Hi Yungfeng,
Thank you so much for getting back!
For the first bug, here is a sample code that should reproduce it. All it does
is subtract 1 from the feedback stream until the tuples reach 0.0. For each
subtraction it outputs a relevant message in the ‘finalOutput’ stream. These
messages are stored in the keyedState of KeyedCoProcessFunction and are
populated by a dataset stream called initialStates. For each key there are
different messages associated with it, hence the need for MapState.
For the second bug, let me compare my implementation to the references you
have provided and get back to you on that.
import java.util.*;
import org.apache.flink.api.common.state.MapState;
import org.apache.flink.api.common.state.MapStateDescriptor;
import org.apache.flink.api.common.state.ValueStateDescriptor;
import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
import org.apache.flink.api.common.typeinfo.TypeHint;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.tuple.Tuple3;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.iteration.DataStreamList;
import org.apache.flink.iteration.IterationBodyResult;
import org.apache.flink.iteration.Iterations;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.co.KeyedCoProcessFunction;
import org.apache.flink.util.Collector;
import org.apache.flink.util.OutputTag;
public class Test {
public static void main(String[] args) throws Exception {
// Sets up the execution environment, which is the main entry point
StreamExecutionEnvironment env =
StreamExecutionEnvironment.createLocalEnvironment();
// sample datastreams (they are assumed to be unbounded streams outside of this
test environment)
List<Tuple2<String, Double>> feedbackinitializer = Arrays.asList(
new Tuple2<>("A", 2.0),
new Tuple2<>("B", 3.0),
new Tuple2<>("C", 1.0),
new Tuple2<>("D", 1.0)
);
List<Tuple3<String, Double, String>> initialStates = Arrays.asList(
new Tuple3<>("A", 0.0, "Final Output A"),
new Tuple3<>("A", 1.0, "Test 1A"),
new Tuple3<>("B", 2.0, "Test 2B"),
new Tuple3<>("B", 1.0, "Test 1B"),
new Tuple3<>("B", 0.0, "Final Output B"),
new Tuple3<>("C", 0.0, "No Change C"),
new Tuple3<>("D", 0.0, "Final Output D")
);
DataStream<Tuple2<String, Double>> feedbackStream =
env.fromCollection(feedbackinitializer);
DataStream<Tuple3<String, Double, String>> initialStateStream =
env.fromCollection(initialStates);
//parallelize
DataStream<Tuple2<String, Double>> feedbackParallel =
feedbackStream.keyBy(x -> x.f0)
.map(i -> Tuple2.of(i.f0,i.f1))
.returns(Types.TUPLE(Types.STRING, Types.DOUBLE));
DataStream<Tuple3<String, Double, String>> initialStateParallel =
initialStateStream.keyBy(x -> x.f0)
.map(i -> Tuple3.of(i.f0,i.f1,i.f2))
.returns(Types.TUPLE(Types.STRING, Types.DOUBLE, Types.STRING));
//iterate
DataStreamList result = Iterations.iterateUnboundedStreams(
DataStreamList.of(feedbackParallel),
DataStreamList.of(initialStateParallel),
(variableStreams, dataStreams) -> {
DataStream<Tuple2<String, Double>> modelUpdate =
variableStreams.get(0);
DataStream<Tuple3<String, Double, String>> stateStream =
dataStreams.get(0);
OutputTag<String> finalOutputTag = new
OutputTag<String>("msgs") {
};
