Status

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Motivation

FLIP-27 sources are non-trivial to implement. At the same time, it is frequently required to generate arbitrary events with a "mock" source. Such requirement arises both for Flink users, in the scope of demo/PoC projects, and for Flink developers when writing tests. The go-to solution for these purposes so far was using pre-FLIP-27 APIs and implementing data generators as SourceFunctions. 
While the new FLIP-27 Source interface introduces important additional functionality, it comes with significant complexity that presents a hurdle for Flink users for implementing drop-in replacements of the SourceFunction-based data generators.  Meanwhile, SourceFunction is effectively superseded by the Source interface and needs to be eventually deprecated. To fill this gap, this FLIP proposes the introduction of a generic data generator source based on the FLIP-27 API. 

...

package org.apache.flink.api.connector.source.lib;

/**
 * A data source that produces generators N events of an arbitrary type in parallel. 
 * This source is useful for testing and for cases that just need a stream of N events of any kind.
 *
 * <p>The source splits the sequence into as many parallel sub-sequences as there are parallel
 * source readers. Each sub-sequence will be produced in order. Consequently, if the parallelism is
 * limited to one, this will produce one sequence in order.
 *
 * <p>This source is always bounded. For very long sequences user may want to consider executing 
 * the application in a streaming manner, because, despite the fact that the produced stream is bounded, 
 * the end bound is pretty far away.
 */

@Public
public class DataGeneratorSource<OUT>                 
		implements Source<
                        OUT,
                        NumberSequenceSource.NumberSequenceSplit,
                        Collection<NumberSequenceSource.NumberSequenceSplit>>,
                ResultTypeQueryable<OUT> {    

    
     /**
     * Creates a new {@code DataGeneratorSource} that produces <code>count</code>@{code count} records in
     * parallel.
     *
     * @param generatorFunction The generatorfactory functionfor thatinstantiating receivesthe indexreaders numbers andof translates
     *     them into events oftype the output typeSourceReader<OUT, NumberSequenceSplit>.
     * @param count The number of events to be produced.
     * @param typeInfo The type information of the returned events.
     */ 
    public DataGeneratorSource(
            MapFunction<LongSourceReaderFactory<OUT, OUT>NumberSequenceSplit> generatorFunctionsourceReaderFactory,
   long count, TypeInformation<OUT> typeInfo) {...}
    }
  long  count,

     /**
     * Creates aTypeInformation<OUT> newtypeInfo) {@code
 DataGeneratorSource} that produces <code>count</code> records in
  this.sourceReaderFactory   * parallel.
= checkNotNull(sourceReaderFactory);
        this.typeInfo = *checkNotNull(typeInfo);
     * @param generatorFunction Thethis.numberSource generator= function that receives index numbers and translatesnew NumberSequenceSource(0, count);
    }

     /**
     them* intoCreates eventsa ofnew the output type.
     * @param count The number of events to be produced.{@code DataGeneratorSource} that produces @{code count} records in
     * parallel.
     *
     * @param sourceRatePerSecondgeneratorFunction The maximumgenerator numberfunction ofthat eventsreceives perindex secondsnumbers that this generator aimsand translates
     *     tothem produce.into Thisevents isof athe targetoutput numbertype.
 for the whole source and* the@param individualcount parallel
The number of events to *be produced.
    source instances* automatically@param adjusttypeInfo theirThe ratetype takinginformation basedof onthe thereturned {@codeevents.
     */
    public sourceRatePerSecond}DataGeneratorSource(
 and the  source parallelism.
     * @param typeInfoGeneratorFunction<Long, TheOUT> typegeneratorFunction, informationlong ofcount, theTypeInformation<OUT> returned events.typeInfo) {...}
     */}
     

    public DataGeneratorSource(/**
     * Creates a new {@code DataGeneratorSource} that MapFunction<Long, OUT> generatorFunction,
produces @{code count} records in
     * parallel.
     *
  long count,
  * @param generatorFunction The generator function that receives index numbers longand sourceRatePerSecond,translates
     *     them into events of TypeInformation<OUT>the typeInfo) {...}

