MapReduce(十三): MapReduce拓扑

本文深入探讨了MapReduce计算环境中JobTracker与TaskTracker的心跳交互机制,详细解释了网络拓扑如何通过树形结构组织并记录主机位置,以及如何通过配置文件动态解析主机归属。

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JobTracker启动后,第一次收到TaskTracker的心跳消息,对收到的TaskTracker所在的主机加入到MapReduce计算环境的网络拓扑中。网络拓扑以树形的方式记录:ROOT(0)->NetworkLocation(1)->Host(2),()号中的数字是网络的level,ROOT是虚节点,整个MapReduce计算网络的根,level是0;ROOT下分多个NetworkLocation,在默认配置一下只有一个“/default/rack/”一个网络,所有的Host都添加在该节点下,Network Location的level是1。用户也可以配置参数“topology.script.file.name”,指定某个脚本文件对心跳消息中接收到的TaskTracker主机进行动态解析指定该Host位于哪个NetworkLocation。NetworkLocation下是主机,每个Network Location下存在多个主机,level是2。

整个网络的拓扑信息ROOT(0)->NetworkLocation(1)->Host(2)记录在NetworkTopology类中。在JobTracker类中hostnameToNodeMap还记录了主机名称对应的节点信息,nodesAtMaxLevel记录了所有NetworkLocation节点信息。
[root@hadoop01 jars]# hadoop jar film.jar CleanDriver /film/input /film/outputs/cleandata 25/03/29 14:28:19 INFO client.RMProxy: Connecting to ResourceManager at hadoop01/192.168.20.20:8032 25/03/29 14:28:19 INFO input.FileInputFormat: Total input paths to process : 1 25/03/29 14:28:19 INFO mapreduce.JobSubmitter: number of splits:1 25/03/29 14:28:19 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1743079842141_0006 25/03/29 14:28:20 INFO impl.YarnClientImpl: Submitted application application_1743079842141_0006 25/03/29 14:28:20 INFO mapreduce.Job: The url to track the job: http://hadoop01:8088/proxy/application_1743079842141_0006/ 25/03/29 14:28:20 INFO mapreduce.Job: Running job: job_1743079842141_0006 25/03/29 14:28:26 INFO mapreduce.Job: Job job_1743079842141_0006 running in uber mode : false 25/03/29 14:28:26 INFO mapreduce.Job: map 0% reduce 0% 25/03/29 14:28:31 INFO mapreduce.Job: map 100% reduce 0% 25/03/29 14:28:36 INFO mapreduce.Job: map 100% reduce 100% 25/03/29 14:28:36 INFO mapreduce.Job: Job job_1743079842141_0006 completed successfully 25/03/29 14:28:36 INFO mapreduce.Job: Counters: 49 File System Counters FILE: Number of bytes read=6 FILE: Number of bytes written=245465 FILE: Number of read operations=0 FILE: Number of large read operations=0 FILE: Number of write operations=0 HDFS: Number of bytes read=8669 HDFS: Number of bytes written=0 HDFS: Number of read operations=6 HDFS: Number of large read operations=0 HDFS: Number of write operations=2 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)=2452 Total time spent by all reduces in occupied slots (ms)=2374 Total time spent by all map tasks (ms)=2452 Total time spent by all reduce tasks (ms)=2374 Total vcore-milliseconds taken by all map tasks=2452 Total vcore-milliseconds taken by all reduce tasks=2374 Total megabyte-milliseconds taken by all map tasks=251084
最新发布
03-30
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