_dir/clk_tag_info_test_500/ \hdfs://labcluster/user/hermes/demo_dir/schema/clk_tag_info_test_500_hermes.schema \key_id \3


  • 参数介绍:
    sh bin/submit_index_job.sh表名 数据时间(时间分区) 源数据在HDFS上地址(单文件或目录) 索引输出的HDFS目录 schema文件在HDFS的地址(需手动创建上传) 主键 索引分片数

3.日志观察:

创建索引插件在运行后会在$HERMES_INDEX_MR_HOME/logs输出hermes.logindex.log。前者为hermes相关的记录,后者为索引创建过程记录(包括MR任务相关信息)。正常情况下index.log会记录提交MR任务成功与否以及相关jobid,可通过HADOOP的RM管理页面看到状态,index.log也会记录Map/Reduce的进度,完成后会输出Job ${job.id} completed successfully以及MR任务相关信息(如图)。如果出现错误日志,需具体分析,下文会总结本次集群适配遇到的一系列问题,目前已在TBDS3.0(Hadoop2.7)集群里测试通过。

4.适配基本过程

前面已提到Hermes-MR-index插件使用的Hadoop-common.jar版本为2.2,但集群本身为Hadoop2.7。在直接执行插件创建索引时出现以下"奇怪"异常。

Diagnostics: Exception from container-launch.Container id: container_e07_1469110119300_0022_02_000001Exit code: 255Stack trace: ExitCodeException exitCode=255: at org.apache.hadoop.util.Shell.runCommand(Shell.java:545)at org.apache.hadoop.util.Shell.run(Shell.java:456)at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:722)at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:211)at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)at java.util.concurrent.FutureTask.run(FutureTask.java:262)at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)at java.lang.Thread.run(Thread.java:745)

查询了所有异常日志后一无所获,和数平Hadoop大神请教后,建议替换Hermes-MR-index插件里用到Hadoop*.jar包为集群内版本。这样开始还是遇到了一系列问题,最终在hadoop2.7环境下Hermes-MR-index插件运行正常。

整理了以下思路进行适配:1.将Hermes-MR-index插件用到的hadoop-*.jar全部替换为集群内使用的版本;2.执行插件看日志错误一般会因为新版(2.7)有新的jar包依赖关系,提示错误,根据错误提示缺少的类找到对应jar包,添加到$HERMES_INDEX_MR_HOME/lib目录,重复此操作,直到不再提示缺少类错误。3.执行以上操作时同时需要注意缺少的类关联的jar包的版本必须和实际集群用到的版本一致(重复步骤2时发现的问题)。

5.问题汇总

插件和集群的适配过程中遇到的问题总结如下:

  • 配置项mapreduce.framework.name异常

    2016-07-21 15:39:51,522 (ERROR org.apache.hadoop.security.UserGroupInformation 1600): PriviledgedActionException as:root (auth:SIMPLE) cause:java.io.IOException: Cannot initialize Cluster. Please check your configuration for mapreduce.framework.name and the correspond server addresses.Exception in thread "main" java.io.IOException: Cannot initialize Cluster. Please check your configuration for mapreduce.framework.name and the correspond server addresses.


    解决方法:查看集群的hadoop相关配置(即hermes.properties里指定的hadoop配置路径里配置目录,也可以复制集群的出来,自己做单独修改)mapred-site.xml里的mapreduce.framework.name配置项内容为yarn-tez,但目前插件只支持到yarn,故单独修改此项配置为yarn后保存,异常解决。

  • 插件无法向集群提交任务

    2016-07-21 20:14:49,355 (ERRORorg.apache.hadoop.security.UserGroupInformation 1600): PriviledgedActionException as:hermes (auth:SIMPLE) cause:java.io.IOException: Failed to run job : org.apache.hadoop.security.AccessControlException: User hermes cannot submit applications to queue root.default