Proposed Changes

The sum of rates of all parallel readers has to approximate the optional user-defined sourceRatePerSecond parameter. Currently, there is no way for the SourceReaders to acquire the current parallelism of the job they are part of. In order to overcome this limitation, this FLIP proposes an extension of the SourceReaderContext interface with the getRuntimeContext method:

package org.apache.flink.api.connector.source;

/** The class that expose some context from runtime to the {@link SourceReader}. */
@Public
public interface SourceReaderContext {
	...
     /**
     * Gets the context that contains information about the readers runtime, such as the parallelismoutput type.
     * @param count The number of events to be produced.
     * @param sourceRatePerSecond The maximum number of events per seconds that this generator aims
     *     to produce. This is a target number for the whole source and the individual parallel
     *     source instances automatically adjust their rate taking based on the {@code
     * of the source.
  sourceRatePerSecond} and the *source parallelism.
     * @param @returntypeInfo The runtimetype contextinformation of the sourcereturned readerevents.
     */     
    RuntimeContextpublic getRuntimeContextDataGeneratorSource();
}

The respective RuntimeContext is available in the SourceOperator and can be easily provisioned during the anonymous SourceReaderContext initialization in its initReader() method.

With the runtime context accessible via SourceReaderContext, initialization of the data generating readers based on the user-provided generatorFunction could look as follows:

   @Override
    public SourceReader<OUT, NumberSequenceSplit> createReader(SourceReaderContext readerContext)

            GeneratorFunction<Long, OUT> generatorFunction,
            long count,
            double throwssourceRatePerSecond,
 Exception {
        if (maxPerSecond >TypeInformation<OUT> 0typeInfo) {
            int parallelism = readerContext.getRuntimeContext().getNumberOfParallelSubtasks();...}

Where GeneratorFunction supports initialization of class fields via the open() method with access to the local SourceReaderContext.

@Public
public interface GeneratorFunction<T, O> extends Function {

    /**
     * Initialization method for the function. It is called RateLimiteronce rateLimiterbefore =the new GuavaRateLimiter(maxPerSecond, parallelism);actual working process
     * methods.
     */
 return new RateLimitedSourceReader<>(
 default void open(SourceReaderContext readerContext) throws Exception {}

    /** Tear-down method for the function. */
   new MappingIteratorSourceReader<>(readerContext, generatorFunction),
   default void close() throws Exception {}

    O map(T value) throws Exception;
}

A new SourceReaderFactory interface is introduced.

public interface SourceReaderFactory<OUT, SplitT extends SourceSplit> extends Serializable  rateLimiter);{
    SourceReader<OUT, SplitT> newSourceReader(SourceReaderContext readerContext);
}

The generator source delegates the SourceReaders' creation to the factory.

@Public
public class DataGeneratorSource<OUT>          } else {
            return new MappingIteratorSourceReader<>(readerContext, generatorFunction);
		implements Source<
        }
    }

Where RateLimiter

package org.apache.flink.api.common.io.ratelimiting;

/** The interface that can be used to throttle execution of methods. */
public interface RateLimiter extends Serializable {

 OUT,
         /**
     * Acquire method is a blocking call that is intended toNumberSequenceSource.NumberSequenceSplit,
 be used in places where it is required
     * to limit the rate at which results are produced or other functions are called.Collection<NumberSequenceSource.NumberSequenceSplit>>,
     *
     * @return The number of milliseconds thisResultTypeQueryable<OUT> call{ blocked  its caller.
  

    private final SourceReaderFactory<OUT, NumberSequenceSplit> sourceReaderFactory;
 
