使用命令行启动和停止hadoop生态系统的最佳方式是什么? [英] What is best way to start and stop hadoop ecosystem, with command line?
问题描述
我看到有几种方式可以启动hadoop生态系统,
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start-all。 sh& stop-all.sh
其中说它已被弃用使用start-dfs.sh& start-yarn.sh。
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start-dfs.sh,stop-dfs.sh和start-yarn.sh,stop-yarn.sh $> c $ c $ <
hadoop-daemon.sh namenode / datanode和yarn-deamon.sh resourcemanager
编辑:我认为每个命令都必须有一些特定的用例。
$ b解决方案start-all.sh& stop-all.sh:用于一次启动和停止hadoop守护进程。在主机上发布它将启动/停止群集中所有节点上的守护进程。已弃用,因为您已经注意到。
start-dfs.sh,stop-dfs.sh和start-yarn.sh,stop-yarn.sh:与上面相同,但是在主机的所有节点上分别启动/停止HDFS和YARN守护进程。建议现在通过start-all.sh& amp; amp; stop-all.sh
hadoop-daemon.sh namenode / datanode和yarn-deamon.sh resourcemanager :启动个人守护进程机器手动。您需要转到特定节点并发出这些命令。
使用案例:假设您已向集群添加了新的DN,并且只需要启动DN守护程序在这台机器上,
bin / hadoop-daemon.sh启动datanode
注意:如果您想从一台机器启动所有节点上的所有守护进程,则应启用ssh。
希望这会回答您的查询。
I see there are several ways we can start hadoop ecosystem,
start-all.sh & stop-all.sh
Which say it's deprecated use start-dfs.sh & start-yarn.sh.start-dfs.sh, stop-dfs.sh and start-yarn.sh, stop-yarn.sh
hadoop-daemon.sh namenode/datanode and yarn-deamon.sh resourcemanager
EDIT: I think there has to be some specific use cases for each command.
解决方案start-all.sh & stop-all.sh : Used to start and stop hadoop daemons all at once. Issuing it on the master machine will start/stop the daemons on all the nodes of a cluster. Deprecated as you have already noticed.
start-dfs.sh, stop-dfs.sh and start-yarn.sh, stop-yarn.sh : Same as above but start/stop HDFS and YARN daemons separately on all the nodes from the master machine. It is advisable to use these commands now over start-all.sh & stop-all.sh
hadoop-daemon.sh namenode/datanode and yarn-deamon.sh resourcemanager : To start individual daemons on an individual machine manually. You need to go to a particular node and issue these commands.
Use case : Suppose you have added a new DN to your cluster and you need to start the DN daemon only on this machine,
bin/hadoop-daemon.sh start datanode
Note : You should have ssh enabled if you want to start all the daemons on all the nodes from one machine.
Hope this answers your query.
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