[flink-009]jar包在flink的执行过程
1.执行java包的命令是 ./bin/flink -c MainClassName x.jar
2. bin/flink脚本，启动 类 org.apache.flink.client.cli.CliFrontend 执行jar包。该类位于flink/flink-clients/src/main/java/org/apache/flink/client/cli/CliFrontend.java
3.本地StandAlone集群的任务提交和执行流程
CliFrontend.main()-->
CliFrontend.parseParameters(args)-->
CliFrontend.run(args)-->
CliFrontend.buildProgram(runOptions)-->
CliFrontend.runProgram(customCommandLine, commandLine, runOptions, program)-->
ClusterDescriptor.deploySessionCluster(clusterSpecification)-->
ClusterDescriptor.executeProgram(program, client, userParallelism)-->
PackagedProgram.invokeInteractiveModeForExecution()-->
PackagedProgram.callMainMethod(Class entryClass, String[] args)-->
mainMethod.invoke(null, (Object) args)
任务提交后，不需要发送到JobManger，就在当前进程内执行。
4.分布式集群提交执行
CliFrontend.main()-->
CliFrontend.parseParameters(args)-->
CliFrontend.run(args)-->
CliFrontend.buildProgram(runOptions)-->
CliFrontend.runProgram(customCommandLine, commandLine, runOptions, program)-->
final JobGraph jobGraph = PackagedProgramUtils.createJobGraph(program, configuration, parallelism)-->
clusterDescriptor.deployJobCluster(clusterSpecification,jobGraph,runOptions.getDetachedMode())-->
如果是提交到分布式集群，JobGraph jobGraph = PackagedProgramUtils.createJobGraph(program, configuration, parallelism)这句比较重要，jobGraph是提交给JobManger的，它是JobManger接受的任务对象。
在deployJobCluter函数调用时，Yarn集群的client，会根据jobGraph里的信息，把任务的所有jar包上传到Yarn集群的文件存储home，然后启动任务。