    解决方法:使用hermes用户向yarn提交任务时无权限提示。修改yarn集群的权限允许hermes即可。TBDS3.0有很方便的访问控制页面进行操作。

  • 提交任务时变量替换异常

    Exception message:/hadoop/data1/hadoop/yarn/local/usercache/hermes/appcache/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001/launch_container.sh: line 9: $PWD:$HADOOP_CONF_DIR:/usr/hdp/current/hadoop-client/*:/usr/hdp/current/hadoop-client/lib/*:/usr/hdp/current/hadoop-hdfs-client/*:/usr/hdp/current/hadoop-hdfs-client/lib/*:/usr/hdp/current/hadoop-yarn-client/*:/usr/hdp/current/hadoop-yarn-client/lib/*:$PWD/mr-framework/hadoop/share/hadoop/mapreduce/*:$PWD/mr-framework/hadoop/share/hadoop/mapreduce/lib/*:$PWD/mr-framework/hadoop/share/hadoop/common/*:$PWD/mr-framework/hadoop/share/hadoop/common/lib/*:$PWD/mr-framework/hadoop/share/hadoop/yarn/*:$PWD/mr-framework/hadoop/share/hadoop/yarn/lib/*:$PWD/mr-framework/hadoop/share/hadoop/hdfs/*:$PWD/mr-framework/hadoop/share/hadoop/hdfs/lib/*:$PWD/mr-framework/hadoop/share/hadoop/tools/lib/*:/usr/hdp/${hdp.version}/hadoop/lib/hadoop-lzo-0.6.0.${hdp.version}.jar:/etc/hadoop/conf/secure:job.jar/job.jar:job.jar/classes/:job.jar/lib/*:$PWD/*: bad substitution/hadoop/data1/hadoop/yarn/local/usercache/hermes/appcache/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001/launch_container.sh: line 67: $JAVA_HOME/bin/java -Dlog4j.configuration=container-log4j.properties -Dyarn.app.container.log.dir=/hadoop/data1/yarn/container-logs/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA -Dhdp.version=${hdp.version} -Xmx5120m org.apache.hadoop.mapreduce.v2.app.MRAppMaster 1>/hadoop/data1/yarn/container-logs/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001/stdout 2>/hadoop/data1/yarn/container-logs/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001/stderr : bad substitutionStack trace: ExitCodeException exitCode=1: /hadoop/data1/hadoop/yarn/local/usercache/hermes/appcache/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001/launch_container.sh: line 9: $PWD:$HADOOP_CONF_DIR:/usr/hdp/current/hadoop-client/*:/usr/hdp/current/hadoop-client/lib/*:/usr/hdp/current/hadoop-hdfs-client/*:/usr/hdp/current/hadoop-hdfs-client/lib/*:/usr/hdp/current/hadoop-yarn-client/*:/usr/hdp/current/hadoop-yarn-client/lib/*:$PWD/mr-framework/hadoop/share/hadoop/mapreduce/*:$PWD/mr-framework/hadoop/share/hadoop/mapreduce/lib/*:$PWD/mr-framework/hadoop/share/hadoop/common/*:$PWD/mr-framework/hadoop/share/hadoop/common/lib/*:$PWD/mr-framework/hadoop/share/hadoop/yarn/*:$PWD/mr-framework/hadoop/share/hadoop/yarn/lib/*:$PWD/mr-framework/hadoop/share/hadoop/hdfs/*:$PWD/mr-framework/hadoop/share/hadoop/hdfs/lib/*:$PWD/mr-framework/hadoop/share/hadoop/tools/lib/*:/usr/hdp/${hdp.version}/hadoop/lib/hadoop-lzo-0.6.0.${hdp.version}.jar:/etc/hadoop/conf/secure:job.jar/job.jar:job.jar/classes/:job.jar/lib/*:$PWD/*: bad substitution/hadoop/data1/hadoop/yarn/local/usercache/hermes/appcache/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001/launch_container.sh: line 67: $JAVA_HOME/bin/java -Dlog4j.configuration=container-log4j.properties -Dyarn.app.container.log.dir=/hadoop/data1/yarn/container-logs/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001 -Dyarn.app.container.log.filesize=0 -Dhadoop.root.logger=INFO,CLA -Dhdp.version=${hdp.version} -Xmx5120m org.apache.hadoop.mapreduce.v2.app.MRAppMaster 1>/hadoop/data1/yarn/container-logs/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001/stdout 2>/hadoop/data1/yarn/container-logs/application_1469110119300_0004/container_e07_1469110119300_0004_02_000001/stderr : bad substitution


