Status

Motivation

Flink ETL job consumes data from Source Table and produces result to Sink Table after computation. Source Table creates relationship with Sink Table through Flink ETL job. Flink needs a mechanism for users to report these relationships with customized listeners to other systems, such as meta system Datahub [1], Atlas [2] and meta store we mentioned in FLINK-276 [3].
I'd like to introduce JobExecutionListener to users in this FLIP. They can implement the listener to receive job events when the job is created, finished, canceled and failed. The information in the job event includes

1. JobID, the identity id for job

2. Job name, the name of given job

3. Source table list of the job

4. Sink table list of the job

Public Interfaces

Job Execution Listener

Added JobExecutionListener listens to the status changes in the job. Job creates JobEvent for each status when it changes, and notify specific method in JobExecutionListener. Users can implement different listeners according to their needs, such as Datahub listener or Atlas listener.

/**
 * When job status is changed in job manager, it will generate job event to
 * notify job execution listener.
 */
@PublicEvolving
public interface JobExecutionListener extends AutoCloseable {
    /* Start the listener with job configuration. */
    void start(Configuration configuration) throws Exception;

    /* Notify listener when job is created, it will be notified once. */
    void onCreated(JobCreatedEvent createdEvent);

    /* Notify listener when job is finished. */
    void onFinished(JobFinishedEvent finishedEvent);

    /* Notify listener when job is canceled. */
    void onCanceled(JobCanceledEvent canceledEvent);

    /* Notify listener when job is failed. */
    void onFailed(JobFailedEvent failedEvent);

    /* Event for job status is changed. */
    interface JobEvent {
        /* Job id. */
        JobID jobId();
        /* Job name. */
        String jobName();
        /* Timestamp for current job status. */
        long timestamp();
    }
    
    /* Source/Sink information. */
    @PublicEvolving
    interface SourceSinkInformation {
        /* Use catalog.database.table for table api and use source/sink name for datastream. */
        String name();
        /* Source/Sink operator name. */
        String operatorName();
        /* Configuration for source/sink. */
        Configuration configuration();
    }

    /* Event for job is created. */
    @PublicEvolving
    interface JobCreatedEvent extends JobEvent {
        /* Scan source list. */
        List<SourceSinkInformation> scanSources();

        /* Sink list. */
        List<SourceSinkInformation> sinks();
    }

    /* Event for job is finished. */
    @PublicEvolving
    interface JobFinishedEvent extends JobEvent { }

    /* Event for job is canceled. */
    @PublicEvolving
    interface JobCanceledEvent extends JobEvent { }

    /* Event for job is failed. */
    @PublicEvolving
    interface JobFailedEvent extends JobEvent {
        Throwable exception();
    }
}

Config Customized Listener

Users should add their listener to the classpath of flink cluster, and use the listener with the option in JobManagerOptions as followed

jobmanager.execution.listener: {user's listener class}

Proposed Changes

The basic information such as job id and name are in ExecutionGraph, but the source and sink list are not. They should be added to ExecutionGraph for JobExecutionListener too.

Flink jobs are created from Planner(sql and table) and DataStream, then they are converted to Transformation and StreamGraph. Finally, the jobs are submitted as JobGraph and job managers create ExecutionGraph from it. The operations of source/sink list are as follows.

SourceScan in Planner and DataStreamSource in DataStream contain source information such as table name, source configuration. But these information is hidden in the Source which is an interface when the SourceScan and DataStreamSource  are converted to Transformation. We should add source information in the conversion of SourceScan/DataStreamSource->Transformation->StreamNode, then we can add Map<JobVertexID, SourceSinkInformation> sources in JobGraph and ExecutionGraph.

Similar to sources, Sink and DataStreamSink contain sink information such as table names and configuration. We should add sink information in the conversion of Sink/DataStreamSink->Transformation->StreamNode, then we can add Map<JobVertexID, SourceSinkInformation> sources in JobGraph and ExecutionGraph too.

JobManager creates instances of user's JobExecutionListener and gets sources/sinks information from ExecutionGraph. When the status of job is changed, JobManager creates specific job events and notifies the JobExecutionListener.

Plan For The Future

1. Add ddl listener and submit listener to report fields in tables and supports customized validations for tables and jobs.

2. This FLIP only supports scan source, we can support lookup join source later.

3. Job vertex listener, such as scheduling and execution status of vertex, execution status of subtask, etc.