window本地部署单机hadoop,修改配置文件和脚本如下,只记录关键配置和步骤,仅供参考

  • hadoop-2.6.5
  • spark-2.3.3

1.配置文件core-site.xml

<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://localhost:9000</value>
</property>
<property>
<name>hadoop.data.dir</name>
<value>file:/D:/02_bigdata/hadoop-2.6.5/data</value>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>${hadoop.data.dir}</value>
</property>
<property>
<name>hadoop.http.staticuser.user</name>
<value>${user.name}</value>
</property>
</configuration>

2.配置文件hdfs-site.xml

<configuration>
<property>
<name>dfs.namenode.http-address</name>
<value>0.0.0.0:50070</value>
</property>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>${hadoop.data.dir}/dfs/name</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>${hadoop.data.dir}/dfs/data</value>
</property>
</configuration>

3.配置文件mapred-site.xml

<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>

4.配置文件yarn-site.xml

<configuration>

<!-- Site specific YARN configuration properties -->
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>512</value>
</property>
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<property>
<name>yarn.log-aggregation.retain-seconds</name>
<value>2592000</value>
</property>
<property>
<name>yarn.log.server.url</name>
<value>http://localhost:19888/jobhistory/logs</value>
</property>
<property>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>hdfs://localhost:9000/user/merit/yarn-logs/</value>
</property> <property>
<name>yarn.nodemanager.address</name>
<value>localhost:8041</value>
</property>
</configuration>

5.环境设置脚本hadoop-env.cmd

@rem 设置JAVA_HOME
set JAVA_HOME=D:\06_devptools\jdk1_8_0_73

6.环境设置脚本yarn-env.cmd

@rem 设置yarn组件的日志文件名称
set YARN_RESOURCEMANAGER_OPTS=-Dyarn.log.file=YARN-RESOURCEMANAGER.log -Dhadoop.log.file=YARN-RESOURCEMANAGER.log
set HADOOP_NODEMANAGER_OPTS=-Dyarn.log.file=YARN-NODEMANAGER.log -Dhadoop.log.file=YARN-NODEMANAGER.log
set HADOOP_HISTORYSERVER_OPTS=-Dyarn.log.file=YARN-HISTORYSERVER.log -Dhadoop.log.file=YARN-HISTORYSERVER.log

7.启动脚本start-dfs.cmd

@rem 设置Path
set PATH=%HADOOP_HOME%\bin;%PATH% start "Apache Hadoop Distribution" hadoop namenode
start "Apache Hadoop Distribution" hadoop datanode

8.启动脚本start-yarn.cmd

@rem 设置Path
set PATH=%HADOOP_HOME%\bin;%PATH%
@rem start resourceManager
start "Apache Hadoop Distribution" yarn resourcemanager
@rem start nodeManager
start "Apache Hadoop Distribution" yarn nodemanager @rem 修改默认的historyserver启动脚本,将yarn historyserver改为mapred historyserver
@rem start historyserver
start "Apache Hadoop Distribution" mapred historyserver

