Linux-Hadoop集群测试

文章目录

一、通过UI界面查看Hadoop运行状态

Hadoop集群正常启动后，它默认开放了两个端口
9870
和
8088
，分别用于监控HDFS集群和YARN集群。通过UI界面可以方便地进行集群的管理和查看，只需要在本地操作系统的浏览器输入集群服务的IP和对应的端口号即可访问。

1、查看HDFS集群状态

在浏览器里访问http://master:9870
不能通过主机名master加端口9870的方式，原因在于没有在hosts文件里IP与主机名的映射，现在只能通过IP地址加端口号的方式访问：`http://192.168.1.101:9870![请添加图片描述](https://img-blog.csdnimg.cn/812f96600c2c45ba88ffb62d32e6c9ef.png)
修改宿主机的C:\Windows\System32\drivers\etc\hosts文件，增加hadoop集群主机名与IP地址的映射
此时，访问http://master:9870，从图中可以看出HDFS集群状态显示正常
单击导航条上的【Datanodes】，查看数据节点信息
访问slave1的数据节点（DataNode）

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点开【Utilities - 实用工具】下拉菜单，选择【Browse the file system - 浏览文件系统】
此时HDFS上没有任何文件或文件夹
在HDFS上创建一个目录·BigData·，既可以在WebUI上创建，也可以通过shell命令创建
执行命令：·hdfs dfs -mkdir /BigData·

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在Hadoop WebUI界面查看刚才创建的目录
单击【BigData】右边的删除按钮
单击【Delete】按钮
查看四个功能按钮
在Hadoop WebUI界面里创建目录
在弹出的【Create Directory】对话里输入目录名 -BigData

单击【Create】按钮

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2、查看YARN集群状态

访问http://master:8088/cluster，从图中可以看出YARN集群状态显示正常
单击【About】链接

二、Hadoop集群 —— 词频统计

1、启动Hadoop集群

在master虚拟机上执行命令：start-all.sh

2、在虚拟机上准备文件

在master虚拟机上创建test.txt文件

3、文件上传到HDFS指定目录

上传test.txt文件到HDFS的/BigData目录（如果没有就创建目录）
利用HDFS命令查看文件是否上传成功

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利用Hadoop WebUI查看文件是否上传成功

4、运行词频统计程序的jar包

查看Hadoop自带示例的jar包
执行命令：hadoop jar ./hadoop-mapreduce-examples-3.3.4.jar wordcount /BigData/test.txt /wc_result

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[root@master mapreduce]# hadoop jar ./hadoop-mapreduce-examples-3.3.4.jar wordcount /BigData/test.txt /wc_result2022-11-16 10:42:43,067 INFO client.DefaultNoHARMFailoverProxyProvider: Connecting to ResourceManager at master/192.168.1.101:8032
2022-11-16 10:42:43,852 INFO mapreduce.JobResourceUploader: Disabling Erasure Coding for path: /tmp/hadoop-yarn/staging/root/.staging/job_1668566449679_0001
2022-11-16 10:42:45,107 INFO input.FileInputFormat: Total input files to process :12022-11-16 10:42:45,555 INFO mapreduce.JobSubmitter: number of splits:1
2022-11-16 10:42:45,904 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1668566449679_0001
2022-11-16 10:42:45,904 INFO mapreduce.JobSubmitter: Executing with tokens: []2022-11-16 10:42:46,107 INFO conf.Configuration: resource-types.xml not found
2022-11-16 10:42:46,108 INFO resource.ResourceUtils: Unable to find'resource-types.xml'.2022-11-16 10:42:46,567 INFO impl.YarnClientImpl: Submitted application application_1668566449679_0001
2022-11-16 10:42:46,607 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1668566449679_0001/
2022-11-16 10:42:46,608 INFO mapreduce.Job: Running job: job_1668566449679_0001
2022-11-16 10:42:54,755 INFO mapreduce.Job: Job job_1668566449679_0001 running in uber mode :false2022-11-16 10:42:54,758 INFO mapreduce.Job:  map 0% reduce 0%
2022-11-16 10:42:59,841 INFO mapreduce.Job:  map 100% reduce 0%
2022-11-16 10:43:04,876 INFO mapreduce.Job:  map 100% reduce 100%
2022-11-16 10:43:05,899 INFO mapreduce.Job: Job job_1668566449679_0001 completed successfully
2022-11-16 10:43:06,021 INFO mapreduce.Job: Counters: 54
        File System Counters
                FILE: Number of bytes read=98
                FILE: Number of bytes written=552153
                FILE: Number of readoperations=0
                FILE: Number of large readoperations=0
                FILE: Number of writeoperations=0
                HDFS: Number of bytes read=190
                HDFS: Number of bytes written=60
                HDFS: Number of readoperations=8
                HDFS: Number of large readoperations=0
                HDFS: Number of writeoperations=2
                HDFS: Number of bytes read erasure-coded=0
        Job Counters 
                Launched map tasks=1
                Launched reduce tasks=1
                Data-local map tasks=1
                Total time spent by all maps in occupied slots (ms)=2619
                Total time spent by all reduces in occupied slots (ms)=3007
                Total time spent by all map tasks (ms)=2619
                Total time spent by all reduce tasks (ms)=3007
                Total vcore-milliseconds taken by all map tasks=2619
                Total vcore-milliseconds taken by all reduce tasks=3007
                Total megabyte-milliseconds taken by all map tasks=2681856
                Total megabyte-milliseconds taken by all reduce tasks=3079168
        Map-Reduce Framework
                Map input records=5
                Map output records=16
                Map output bytes=154
                Map output materialized bytes=98
                Input splitbytes=100
                Combine input records=16
                Combine output records=8
                Reduce input groups=8
                Reduce shuffle bytes=98
                Reduce input records=8
                Reduce output records=8
                Spilled Records=16
                Shuffled Maps =1
                Failed Shuffles=0
                Merged Map outputs=1
                GC time elapsed (ms)=109
                CPU time spent (ms)=1680
                Physical memory (bytes)snapshot=511000576
                Virtual memory (bytes)snapshot=5589139456
                Total committed heap usage (bytes)=388497408
                Peak Map Physical memory (bytes)=295997440
                Peak Map Virtual memory (bytes)=2790174720
                Peak Reduce Physical memory (bytes)=215003136
                Peak Reduce Virtual memory (bytes)=2798964736
        Shuffle Errors
                BAD_ID=0CONNECTION=0IO_ERROR=0WRONG_LENGTH=0WRONG_MAP=0WRONG_REDUCE=0
        File Input Format Counters 
                Bytes Read=90
        File Output Format Counters 
                Bytes Written=60