SingleOutputStreamOperator<Tuple2<String, Double>>
newModelUpdate = stateStream.connect(modelUpdate).keyBy(0, 0).process(new
KeyedCoProcessFunction<String, Tuple3<String, Double, String>, Tuple2<String,
Double>, Tuple2<String, Double>>() {
private transient MapState<Double, String> state;
@Override
public void processElement1(Tuple3<String, Double,
String> stateUpdate, Context context, Collector<Tuple2<String, Double>>
collector) throws Exception {
state.put(stateUpdate.f1, stateUpdate.f2); //load
stateStream into mapState
}
@Override
public void processElement2(Tuple2<String, Double>
modelUpdate, Context context, Collector<Tuple2<String, Double>> collector)
throws Exception {
double weight = modelUpdate.f1;
weight = weight - 1;
//subtract 1 until 0.0
if (weight > -1.0) {
collector.collect(Tuple2.of(modelUpdate.f0,
weight));
context.output(finalOutputTag,
state.get(weight));
}
}
@Override
public void open(Configuration config) {
MapStateDescriptor<Double, String> stateDescriptor =
new MapStateDescriptor<>(
"statedescriptor", // the state name
BasicTypeInfo.DOUBLE_TYPE_INFO,
BasicTypeInfo.STRING_TYPE_INFO
);
this.state =
getRuntimeContext().getMapState(stateDescriptor);
}
});
DataStream<String> finalOutput =
newModelUpdate.getSideOutput(finalOutputTag);
return new IterationBodyResult(
DataStreamList.of(newModelUpdate),
DataStreamList.of(finalOutput));
});
result.get(0).print();
// Execute program
env.execute("Flink Java API Skeleton");
}
}
Best,
Komal
From: Yunfeng Zhou <flink.zhouyunf...@gmail.com>
Date: Sunday, April 7, 2024 11:36
To: dev@flink.apache.org <dev@flink.apache.org>
Subject: Re: Two potential bugs in Flink ML
Hi Komal,
For the first question, could you please provide a simple program that
could help reproduce this exception? That could help us better find
out the bugs (if any) in Flink ML.
For the second question, there have been Functions implementing the
IterationListener interface in Flink ML[1] and I just manually
verified that their onEpochWatermarkIncremented method can be invoked
in the test cases. You may check whether there is any difference
between your implementation and that in the Flink ML repo, and please
also feel free to provide a program that we can check together.
[1]
https://github.com/apache/flink-ml/blob/master/flink-ml-core/src/main/java/org/apache/flink/ml/common/iteration/ForwardInputsOfLastRound.java#L45
Best,
Yunfeng
On Fri, Apr 5, 2024 at 2:01 PM Komal M <komal.mar...@gmail.com> wrote:
>
> Hi Flink Dev Team,
> I have two possible bugs to report for Flink ML Iteration.
> Flink v1.17.2
> Flink ML v2.3.0
> Java 11
>
> Bug # 1
> Implementing a UDF KeyedRichCoProcessFunction or CoFlatMapFunction inside
> IterationBody yields a “java.lang.ClassCastException:
> org.apache.flink.iteration.IterationRecord cannot be cast to class
> org.apache.flink.api.java.tuple.Tuple” error. For reference, I do not get any
> error when applying .keyBy().flatMap()on the streams individually inside the
> iteration body.
>
> Exception in thread "main"
> org.apache.flink.runtime.client.JobExecutionException: Job execution failed.
> at
> org.apache.flink.runtime.jobmaster.JobResult.toJobExecutionResult(JobResult.java:144)
> ….