9.测试yarn运行mapreduce任务

C:\Windows\system32>D:\02_bigdata\hadoop-2.6.5\bin\hadoop jar D:\02_bigdata\hadoop-2.6.5\share\hadoop\mapreduce\hadoop-mapreduce-examples-2.6.5.jar pi 12 3
Number of Maps = 12
Samples per Map = 3
Wrote input for Map #0
Wrote input for Map #1
Wrote input for Map #2
Wrote input for Map #3
Wrote input for Map #4
Wrote input for Map #5
Wrote input for Map #6
Wrote input for Map #7
Wrote input for Map #8
Wrote input for Map #9
Wrote input for Map #10
Wrote input for Map #11
Starting Job
22/06/18 14:09:30 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
22/06/18 14:09:30 INFO input.FileInputFormat: Total input paths to process : 12
22/06/18 14:09:30 INFO mapreduce.JobSubmitter: number of splits:12
22/06/18 14:09:30 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1655532552208_0001
22/06/18 14:09:30 INFO impl.YarnClientImpl: Submitted application application_1655532552208_0001
22/06/18 14:09:30 INFO mapreduce.Job: The url to track the job: http://LAPTOP-TC4A0SCV:8088/proxy/application_1655532552208_0001/
22/06/18 14:09:30 INFO mapreduce.Job: Running job: job_1655532552208_0001
22/06/18 14:09:43 INFO mapreduce.Job: Job job_1655532552208_0001 running in uber mode : false
22/06/18 14:09:43 INFO mapreduce.Job: map 0% reduce 0%
22/06/18 14:09:55 INFO mapreduce.Job: map 8% reduce 0%
22/06/18 14:09:58 INFO mapreduce.Job: map 17% reduce 0%
22/06/18 14:10:02 INFO mapreduce.Job: map 25% reduce 0%
22/06/18 14:10:05 INFO mapreduce.Job: map 42% reduce 0%
22/06/18 14:10:06 INFO mapreduce.Job: map 50% reduce 0%
22/06/18 14:10:08 INFO mapreduce.Job: map 58% reduce 0%
22/06/18 14:10:16 INFO mapreduce.Job: map 58% reduce 19%
22/06/18 14:10:21 INFO mapreduce.Job: map 67% reduce 19%
22/06/18 14:10:23 INFO mapreduce.Job: map 75% reduce 19%
22/06/18 14:10:24 INFO mapreduce.Job: map 75% reduce 25%
22/06/18 14:10:25 INFO mapreduce.Job: map 100% reduce 25%
22/06/18 14:10:27 INFO mapreduce.Job: map 100% reduce 100%
22/06/18 14:10:27 INFO mapreduce.Job: Job job_1655532552208_0001 completed successfully
22/06/18 14:10:27 INFO mapreduce.Job: Counters: 49
File System Counters
FILE: Number of bytes read=270
FILE: Number of bytes written=1413432
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=3182
HDFS: Number of bytes written=215
HDFS: Number of read operations=51
HDFS: Number of large read operations=0
HDFS: Number of write operations=3
Job Counters
Launched map tasks=12
Launched reduce tasks=1
Rack-local map tasks=12
Total time spent by all maps in occupied slots (ms)=321884
Total time spent by all reduces in occupied slots (ms)=53392
Total time spent by all map tasks (ms)=160942
Total time spent by all reduce tasks (ms)=26696
Total vcore-milliseconds taken by all map tasks=160942
Total vcore-milliseconds taken by all reduce tasks=26696
Total megabyte-milliseconds taken by all map tasks=164804608
Total megabyte-milliseconds taken by all reduce tasks=27336704
Map-Reduce Framework
Map input records=12
Map output records=24
Map output bytes=216
Map output materialized bytes=336
Input split bytes=1766
Combine input records=0
Combine output records=0
Reduce input groups=2
Reduce shuffle bytes=336
Reduce input records=24
Reduce output records=0
Spilled Records=48
Shuffled Maps =12
Failed Shuffles=0
Merged Map outputs=12
GC time elapsed (ms)=877
CPU time spent (ms)=8426
Physical memory (bytes) snapshot=3624378368
Virtual memory (bytes) snapshot=4172316672
Total committed heap usage (bytes)=2562195456
Shuffle Errors
BAD_ID=0
CONNECTION=0
IO_ERROR=0
WRONG_LENGTH=0
WRONG_MAP=0
WRONG_REDUCE=0
File Input Format Counters
Bytes Read=1416
File Output Format Counters
Bytes Written=97
Job Finished in 57.683 seconds
Estimated value of Pi is 3.44444444444444444444