    @Override
   * @throwspublic InterruptedExceptionSourceReader<OUT, TheNumberSequenceSplit> interrupted exception.
createReader(SourceReaderContext readerContext)
      */
    int acquire() throws Exception InterruptedException;
}

---

It is desirable to reuse the functionality of IteratorSourceReader for cases where the input data type is different from the output (IN: Long from the wrapped NumberSequenceSplit, OUT: the result of applying MapFunction<Long, OUT> function provided by the user). For that purpose, the following changes are proposed:

• New IteratorSourceReaderBase is introduced parameterized with both in and out data types generics.
• All methods apart from pollNext() from the IteratorSourceReader are "pulled-up" to the *Base class
• IteratorSourceReader API remains the same while implementing IteratorSourceReaderBase where input and output types are the same
• New MappingIteratorSourceReader is introduced where input and output types are different (result of applying the MapFunction)

{
        return sourceReaderFactory.newSourceReader(readerContext);
    }
}

Proposed Changes

In order to deliver convenient rate-limiting functionality to the users of the new API, a small addition to the SourceReaderContext is required.

The sum of rates of all parallel readers has to approximate the optional user-defined sourceRatePerSecond parameter. Currently, there is no way for the SourceReaders to acquire the current parallelism of the job they are part of. To overcome this limitation, this FLIP proposes an extension of the SourceReaderContext interface with the currentParallelism() method:

package org.apache.flink.api.connector.source.lib.util;

@Experimental
abstract/** The class IteratorSourceReaderBase<
that expose some context from runtime to the {@link SourceReader}. */
@Public
public interface SourceReaderContext {
	...         
	/**
   E,  O,* IterTGet extendsthe Iterator<E>,current SplitTparallelism extendsof IteratorSourceSplit<E,this IterT>>Source.
     *
   implements SourceReader<O, SplitT> {...}

Reader:

package org.apache.flink.api.connector.source.lib.util;

@Public
public class IteratorSourceReader<
  * @return the parallelism of the Source.
     */
    int     E, IterT extends Iterator<E>, SplitT extends IteratorSourceSplit<E, IterT>>currentParallelism(); 
}

With the parallelism accessible via SourceReaderContext, initialization of the rate-limiting data generating readers can be taken care of by the SourceReaderFactories. For example:

public class GeneratorSourceReaderFactory<OUT>
        extendsimplements IteratorSourceReaderBase<ESourceReaderFactory<OUT, E, IterT, SplitT>NumberSequenceSource.NumberSequenceSplit> {

    public IteratorSourceReaderGeneratorSourceReaderFactory(SourceReaderContext
   context) {
        super(context);
    GeneratorFunction<Long, OUT> generatorFunction, long sourceRatePerSecond){...}

    @Override
    public InputStatus pollNext(ReaderOutput<E> output) {...}

}

package org.apache.flink.api.connector.source.lib.util;

@Experimental
public class MappingIteratorSourceReader<
 SourceReader<OUT, NumberSequenceSource.NumberSequenceSplit> newSourceReader(
            SourceReaderContext readerContext) {
        if (sourceRatePerSecond > 0) {
       E, O, IterT extends Iterator<E>, SplitTint extendsparallelism IteratorSourceSplit<E, IterT>>
= readerContext.currentParallelism();
            RateLimiter extendsrateLimiter IteratorSourceReaderBase<E,= O, IterT, SplitT> {
new GuavaRateLimiter(sourceRatePerSecond, parallelism);
    public MappingIteratorSourceReader(
       return new RateLimitedSourceReader<>(
   SourceReaderContext context, MapFunction<E, O> generatorFunction) {...} 

    @Override
    public InputStatus pollNext(ReaderOutput<O> output)  {...} 
}

RateLimitedSourceReader wraps another SourceReader (delegates to its methods) while rate-limiting the pollNext() calls.

package org.apache.flink.api.connector.source.lib.util;

