精通Hadoop运维与管理:实战指南

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《Expert Hadoop® Administration》是一本专为Hadoop管理员设计的权威指南,作者Sam R. Alapati以其在大规模Hadoop管理方面的经验为基础,提供了创建、配置、保护、管理和优化生产Hadoop集群的实用知识。这本书涵盖了广泛的Hadoop环境和工作流程,旨在帮助读者理解Hadoop架构并掌握关键技能。 本书分为五个主要部分: 1. **入门与基础**:这部分首先介绍Hadoop及其环境,接着深入探讨其架构,包括创建和配置简单的以及完全分布式的Hadoop集群。章节1-4引导读者从零开始构建和规划集群,确保对Hadoop生态有扎实的理解。 2. **Hadoop应用框架**:这部分聚焦于MapReduce、Spark等框架在Hadoop集群中的运行。第5章讲解MapReduce框架(以及Hive和Pig),而第6-7章分别阐述如何在Spark框架下运行和优化应用程序。 3. **数据管理与高可用性**:这一阶段重点关注HDFS(Hadoop分布式文件系统)的核心作用,包括NameNode操作、数据保护、存储管理等。第8-11章详细介绍了NameNode的角色、HDFS命令、权限管理和数据保护策略,以及如何实现高可用性和数据一致性。 4. **数据移动、资源调度与安全**:通过第12-15章,读者将学习如何在Hadoop中移动数据,如何利用YARN进行资源分配和任务调度,并了解如何通过Oozie管理和安全Hadoop系统。 5. **监控、优化与故障排查**:最后部分涉及日常任务管理、性能监控、日志分析以及针对Hadoop和Spark的深度调优技巧。从第16-22章,读者将掌握如何识别问题、调整配置以提高性能,以及如何在出现问题时进行故障诊断和修复。 《Expert Hadoop® Administration》不仅适合Hadoop新手,也对已有一定经验的管理员具有参考价值,因为书中提供了大量实例和实操指导,使读者无论使用何种Hadoop发行版或运行何种应用程序都能受益匪浅。此外,该书还包含了安装虚拟环境(如VirtualBox和Linux)以及克隆虚拟机的步骤,方便读者在本地进行实践和实验。整个系列的目标是帮助读者构建完整的数据分析生态系统,以解决实际问题和挖掘数据价值。
2017-08-22 上传
The professional's one-stop guide to this open-source, Java-based big data framework, Professional Hadoop is the complete reference and resource for experienced developers looking to employ Apache Hadoop in real-world settings. Written by an expert team of certified Hadoop developers, committers, and Summit speakers, this book details every key aspect of Hadoop technology to enable optimal processing of large data sets. Designed expressly for the professional developer, this book skips over the basics of database development to get you acquainted with the framework's processes and capabilities right away. The discussion covers each key Hadoop component individually, culminating in a sample application that brings all of the pieces together to illustrate the cooperation and interplay that make Hadoop a major big data solution. Coverage includes everything from storage and security to computing and user experience, with expert guidance on integrating other software and more., Hadoop is quickly reaching significant market usage, and more and more developers are being called upon to develop big data solutions using the Hadoop framework. This book covers the process from beginning to end, providing a crash course for professionals needing to learn and apply Hadoop quickly., Configure storage, UE, and in-memory computing Integrate Hadoop with other programs including Kafka and Storm Master the fundamentals of Apache Big Top and Ignite Build robust data security with expert tips and advice, Hadoop's popularity is largely due to its accessibility. Open-source and written in Java, the framework offers almost no barrier to entry for experienced database developers already familiar with the skills and requirements real-world programming entails. Professional Hadoop gives you the practical information and framework-specific skills you need quickly.
2014-03-07 上传
Hadoop_hbase 1.处理hadoop的datanode宕机 cd path/to/hadoop 走到hadoop的bin目录 ./hadoop-daemon.sh start datanode ./hadoop-daemon.sh start tasktracker 2.处理hadoop的namenode宕机 ./hadoop-daemon.sh start namenode ./hadoop-daemon.sh start tasktracker 3.如果是新添加一个节点,需要执行以下步骤: 首先,把新节点的 IP或主机名 加入主节点(master)的 conf/slaves 文件。 然后登录新的从节点,执行以下命令: $ cd path/to/hadoop $ bin/hadoop-daemon.sh start datanode $ bin/hadoop-daemon.sh start tasktracker 然后就可以在master机器上运行balancer,执行负载均衡 $bin/hadoop balancer 4.处理hbase的regionserver宕机的办法 ./hbase-daemon.sh start regionserver ./hbase-deamon.sh start zookeeper//只针对有zookeeper的regionserver而且是机子需要重启的情况 5.处理hbase的master宕机的办法 ./hbase-daemon.sh start master ./hbase-daemon.sh start zookeeper//可选 6.完全重启整个集群的过程 首先是用root权限关闭所有节点的防火墙,/etc/init.d/iptables stop 然后启动hadoop集群 来到hadoop的安装路径执行: ./start-all.sh 待到集群全部成功启动之后两分钟之后执行关闭hadoop文件系统的安全模式, ./hadoop dfsadmin -safemode leave 对于hadoop文件系统安全模式的解释,如下 NameNode在启动的时候首先进入安全模式,如果datanode丢失的block达到一定的比例(1- dfs.safemode.threshold.pct),则系统会一直处于安全模式状态即只读状态。 dfs.safemode.threshold.pct(缺省值0.999f)表示HDFS启动的时候,如果DataNode上报的block个数达到了 元数据记录的block个数的0.999倍才可以离开安全模式,否则一直是这种只读模式。如果设为1则HDFS永远是处于SafeMode。 有两个方法离开这种安全模式 (1)修改dfs.safemode.threshold.pct为一个比较小的值,缺省是0.999。 (2)hadoop dfsadmin -safemode leave命令强制离开 用户可以通过dfsadmin -safemode $value来操作安全模式,参数$value的说明如下: enter – 进入安全模式 leave – 强制NameNode离开安全模式 get – 返回安全模式是否开启的信息 wait – 等待,一直到安全模式结束。 //因为我们后面要用到

Java对hdfs操作报如下错误,请问怎么解决?错误如下:Exception in thread "main" java.io.IOException: (null) entry in command string: null chmod 0700 I:\tmp\hadoop-22215\mapred\staging\222151620622033\.staging at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:770) at org.apache.hadoop.util.Shell.execCommand(Shell.java:866) at org.apache.hadoop.util.Shell.execCommand(Shell.java:849) at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:733) at org.apache.hadoop.fs.RawLocalFileSystem.mkOneDirWithMode(RawLocalFileSystem.java:491) at org.apache.hadoop.fs.RawLocalFileSystem.mkdirsWithOptionalPermission(RawLocalFileSystem.java:532) at org.apache.hadoop.fs.RawLocalFileSystem.mkdirs(RawLocalFileSystem.java:509) at org.apache.hadoop.fs.FilterFileSystem.mkdirs(FilterFileSystem.java:305) at org.apache.hadoop.mapreduce.JobSubmissionFiles.getStagingDir(JobSubmissionFiles.java:133) at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:144) 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:422) at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698) at org.apache.hadoop.mapreduce.Job.submit(Job.java:1287) at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1308) at com.sl.maxTemperature.main(maxTemperature.java:41)

2023-04-23 上传