diff --git a/docs/internals/job_scheduling.zh.md b/docs/internals/job_scheduling.zh.md index 87f30014ca8a3854bf54f37b21699cbeb1bf7ea5..d7816774a014cda2aef140dd74b04d4da804b1ff 100644 --- a/docs/internals/job_scheduling.zh.md +++ b/docs/internals/job_scheduling.zh.md @@ -48,7 +48,7 @@ Flink 内部通过 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runt JobManager 会接收到一个 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/jobgraph/ "JobGraph" %},用来描述由多个算子顶点 ({% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/jobgraph/JobVertex.java "JobVertex" %}) 组成的数据流图,以及中间结果数据 ({% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/jobgraph/IntermediateDataSet.java "IntermediateDataSet" %})。每个算子都有自己的可配置属性,比如并行度和运行的代码。除此之外,JobGraph 还包含算子代码执行所必须的依赖库。 -JobManager 会将 JobGraph 转换成 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ "ExecutionGraph" %}。可以将 ExecutionGraph 理解为并行版本的 JobGraph,对于每一个顶点 JobVertex,它的每个并行子 task 都有一个 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ExecutionVertex.java "ExecutionVertex" %}。一个并行度为 100 的算子会有 1 个 JobVertext 和 100 个 ExecutionVertex。ExecutionVertex 会跟踪子 task 的执行状态。 同一个 JobVertext 的所有 ExecutionVertex 都通过 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ExecutionJobVertex.java "ExecutionJobVertex" %} 来持有,并跟踪整个算子的运行状态。ExecutionGraph 除了这些顶点,还包含中间数据结果和分片情况 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/IntermediateResult.java "IntermediateResult" %} 和 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/IntermediateResultPartition.java "IntermediateResultPartition" %}。前者跟踪中间结果的状态,后者跟踪每个分片的状态。 +JobManager 会将 JobGraph 转换成 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ "ExecutionGraph" %}。可以将 ExecutionGraph 理解为并行版本的 JobGraph,对于每一个顶点 JobVertex,它的每个并行子 task 都有一个 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ExecutionVertex.java "ExecutionVertex" %}。一个并行度为 100 的算子会有 1 个 JobVertex 和 100 个 ExecutionVertex。ExecutionVertex 会跟踪子 task 的执行状态。 同一个 JobVertex 的所有 ExecutionVertex 都通过 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/ExecutionJobVertex.java "ExecutionJobVertex" %} 来持有,并跟踪整个算子的运行状态。ExecutionGraph 除了这些顶点,还包含中间数据结果和分片情况 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/IntermediateResult.java "IntermediateResult" %} 和 {% gh_link /flink-runtime/src/main/java/org/apache/flink/runtime/executiongraph/IntermediateResultPartition.java "IntermediateResultPartition" %}。前者跟踪中间结果的状态,后者跟踪每个分片的状态。