@Experimental
public class RateLimitedSourceReader<E, SplitT extends SourceSplit>
        implements SourceReader<E, SplitT> {

    private final SourceReader<E, SplitT> sourceReader;
    private final RateLimiter rateLimiter;

    public RateLimitedSourceReader(SourceReader<E, SplitT> sourceReader, RateLimiter rateLimiter) {
        this.sourceReader = sourceReader;
        this.rateLimiter = rateLimiter;
    }

    @Override
    public void start() {
        sourceReader.start();
    }

    @Override
    public InputStatus pollNext(ReaderOutput<E> output) throws Exception {
        rateLimiter.acquire();
        return sourceReader.pollNext(output);
    }
  ...
}

Usage: 

The envisioned usage looks like this:

 new GeneratingIteratorSourceReader<>(readerContext, generatorFunction),
                    rateLimiter);
        } else {
            return new GeneratingIteratorSourceReader<>(readerContext, generatorFunction);
        }
    }
}

Where RateLimiter

/** The interface that can be used to throttle execution of methods. */
interface RateLimiter extends Serializable {

    /**
     * Acquire method is a blocking call that is intended to be used in places where it is required
     * to limit the rate at which results are produced or other functions are called.
     *
     * @return The number of milliseconds this call blocked its caller.
     * @throws InterruptedException The interrupted exception.
     */
    int acquire() throws InterruptedException;
}

---

It is desirable to reuse the functionality of IteratorSourceReader for cases where the input data type is different from the output (IN: Long from the wrapped NumberSequenceSplit, OUT: the result of applying GeneratorFunction<Long, OUT>  provided by the user). For that purpose, the following changes are proposed:

• New IteratorSourceReaderBase is introduced parameterized with both in and out data types generics.
• All methods apart from pollNext() from the IteratorSourceReader are "pulled-up" to the *Base class
• IteratorSourceReader API remains the same while implementing IteratorSourceReaderBase where input and output types are the same
• New GeneratingIteratorSourceReader is introduced where input and output types are different (the result of applying GeneratorFunction)
• GeneratingIteratorSourceReader initializes the GeneratorFunction (if needed), by calling open() method within its start() method.

package org.apache.flink.api.connector.source.lib.util;

@Experimental
abstract class IteratorSourceReaderBase<
                E, O, IterT extends Iterator<E>, SplitT extends IteratorSourceSplit<E, IterT>>
        implements SourceReader<O, SplitT> {...}

Reader:

package org.apache.flink.api.connector.source.lib.util;

@Public
public class IteratorSourceReader<
                E, IterT extends Iterator<E>, SplitT extends IteratorSourceSplit<E, IterT>>
        extends IteratorSourceReaderBase<E, E, IterT, SplitT> {

    public IteratorSourceReader(SourceReaderContext context) {
        super(context);
    }

    @Override
    public InputStatus pollNext(ReaderOutput<E> output) {...}

}

package org.apache.flink.api.connector.source.lib.util;

@Experimental
public class GeneratingIteratorSourceReader<
                E, O, IterT extends Iterator<E>, SplitT extends IteratorSourceSplit<E, IterT>>
        extends IteratorSourceReaderBase<E, O, IterT, SplitT> {

    public GeneratingIteratorSourceReader(
            SourceReaderContext context, GeneratorFunction<E, O> generatorFunction) {...} 

    @Override
    public InputStatus pollNext(ReaderOutput<O> output)  {...} 

    
}

RateLimitedSourceReader wraps another SourceReader (delegates to its methods) while rate-limiting the pollNext() calls.

package org.apache.flink.api.connector.source.lib.util;

@Experimental
class RateLimitedSourceReader<E, SplitT extends SourceSplit>
        implements SourceReader<E, SplitT> {

    private final SourceReader<E, SplitT> sourceReader;
    private final RateLimiter rateLimiter;

    public RateLimitedSourceReader(SourceReader<E, SplitT> sourceReader, RateLimiter rateLimiter) {
        this.sourceReader = sourceReader;
        this.rateLimiter = rateLimiter;
    }

