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[Flink] spotless
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@jto
jto committed Oct 17, 2024
1 parent a7b9023 commit ae0f3b4
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180 changes: 95 additions & 85 deletions ...nk/src/main/java/org/apache/beam/runners/flink/FlinkStreamingAggregationsTranslators.java
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Expand Up @@ -17,6 +17,11 @@
*/
package org.apache.beam.runners.flink;

import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import org.apache.beam.runners.core.KeyedWorkItem;
import org.apache.beam.runners.core.SystemReduceFn;
import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
Expand Down Expand Up @@ -58,14 +63,9 @@
import org.apache.flink.streaming.api.transformations.TwoInputTransformation;
import org.apache.flink.util.Collector;

import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

public class FlinkStreamingAggregationsTranslators {
public static class ConcatenateAsIterable<T> extends Combine.CombineFn<T, Iterable<T>, Iterable<T>> {
public static class ConcatenateAsIterable<T>
extends Combine.CombineFn<T, Iterable<T>, Iterable<T>> {
@Override
public Iterable<T> createAccumulator() {
return new ArrayList<>();
Expand Down Expand Up @@ -214,8 +214,7 @@ WindowDoFnOperator<K, InputAccumT, OutputAccumT> getWindowedAggregateDoFnOperato
WindowedValue.getFullCoder(workItemCoder, windowingStrategy.getWindowFn().windowCoder());

// Key selector
WorkItemKeySelector<K, InputAccumT> workItemKeySelector =
new WorkItemKeySelector<>(keyCoder);
WorkItemKeySelector<K, InputAccumT> workItemKeySelector = new WorkItemKeySelector<>(keyCoder);

return new WindowDoFnOperator<>(
reduceFn,
Expand Down Expand Up @@ -257,29 +256,30 @@ WindowDoFnOperator<K, InputAccumT, OutputAccumT> getWindowedAggregateDoFnOperato
}

private static class FlattenIterable<K, InputT>
implements FlatMapFunction<WindowedValue<KV<K, Iterable<Iterable<InputT>>>>, WindowedValue<KV<K, Iterable<InputT>>>> {
implements FlatMapFunction<
WindowedValue<KV<K, Iterable<Iterable<InputT>>>>,
WindowedValue<KV<K, Iterable<InputT>>>> {
@Override
public void flatMap(
WindowedValue<KV<K, Iterable<Iterable<InputT>>>> w,
Collector<WindowedValue<KV<K, Iterable<InputT>>>> collector) throws Exception {
WindowedValue<KV<K, Iterable<InputT>>> flattened = w.withValue(
KV.of(
w.getValue().getKey(),
Iterables.concat(w.getValue().getValue())));
Collector<WindowedValue<KV<K, Iterable<InputT>>>> collector)
throws Exception {
WindowedValue<KV<K, Iterable<InputT>>> flattened =
w.withValue(KV.of(w.getValue().getKey(), Iterables.concat(w.getValue().getValue())));
collector.collect(flattened);
}
}

public static <K, InputT, AccumT, OutputT>
SingleOutputStreamOperator<WindowedValue<KV<K, OutputT>>> getBatchCombinePerKeyOperator(
FlinkStreamingTranslationContext context,
PCollection<KV<K, InputT>> input,
Map<Integer, PCollectionView<?>> sideInputTagMapping,
List<PCollectionView<?>> sideInputs,
Coder<WindowedValue<KV<K, AccumT>>> windowedAccumCoder,
CombineFnBase.GlobalCombineFn<InputT, AccumT, ?> combineFn,
WindowDoFnOperator<K, AccumT, OutputT> finalDoFnOperator,
TypeInformation<WindowedValue<KV<K, OutputT>>> outputTypeInfo){
SingleOutputStreamOperator<WindowedValue<KV<K, OutputT>>> getBatchCombinePerKeyOperator(
FlinkStreamingTranslationContext context,
PCollection<KV<K, InputT>> input,
Map<Integer, PCollectionView<?>> sideInputTagMapping,
List<PCollectionView<?>> sideInputs,
Coder<WindowedValue<KV<K, AccumT>>> windowedAccumCoder,
CombineFnBase.GlobalCombineFn<InputT, AccumT, ?> combineFn,
WindowDoFnOperator<K, AccumT, OutputT> finalDoFnOperator,
TypeInformation<WindowedValue<KV<K, OutputT>>> outputTypeInfo) {