10.测试yarn运行spark任务

D:\02_bigdata\spark-2.3.3-bin-hadoop2.6>bin\spark-submit.cmd --master yarn --deploy-mode cluster --class org.apache.spark.examples.SparkPi examples\jars\spark-examples_2.11-2.3.3.jar 122
22/06/18 14:11:15 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
22/06/18 14:11:15 INFO RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
22/06/18 14:11:15 INFO Client: Requesting a new application from cluster with 1 NodeManagers
22/06/18 14:11:15 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container)
22/06/18 14:11:15 INFO Client: Will allocate AM container, with 1408 MB memory including 384 MB overhead
22/06/18 14:11:15 INFO Client: Setting up container launch context for our AM
22/06/18 14:11:15 INFO Client: Setting up the launch environment for our AM container
22/06/18 14:11:15 INFO Client: Preparing resources for our AM container
22/06/18 14:11:16 WARN Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
22/06/18 14:11:20 INFO Client: Uploading resource file:/C:/Users/merit/AppData/Local/Temp/spark-c2946869-0b04-4a44-97b6-b8389f691999/__spark_libs__3819455099437137527.zip -> file:/C:/Users/merit/.sparkStaging/application_1655532552208_0002/__spark_libs__3819455099437137527.zip
22/06/18 14:11:21 INFO Client: Uploading resource file:/D:/02_bigdata/spark-2.3.3-bin-hadoop2.6/examples/jars/spark-examples_2.11-2.3.3.jar -> file:/C:/Users/merit/.sparkStaging/application_1655532552208_0002/spark-examples_2.11-2.3.3.jar
22/06/18 14:11:22 INFO Client: Uploading resource file:/C:/Users/merit/AppData/Local/Temp/spark-c2946869-0b04-4a44-97b6-b8389f691999/__spark_conf__1079735780404125589.zip -> file:/C:/Users/merit/.sparkStaging/application_1655532552208_0002/__spark_conf__.zip
22/06/18 14:11:22 INFO SecurityManager: Changing view acls to: merit
22/06/18 14:11:22 INFO SecurityManager: Changing modify acls to: merit
22/06/18 14:11:22 INFO SecurityManager: Changing view acls groups to:
22/06/18 14:11:22 INFO SecurityManager: Changing modify acls groups to:
22/06/18 14:11:22 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(merit); groups with view permissions: Set(); users with modify permissions: Set(merit); groups with modify permissions: Set()
22/06/18 14:11:22 INFO Client: Submitting application application_1655532552208_0002 to ResourceManager
22/06/18 14:11:22 INFO YarnClientImpl: Submitted application application_1655532552208_0002
22/06/18 14:11:23 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:23 INFO Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: default
start time: 1655532682804
final status: UNDEFINED
tracking URL: http://LAPTOP-TC4A0SCV:8088/proxy/application_1655532552208_0002/
user: merit
22/06/18 14:11:24 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:25 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:26 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:27 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:28 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:29 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:30 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:31 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:32 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:33 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:34 INFO Client: Application report for application_1655532552208_0002 (state: ACCEPTED)
22/06/18 14:11:35 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:35 INFO Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: 191.168.2.78
ApplicationMaster RPC port: 0
queue: default
start time: 1655532682804
final status: UNDEFINED
tracking URL: http://LAPTOP-TC4A0SCV:8088/proxy/application_1655532552208_0002/
user: merit
22/06/18 14:11:36 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:37 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:38 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:39 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:40 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:41 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:42 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:44 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:45 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:46 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:47 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:48 INFO Client: Application report for application_1655532552208_0002 (state: RUNNING)
22/06/18 14:11:49 INFO Client: Application report for application_1655532552208_0002 (state: FINISHED)
22/06/18 14:11:49 INFO Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: 191.168.2.78
ApplicationMaster RPC port: 0
queue: default
start time: 1655532682804
final status: SUCCEEDED
tracking URL: http://LAPTOP-TC4A0SCV:8088/proxy/application_1655532552208_0002/
user: merit
22/06/18 14:11:49 INFO ShutdownHookManager: Shutdown hook called
22/06/18 14:11:49 INFO ShutdownHookManager: Deleting directory C:\Users\merit\AppData\Local\Temp\spark-0282c910-523b-495d-bae8-f42d4559dac2
22/06/18 14:11:49 INFO ShutdownHookManager: Deleting directory C:\Users\merit\AppData\Local\Temp\spark-c2946869-0b04-4a44-97b6-b8389f691999

window下部署单机hadoop环境的更多相关文章

  1. window下eclipse搭建hadoop环境

    1 生成插件jar 1.1 安装java,ant运行环境 1.2 下载hadoop-2.5.0.tar.gz并解压到指定目录 1.3 下载hadoop2x-eclipse-plugin-master. ...

  2. Linux 下部署单机 hadoop 测试

    最终运行结果展示: 格式化namenode. 开始测试 显示测试进程 浏览器查看效果展示:(虽然还不清楚是什么意思,但是能看到这个效果已经很开心了) 话不多说,进入主题: 1. 安装 VMwareSt ...

  3. Window下搭建foundation apps环境

    Window下搭建foundation apps环境 框架:AngularJS.Foundation, 构建工具:Gulp, 开发环境:node.js. 操作系统:windows (一)环境准备 1 ...

  4. Linux:Ubuntu下部署Web运行环境

    Linux:Ubuntu下部署Web运行环境 本次博客将会从三部分内容详述Ubuntu系统下Web运行环境的配置: 依次是:FTP服务器的搭建.MYSQL数据库的搭建.JDK的安装等. 参考文章如下: ...

