hadoop 查看job端口 查看hadoop端口配置

（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、hadoop2和hadoop3端口区别表

 2、查看HDFS集群状态

·在浏览器里访问http://master1:9870

·不能通过主机名master1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://192.168.219.19:9870(地址为实例中的浮动ip)

如果无法加载，查看防火墙是否关闭

·执行命令：systemctl status firewalld

`临时关闭：systemctl stop firewalld

·永久关闭：systemctl disable firewalld

 ·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://master1:9870，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

 ·点开【Utilities】下拉菜单，选择【Browse the file system】

·此时HDFS上什么都无

·在HDFS上创建一个目录BigData，执行命令：hdfs dfs -mkdir /BigData

 ·在Hadoop WebUI界面查看刚才创建的目录

 3、查看YARN集群状态

·访问http://master1:8088/cluster，从图中可以看出YARN集群状态显示正常。

 ·单击[About]链接

 （二）Hadoop集群初体验 —— 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

 ·利用HDFS命令查看文件是否上传成功

 ·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：cd $HADOOP_HOME/share/hadoop/mapreduce

·执行：ll

 ·执行命令：hadoop jar ./hadoop-mapreduce-examples-3.3.4.jar wordcount /BigData/test.txt /wc_result

[root@master mapreduce]# hadoop jar ./hadoop-mapreduce-examples-3.3.4.jar wordcount /BigData/test.txt /wc_result
2022-10-04 12:40:30,559 INFO client.DefaultNoHARMFailoverProxyProvider: Connecting to ResourceManager at master/192.168.1.101:8032
2022-10-04 12:40:31,501 INFO mapreduce.JobResourceUploader: Disabling Erasure Coding for path: /tmp/hadoop-yarn/staging/root/.staging/job_1664901602347_0001
2022-10-04 12:40:32,416 INFO input.FileInputFormat: Total input files to process : 1
2022-10-04 12:40:32,911 INFO mapreduce.JobSubmitter: number of splits:1
2022-10-04 12:40:33,204 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1664901602347_0001
2022-10-04 12:40:33,205 INFO mapreduce.JobSubmitter: Executing with tokens: []
2022-10-04 12:40:33,418 INFO conf.Configuration: resource-types.xml not found
2022-10-04 12:40:33,418 INFO resource.ResourceUtils: Unable to find 'resource-types.xml'.
2022-10-04 12:40:33,939 INFO impl.YarnClientImpl: Submitted application application_1664901602347_0001
2022-10-04 12:40:33,974 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1664901602347_0001/
2022-10-04 12:40:33,974 INFO mapreduce.Job: Running job: job_1664901602347_0001
2022-10-04 12:40:45,146 INFO mapreduce.Job: Job job_1664901602347_0001 running in uber mode : false
2022-10-04 12:40:45,147 INFO mapreduce.Job:  map 0% reduce 0%
2022-10-04 12:40:52,319 INFO mapreduce.Job:  map 100% reduce 0%
2022-10-04 12:40:59,512 INFO mapreduce.Job:  map 100% reduce 100%
2022-10-04 12:41:00,531 INFO mapreduce.Job: Job job_1664901602347_0001 completed successfully
2022-10-04 12:41:00,694 INFO mapreduce.Job: Counters: 54
        File System Counters
                FILE: Number of bytes read=98
                FILE: Number of bytes written=552153
                FILE: Number of read operations=0
                FILE: Number of large read operations=0
                FILE: Number of write operations=0
                HDFS: Number of bytes read=191
                HDFS: Number of bytes written=60
                HDFS: Number of read operations=8
                HDFS: Number of large read operations=0
                HDFS: Number of write operations=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)=4860
                Total time spent by all reduces in occupied slots (ms)=5021
                Total time spent by all map tasks (ms)=4860
                Total time spent by all reduce tasks (ms)=5021
                Total vcore-milliseconds taken by all map tasks=4860
                Total vcore-milliseconds taken by all reduce tasks=5021
                Total megabyte-milliseconds taken by all map tasks=4976640
                Total megabyte-milliseconds taken by all reduce tasks=5141504
        Map-Reduce Framework
                Map input records=6
                Map output records=16
                Map output bytes=154
                Map output materialized bytes=98
                Input split bytes=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)=235
                CPU time spent (ms)=1180
                Physical memory (bytes) snapshot=318394368
                Virtual memory (bytes) snapshot=5478535168
                Total committed heap usage (bytes)=141692928
                Peak Map Physical memory (bytes)=211103744
                Peak Map Virtual memory (bytes)=2734690304
                Peak Reduce Physical memory (bytes)=107290624
                Peak Reduce Virtual memory (bytes)=2743844864
        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=91
        File Output Format Counters
                Bytes Written=60

·查看输出目录/wc_result，执行命令：hdfs dfs -ls /wc_result

 ·查看词频统计结果，执行命令：hdfs dfs -cat /wc_result/*

 5、在HDFS集群UI界面查看结果文件

·在HDFS集群UI界面，查看/wc_result目录

 ·单击结果文件part-r-00000

·单击【Download】，下载结果文件到本地

·利用记事本打开该文件

 6、在YARN集群UI界面查看程序运行状态

·访问http://master:8088，看到FINISHED和SUCCEEDED

 ·单击应用标识application_1664901602347_0001，查看应用的运行详情