String fullName = FlinkStreamingTransformTranslators.getCurrentTransformName(context);
DataStream<WindowedValue<KV<K, InputT>>> inputDataStream = context.getInputDataStream(input);
Expand Down Expand Up @@ -314,50 +314,55 @@ SingleOutputStreamOperator<WindowedValue<KV<K, OutputT>>> getBatchCombinePerKeyO
if (sideInputs.isEmpty()) {
return inputDataStream
.transform(partialName, partialTypeInfo, partialDoFnOperator)
.uid(partialName).name(partialName)
.uid(partialName)
.name(partialName)
.keyBy(accumKeySelector)
.transform(fullName, outputTypeInfo, finalDoFnOperator)
.uid(fullName).name(fullName);
.uid(fullName)
.name(fullName);
} else {

Tuple2<Map<Integer, PCollectionView<?>>, DataStream<RawUnionValue>> transformSideInputs =
FlinkStreamingTransformTranslators.transformSideInputs(sideInputs, context);

TwoInputTransformation<
WindowedValue<KV<K, InputT>>, RawUnionValue, WindowedValue<KV<K, AccumT>>> rawPartialFlinkTransform =
new TwoInputTransformation<>(
inputDataStream.getTransformation(),
transformSideInputs.f1.broadcast().getTransformation(),
partialName,
partialDoFnOperator,
partialTypeInfo,
inputDataStream.getParallelism());
WindowedValue<KV<K, InputT>>, RawUnionValue, WindowedValue<KV<K, AccumT>>>
rawPartialFlinkTransform =
new TwoInputTransformation<>(
inputDataStream.getTransformation(),
transformSideInputs.f1.broadcast().getTransformation(),
partialName,
partialDoFnOperator,
partialTypeInfo,
inputDataStream.getParallelism());

SingleOutputStreamOperator<WindowedValue<KV<K, AccumT>>> partialyCombinedStream =
new SingleOutputStreamOperator<WindowedValue<KV<K, AccumT>>>(
inputDataStream.getExecutionEnvironment(),
rawPartialFlinkTransform) {}; // we have to cheat around the ctor being protected

inputDataStream.getExecutionEnvironment().addOperator(rawPartialFlinkTransform);
inputDataStream.getExecutionEnvironment().addOperator(rawPartialFlinkTransform);

return buildTwoInputStream(
partialyCombinedStream.keyBy(accumKeySelector),
transformSideInputs.f1,
fullName,
finalDoFnOperator,
outputTypeInfo);
return buildTwoInputStream(
partialyCombinedStream.keyBy(accumKeySelector),
transformSideInputs.f1,
fullName,
finalDoFnOperator,
outputTypeInfo);
}
}

/**
* Creates a two-steps GBK operation. Elements are first aggregated locally to save on serialized size since in batch
* it's very likely that all the elements will be within the same window and pane.
* The only difference with batchCombinePerKey is the nature of the SystemReduceFn used. It uses SystemReduceFn.buffering()
* instead of SystemReduceFn.combining() so that new element can simply be appended without accessing the existing state.
* Creates a two-steps GBK operation. Elements are first aggregated locally to save on serialized
* size since in batch it's very likely that all the elements will be within the same window and
* pane. The only difference with batchCombinePerKey is the nature of the SystemReduceFn used. It
* uses SystemReduceFn.buffering() instead of SystemReduceFn.combining() so that new element can
* simply be appended without accessing the existing state.
*/
public static <K, InputT> SingleOutputStreamOperator<WindowedValue<KV<K, Iterable<InputT>>>> batchGroupByKey(
FlinkStreamingTranslationContext context,
PTransform<PCollection<KV<K, InputT>>, PCollection<KV<K, Iterable<InputT>>>> transform) {
public static <K, InputT>
SingleOutputStreamOperator<WindowedValue<KV<K, Iterable<InputT>>>> batchGroupByKey(
FlinkStreamingTranslationContext context,
PTransform<PCollection<KV<K, InputT>>, PCollection<KV<K, Iterable<InputT>>>> transform) {

