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zlzhang0122 commented on FLINK-23194: ------------------------------------- [~trohrmann] [~fly_in_gis] sorry for the late reply. [~trohrmann] Since startTaskExecutorInContainer is an asynchronous call, so the acceleration of the speed of creation of ContainerLaunchContext is very limited, but it definitely decrease the rpc call of the HDFS namenode. [~fly_in_gis] You are right, when registerLocalResource for keytab, yarnConf and krb5Conf, we will access the HDFS and call the method getFileStatus, cache the ContainerLaunchContext will decrease the pressure on HDFS namenode. And if TaskManager have different resource specs or JVM parameters in the future, we can just not cache these parameters and expose a interface to set them, so, it doesn't matter I think. > Cache and reuse the ContainerLaunchContext and accelarate the progress of > createTaskExecutorLaunchContext on yarn > ----------------------------------------------------------------------------------------------------------------- > > Key: FLINK-23194 > URL: https://issues.apache.org/jira/browse/FLINK-23194 > Project: Flink > Issue Type: Improvement > Components: Deployment / YARN > Affects Versions: 1.13.1, 1.12.4 > Reporter: zlzhang0122 > Priority: Major > Fix For: 1.14.0 > > > When starting the TaskExecutor in container on yarn, this will create > ContainerLaunchContext for n times(n represent the number of the TaskManager). > When I examined the progress of this creation, I found that most of them were > in common and had nothing to do with the particular TaskManager except the > launchCommand. We can create ContainerLaunchContext once and reuse it. Only > the launchCommand need to create separately for every particular TaskManager. > So I propose that we can cache and reuse the ContainerLaunchContext object to > accelerate this creation progress. > I think this can have some benefit like below: > # this can accelerate the creation of ContainerLaunchContext and also the > start of the TaskExecutor, especially under the situation of massive > TaskManager. > # this can decrease the pressure of the HDFS, etc. > # this can also avoid the suddenly failure of the HDFS or yarn, etc. > We have implemented this on our production environment. So far there has no > problem and have a good benefit. Please let me know if there's any point that > I haven't considered. -- This message was sent by Atlassian Jira (v8.3.4#803005)