    @Override
    public void start() {
        sourceReader.start();
    }

    @Override
    public InputStatus pollNext(ReaderOutput<E> output) throws Exception {
        rateLimiter.acquire();
        return sourceReader.pollNext(output);
    }
  ...
}

Usage: 

The envisioned usage for functions that do not contain any class fields that need initialization looks like this:

int count = 1000;
int sourceRatePerSecond = 2;
GeneratorFunction<Long, String> generator = index -> "Event from index: " + index;
DataGeneratorSource<String> source = new DataGeneratorSource<>(generator, count, sourceRatePerSecond, Types.STRING);
DataStreamSource<String> watermarked =
                  env.fromSource(
                        source,
                        WatermarkStrategy.forBoundedOutOfOrderness(Duration.ofSeconds(1)),
                        "watermarked");

Scenarios, where GeneratorFunction requires initialization of non-serializable fields, is supported as follows:

GeneratorFunction<Long, String> generator =
     new GeneratorFunction<Long, String>() {

      transient SourceReaderMetricGroup sourceReaderMetricGroup;

      @Override
      public void open(SourceReaderContext readerContext) {
      	  sourceReaderMetricGroup = readerContext.metricGroup();
      }

      @Override
      public String map(Long value) {
          return "Generated: >> "

int count = 1000;
int sourceRatePerSecond = 2;
MapFunction<Long, String> generator = index -> "Event from index: " + index;
DataGeneratorSource<String> source = new DataGeneratorSource<>(generator, count, sourceRatePerSecond, Types.STRING);
DataStreamSource<String> watermarked =
                 + envvalue.fromSourcetoString()
                 + "; local metric    source,group: "
                        WatermarkStrategy.forBoundedOutOfOrderness(Duration.ofSeconds(1)),+ sourceReaderMetricGroup.hashCode();
                   }
     "watermarked");

It is up for discussion if an additional utility method of StreamExecutionEnvironment with default watermarking might also be desirable (similar to env.fromSequence(long from, long to) ).

Compatibility, Deprecation, and Migration Plan

This feature is a stepping stone toward deprecating the SourceFunction API (see this discussion). 

1. After this feature is introduced, it will be documented and promoted as the recommended way to write data generators.
2. A list of Flink tests that currently use the SourceFunction API will be compiled and follow-up tickets for migration will be created.

Test Plan

• Unit tests will be added to verify the behavior of Source's Splits in relation to the SourceReader
• Integration tests will be added to verify correct functioning with different levels of parallelism

Rejected Alternatives

It is possible to use a NumberSequenceSource followed by a map function to achieve similar results, however, this has two disadvantages:

• It introduces another level of indirection and is less intuitive to use
• It does not promote best practices of assigning watermarks (see this discussion)

POC Branch:

https://github.com/apache/flink/compare/master...afedulov:flink:FLINK-27919-generator-source

...

  };
DataGeneratorSource<String> source = new DataGeneratorSource<>(generator, count, sourceRatePerSecond, Types.STRING);

Remarks:

• It is up for discussion an addition of a utility method to StreamExecutionEnvironment with default watermarking might also be desirable (similar to env.fromSequence(long from, long to) ).
• To be able to reuse the existing functionality of NumberSequenceSource it is required to change the visibility of NumberSequenceSource.CheckpointSerializer from private to package-private. 

Compatibility, Deprecation, and Migration Plan

This feature is a stepping stone toward deprecating the SourceFunction API (see this discussion). 

1. After this feature is introduced, it will be documented and promoted as the recommended way to write data generators.
2. A list of Flink tests that currently use the SourceFunction API will be compiled and follow-up tickets for migration will be created.

Test Plan

• Unit tests will be added to verify the behavior of Source's Splits in relation to the SourceReader
• Integration tests will be added to verify correct functioning with different levels of parallelism