FlinkSQL源码解析1--提交任务过程

提交入口

org.apache.flink.table.api.internal.TableEnvironmentImpl#executeSql

@Override

public TableResult executeSql(String statement) {

List<Operation> operations = getParser().parse(statement);

if (operations.size() != 1) {

throw new TableException(UNSUPPORTED_QUERY_IN_EXECUTE_SQL_MSG);

}

Operation operation = operations.get(0);

return executeInternal(operation);

}

sql--》operation--》Transformation--》pipeline(StreamGraph)--》JobGraph--》deployJobCluster

sql-->SqlNodeList-->flinkPlanner.validate(sqlNode)-->Optional<Operation> operation = SqlNodeConverters.convertSqlNode(validated, context);

org.apache.flink.table.api.internal.TableEnvironmentImpl#executeQueryOperation

executeQueryOperation--》

List<Transformation<?>> transformations = translate(Collections.singletonList(sinkOperation));--》

org.apache.flink.table.planner.delegation.PlannerBase#translate

Pipeline pipeline =

execEnv.createPipeline(

transformations, tableConfig.getConfiguration(), defaultJobName);

final StreamGraph streamGraph = executionEnvironment.generateStreamGraph(transformations); // StreamGraph是Pipeline接口的实现类

org.apache.flink.streaming.api.environment.StreamExecutionEnvironment#executeAsync(org.apache.flink.streaming.api.graph.StreamGraph)

JobClient jobClient = execEnv.executeAsync(pipeline);

3.1、final PipelineExecutor executor = getPipelineExecutor();

CompletableFuture<JobClient> jobClientFuture =

executor.execute(streamGraph, configuration, userClassloader);

3.2、createJobGraph#new StreamingJobGraphGenerator(

userClassLoader, streamGraph, jobID, serializationExecutor)

.createJobGraph();

org.apache.flink.client.deployment.executors.AbstractJobClusterExecutor#execute

final ClusterClientProvider<ClusterID> clusterClientProvider =

clusterDescriptor.deployJobCluster(

clusterSpecification, jobGraph, configAccessor.getDetachedMode

return CompletableFuture.completedFuture(

new ClusterClientJobClientAdapter<>(

clusterClientProvider, jobGraph.getJobID(), userCodeClassloader));