  5. window下搭建c开发环境(GNU环境的安装)

    一.在windows平台上安装GNU环境 windows操作系统不自带GNU环境,如果需要开发跨平台的C语言程序,那么需要给windows安装GNU环境 windows下的两款GNU环境:MinGW和 ...

  6. Linux下部署Samba服务环境的操作记录

    关于Linux和Windows系统之间的文件传输,很多人选择使用FTP,相对较安全,但是有时还是会出现一些问题,比如上传文件时,文件名莫名出现乱码,文件大小改变等问题.相比较来说,使用Samba作为文 ...

  7. Window下Tomcat单机部署多应用

    1. 新增tomcat相关环境变量 如上图,有两个tomcat,tomcat1和tomcat2 2.修改catalina.bat 文件 第一个tomcat不变 第二个tamcat的catalina.b ...

  8. 【hadoop】——window下elicpse连接hadoop集群基础超详细版

    1.Hadoop开发环境简介 1.1 Hadoop集群简介 Java版本:jdk-6u31-linux-i586.bin Linux系统:CentOS6.0 Hadoop版本:hadoop-1.0.0 ...

  9. window 下Qt for android 环境搭建

    ******************************************************************* 转自http://www.cnblogs.com/rophie/ ...

  10. Mac下部署Android开发环境附加NDK

    作为开发者,我们深有体会,不管是进行什么开发,为了部署开发环境,我们往往需要折腾很长时间.查阅很多资料才能完成,而且这次折腾完了,下次到了另一台新电脑上又得重新来过,整个部署过程记得还好,要是不记得又 ...

随机推荐

  1. 面对科技公司的制裁,俄罗斯放出封印7年的神兽:RuTracker

    大家好,我是DD! 最近俄乌冲突引发的科技公司站队,Oracle.微软.三星等全球知名科技公司都开始对俄罗斯实施制裁与封锁.就连崇尚自由的开源社区GitHub也发文会严格限制俄罗斯获得维持其咄咄逼人的 ...

  2. C++ lambda 内 std::move 失效问题的思考

    最近在学习 C++ Move 时,有看到这样一个代码需求:在 lambda 中,将一个捕获参数 move 给另外一个变量. 看似一个很简单常规的操作,然而这个 move 动作却没有生效. 具体代码如下 ...

  3. 题解 - Japanese Student Championship 2021

    前言:这场的题解由于蓝桥杯比赛拖延几天才发 关于本篇题解,目前还是有部分题没有解答出来正在加油补题ing 补题链接:Here A - Competition 题意:给定 \(X,Y,Z\) 代表的意义 ...

  4. 如何设置IDEA代码风格为Google风格,使用Google风格format

    1.在Github仓库寻找:google style 为了节省大家时间直接放链接了:Here 2.进到项目 找到名为intellij-java-google-style.xml 文件 Ctrl + F ...

  5. 四、mycat垂直分库

    系列导航 一.Mycat实战---为什么要用mycat 二.Mycat安装 三.mycat实验数据 四.mycat垂直分库 五.mycat水平分库 六.mycat全局自增 七.mycat-ER分片 一 ...

  6. Ubuntu 18.04安装arm-linux-gcc交叉编译器的两种方法(附下载地址)

    方法一:   我们都知道Ubuntu有一个专门用来安装软件的工具apt,我们可以用它来全自动安装arm-linux-gcc.   此方法安装的是最新版的,但是此方法需要FQ,否则99%会失败,这就是为 ...

  7. vue-devtools调试工具

  8. [QML]从零开始QML开发(二)QML开发,浅谈控件、槽函数、锚等基本概念。QML和C++怎么交互?贯彻落实MVC原则

    [QML]从零开始QML开发(二)QML开发,浅谈控件.槽函数.锚等基本概念.QML和C++怎么交互?贯彻落实MVC原则 先看代码: import QtQuick 2.12 import QtQuic ...

  9. php开发中常见的漏洞点(一) 基础sql注入

    前言 本系列为小迪2022的学习笔记,仅用于自我记录. 正文 在一般情况下,一个网站的首页大致如下 在上方存在着各种各样的导航标签.链接.而一般情况下网站的导航会用参数进行索引的编写,比如id.pag ...

  10. OB指定开源版本MySQL模式单节点安装

    OB指定开源版本MySQL模式单节点安装 yum源处理 yum install -y yum-utils yum-config-manager --add-repo https://mirrors.a ...