    解决方法:从bad substitution可以判定为是某些配置的参数没有正常替换造成。查看具体异常里面用到的变量有$PWD,$JAVA_HOME,${hdp.version}和$HADOOP_CONF_DIR以上变量在hadoop的配置文件里找到逐个替换为实际值而不用变量直到错误提示不再出现。实践中发现是因为hdp.version这个变量没有值造成的,可以在hadoop配置里增加一项此配置或者将用到该变量的地方替换为实际值即可。

  • 一个"奇怪的"错误

    2016-07-22 15:25:40,657 (INFO org.apache.hadoop.mapreduce.Job 1374): Job job_1469110119300_0022 failed with state FAILED due to: Application application_1469110119300_0022 failed 2 times due to AM Container for appattempt_1469110119300_0022_000002 exited with  exitCode: 255For more detailed output, check application tracking page:http://bdlabnn2:8088/cluster/app/application_1469110119300_0022Then, click on links to logs of each attempt.Diagnostics: Exception from container-launch.Container id: container_e07_1469110119300_0022_02_000001Exit code: 255Stack trace: ExitCodeException exitCode=255: at org.apache.hadoop.util.Shell.runCommand(Shell.java:545)at org.apache.hadoop.util.Shell.run(Shell.java:456)at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:722)at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:211)at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)


    解决方法:这个错误是最难解决的错误,最终是用本文提到的插件和集群版本适配的办法解决,解决方法及思路见"适配基本过程"。替换或者增加了的jar包列表如下:

    jackson-core-2.2.3.jarjersey-json-1.9.jarjersey-client-1.9.jarjersey-core-1.9.jarjackson-xc-1.9.13.jarjersey-guice-1.9.jarjersey-server-1.9.jarjackson-jaxrs-1.9.13.jarcommons-io-2.5.jarhtrace-core-3.1.0-incubating.jarhermes-index-2.1.2.jarhadoop-cdh4-hdfs-2.2.0.jarhadoop-cdh4-core-2.2.0.jarhadoop-yarn-common-2.7.2.jarhadoop-yarn-client-2.7.2.jarhadoop-yarn-api-2.7.2.jarhadoop-mapreduce-client-jobclient-2.7.2.jarhadoop-mapreduce-client-core-2.7.2.jarhadoop-mapreduce-client-common-2.7.2.jarhadoop-hdfs-2.7.2.jarhadoop-common-2.7.2.jarhadoop-auth-2.7.2.jar


  • 无法连接yarn的RM任务提交端口
    在TBDS3.0的环境下提交任务后日志提示重连RMserver失败,一直提示该错误
    解决方法:查看启动进程发现内部集群接收mr请求的端口为8032,修改项里的RMserveraddress配置的端口后任务通过