> at
> java.base/java.util.concurrent.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:183)
> Caused by: org.apache.flink.runtime.JobException: Recovery is suppressed by
> NoRestartBackoffTimeStrategy
> at
> org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.handleFailure(ExecutionFailureHandler.java:139)
> …
> at akka.dispatch.Mailbox.exec(Mailbox.scala:243)
> ... 5 more
> Caused by: java.lang.ClassCastException: class
> org.apache.flink.iteration.IterationRecord cannot be cast to class
> org.apache.flink.api.java.tuple.Tuple
> (org.apache.flink.iteration.IterationRecord and
> org.apache.flink.api.java.tuple.Tuple are in unnamed module of loader 'app')
> at
> org.apache.flink.api.java.typeutils.runtime.TupleComparator.extractKeys(TupleComparator.java:148)
> at
> org.apache.flink.streaming.util.keys.KeySelectorUtil$ComparableKeySelector.getKey(KeySelectorUtil.java:195)
> at
> org.apache.flink.streaming.util.keys.KeySelectorUtil$ComparableKeySelector.getKey(KeySelectorUtil.java:168)
> at
> org.apache.flink.streaming.api.operators.AbstractStreamOperator.setKeyContextElement(AbstractStreamOperator.java:502)
> at
> org.apache.flink.streaming.api.operators.AbstractStreamOperator.setKeyContextElement1(AbstractStreamOperator.java:478)
> at
> org.apache.flink.iteration.operator.allround.AbstractAllRoundWrapperOperator.setKeyContextElement1(AbstractAllRoundWrapperOperator.java:203)
> at
> org.apache.flink.streaming.runtime.io.RecordProcessorUtils.lambda$getRecordProcessor1$1(RecordProcessorUtils.java:87)
> at
> org.apache.flink.streaming.runtime.io.StreamTwoInputProcessorFactory$StreamTaskNetworkOutput.emitRecord(StreamTwoInputProcessorFactory.java:254)
> at
> org.apache.flink.streaming.runtime.io.AbstractStreamTaskNetworkInput.processElement(AbstractStreamTaskNetworkInput.java:146)
> at
> org.apache.flink.streaming.runtime.io.AbstractStreamTaskNetworkInput.emitNext(AbstractStreamTaskNetworkInput.java:110)
> at
> org.apache.flink.streaming.runtime.io.StreamOneInputProcessor.processInput(StreamOneInputProcessor.java:65)
> at
> org.apache.flink.streaming.runtime.io.StreamMultipleInputProcessor.processInput(StreamMultipleInputProcessor.java:85)
> at
> org.apache.flink.streaming.runtime.tasks.StreamTask.processInput(StreamTask.java:550)
> at
> org.apache.flink.streaming.runtime.tasks.mailbox.MailboxProcessor.runMailboxLoop(MailboxProcessor.java:231)
> at
> org.apache.flink.streaming.runtime.tasks.StreamTask.runMailboxLoop(StreamTask.java:839)
> at
> org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:788)
> at
> org.apache.flink.runtime.taskmanager.Task.runWithSystemExitMonitoring(Task.java:952)
> at
> org.apache.flink.runtime.taskmanager.Task.restoreAndInvoke(Task.java:931)
> at
> org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:745)
> at
> org.apache.flink.runtime.taskmanager.Task.run(Task.java:562)
> at java.base/java.lang.Thread.run(Thread.java:829)
>
>
>
> Potential Bug # 2
>
> The onEpochWatermarkIncremented method is never invoked when the
> IterationListener<T> interface is implemented by a UDF inside the
> iterationBody.
>
>
>
> // method is invoked from within IterationBody
>
> public class ComputeML2 extends KeyedProcessFunction<String, Tuple2<Integer,
> String>, Tuple2<Integer, String>> implements
> IterationListener<Tuple2<Integer, String>> {
>
> // this method is never invoked, getting no output
>
> @Override
>
> public void onEpochWatermarkIncremented(int epochWaterMark,
> IterationListener.Context context, Collector<Tuple2<Integer, String>>
> collector) throws Exception {
>
> collector.collect(Tuple2.of(epochWaterMark,"epoch")); //Bug: no
> output
>
> }
>
>
>
>
> @Override
>
> public void onIterationTerminated(IterationListener.Context context,
> Collector<Tuple2<Integer, String>> collector) throws Exception {
>
> }
>
>
> @Override
>
> public void processElement(Tuple2<Integer, String> integerStringTuple2,
> KeyedProcessFunction<String, Tuple2<Integer, String>, Tuple2<Integer,
> String>>.Context context, Collector<Tuple2<Integer, String>> collector)
> throws Exception {
>
> // some processing here
>
> }
>
>
> }
>
>
>
>
> Let me know if I should submit these issues on JIRA.
> Thank you so much
> Komal
>