  • 适配完成替换/新增所有jar包后出现的异常

    Exception in thread "main" java.lang.VerifyError: class org.codehaus.jackson.xc.JaxbAnnotationIntrospector overrides final method findDeserializer.(Lorg/codehaus/jackson/map/introspect/Annotated;)Ljava/lang/Object;at java.lang.ClassLoader.defineClass1(Native Method)at java.lang.ClassLoader.defineClass(ClassLoader.java:800)at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)at java.net.URLClassLoader.defineClass(URLClassLoader.java:449)at java.net.URLClassLoader.access$100(URLClassLoader.java:71)at java.net.URLClassLoader$1.run(URLClassLoader.java:361)at java.net.URLClassLoader$1.run(URLClassLoader.java:355)at java.security.AccessController.doPrivileged(Native Method)at java.net.URLClassLoader.findClass(URLClassLoader.java:354)at java.lang.ClassLoader.loadClass(ClassLoader.java:425)at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)at java.lang.ClassLoader.loadClass(ClassLoader.java:358)at java.lang.Class.getDeclaredMethods0(Native Method)at java.lang.Class.privateGetDeclaredMethods(Class.java:2615)at java.lang.Class.getDeclaredMethods(Class.java:1860)at com.sun.jersey.core.reflection.MethodList.getAllDeclaredMethods(MethodList.java:70)at com.sun.jersey.core.reflection.MethodList.(MethodList.java:64)at com.sun.jersey.core.spi.component.ComponentConstructor.getPostConstructMethods(ComponentConstructor.java:131)at com.sun.jersey.core.spi.component.ComponentConstructor.(ComponentConstructor.java:123)at com.sun.jersey.core.spi.component.ProviderFactory.__getComponentProvider(ProviderFactory.java:165)at com.sun.jersey.core.spi.component.ProviderFactory._getComponentProvider(ProviderFactory.java:159)at com.sun.jersey.core.spi.component.ProviderFactory.getComponentProvider(ProviderFactory.java:153)at com.sun.jersey.core.spi.component.ProviderServices.getComponent(ProviderServices.java:251)


    解决方法:查询这个异常类属于jackson*.jar,那问题就出在这一系列的包身上,检查发现Hermes-MR-index插件的lib目录下有

    jackson-core-asl-1.7.3.jarjackson-mapper-asl-1.7.3.jarjackson-core-asl-1.9.13.jarjackson-mapper-asl-1.9.13.jar


    这两个包的版本有2个,检查Hadoop集群用的版本为1.9.13,将插件lib目录下的1.7.3版本的两个包删除后,插件正常运行。原因归结为jar包版本冲突。

  • 提示无法找到MR框架路径

    Exception in thread "main" java.lang.IllegalArgumentException: Could not locate MapReduce framework name 'mr-framework' in mapreduce.application.classpathat org.apache.hadoop.mapreduce.v2.util.MRApps.setMRFrameworkClasspath(MRApps.java:231)at org.apache.hadoop.mapreduce.v2.util.MRApps.setClasspath(MRApps.java:258)at org.apache.hadoop.mapred.YARNRunner.createApplicationSubmissionContext(YARNRunner.java:458)at org.apache.hadoop.mapred.YARNRunner.submitJob(YARNRunner.java:285)at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:240)at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1290)at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1287)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:1657)at org.apache.hadoop.mapreduce.Job.submit(Job.java:1287)at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1308)at com.tencent.hermes.hadoop.job.HermesIndexJob.subRun(HermesIndexJob.java:262)at com.tencent.hermes.hadoop.job.HermesIndexJob.run(HermesIndexJob.java:122)at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)at com.tencent.hermes.hadoop.job.SubmitIndexJob.call(SubmitIndexJob.java:194)at com.tencent.hermes.hadoop.job.SubmitIndexJob.main(SubmitIndexJob.java:101)


    解决方法:提示mapreduce.application.framework.path配置里没找到mr框架的路径,检查mapred-site.xml的该配置项确实配置有异常,在该配置项里增加mr框架路径后通过(以下红色为新增配置)。

mapreduce.application.classpath      $PWD/mr-framework/hadoop/share/hadoop/mapreduce/*:$PWD/mr-framework/hadoop/share/hadoop/mapreduce/lib/*:$PWD/mr-framework/hadoop/share/hadoop/common/*:$PWD/mr-framework/hadoop/share/hadoop/common/lib/*:$PWD/mr-framework/hadoop/share/hadoop/yarn/*:$PWD/mr-framework/hadoop/share/hadoop/yarn/lib/*:$PWD/mr-framework/hadoop/share/hadoop/hdfs/*:$PWD/mr-framework/hadoop/share/hadoop/hdfs/lib/*:/usr/hdp/2.2.0.0-2041/hadoop/lib/hadoop-lzo-0.6.0.2.2.0.0-2041.jar:/etc/hadoop/conf/secure

看完上述内容,你们掌握大数据套件Hermes-MR索引插件该怎么使用的方法了吗?如果还想学到更多技能或想了解更多相关内容,欢迎关注行业资讯频道,感谢各位的阅读!

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