Map<Integer, PCollectionView<?>> sideInputTagMapping = new HashMap<>();
List<PCollectionView<?>> sideInputs = Collections.emptyList();
Expand All @@ -372,58 +377,64 @@ public static <K, InputT> SingleOutputStreamOperator<WindowedValue<KV<K, Iterabl
context.getTypeInfo(context.getOutput(transform));

Coder<Iterable<InputT>> accumulatorCoder = IterableCoder.of(inputKvCoder.getValueCoder());
KvCoder<K, Iterable<InputT>> accumKvCoder = KvCoder.of(inputKvCoder.getKeyCoder(), accumulatorCoder);
KvCoder<K, Iterable<InputT>> accumKvCoder =
KvCoder.of(inputKvCoder.getKeyCoder(), accumulatorCoder);

Coder<WindowedValue<KV<K, Iterable<InputT>>>> windowedAccumCoder =
WindowedValue.getFullCoder(
accumKvCoder, input.getWindowingStrategy().getWindowFn().windowCoder());

Coder<WindowedValue<KV<K, Iterable<Iterable<InputT>>>>> outputCoder =
WindowedValue.getFullCoder(
KvCoder.of(inputKvCoder.getKeyCoder(), IterableCoder.of(accumulatorCoder)) , input.getWindowingStrategy().getWindowFn().windowCoder());
KvCoder.of(inputKvCoder.getKeyCoder(), IterableCoder.of(accumulatorCoder)),
input.getWindowingStrategy().getWindowFn().windowCoder());

TypeInformation<WindowedValue<KV<K, Iterable<Iterable<InputT>>>>> accumulatedTypeInfo =
new CoderTypeInformation<>(
WindowedValue.getFullCoder(
KvCoder.of(inputKvCoder.getKeyCoder(), IterableCoder.of(IterableCoder.of(inputKvCoder.getValueCoder()))), input.getWindowingStrategy().getWindowFn().windowCoder()),
WindowedValue.getFullCoder(
KvCoder.of(
inputKvCoder.getKeyCoder(),
IterableCoder.of(IterableCoder.of(inputKvCoder.getValueCoder()))),
input.getWindowingStrategy().getWindowFn().windowCoder()),
serializablePipelineOptions);

// final aggregation
WindowDoFnOperator<K, Iterable<InputT>, Iterable<Iterable<InputT>>> finalDoFnOperator =
getWindowedAccumulateDoFnOperator(
context,
transform,
accumKvCoder,
outputCoder,
sideInputTagMapping,
sideInputs);

return
getBatchCombinePerKeyOperator(
context,
input,
sideInputTagMapping,
sideInputs,
windowedAccumCoder,
new ConcatenateAsIterable<>(),
finalDoFnOperator,
accumulatedTypeInfo
)
.flatMap(new FlattenIterable<>(), outputTypeInfo)
.name("concatenate");
getWindowedAccumulateDoFnOperator(
context, transform, accumKvCoder, outputCoder, sideInputTagMapping, sideInputs);

return getBatchCombinePerKeyOperator(
context,
input,
sideInputTagMapping,
sideInputs,
windowedAccumCoder,
new ConcatenateAsIterable<>(),
finalDoFnOperator,
accumulatedTypeInfo)
.flatMap(new FlattenIterable<>(), outputTypeInfo)
.name("concatenate");
}

private static <InputT, K> WindowDoFnOperator<K, Iterable<InputT>, Iterable<Iterable<InputT>>> getWindowedAccumulateDoFnOperator(
FlinkStreamingTranslationContext context,
PTransform<PCollection<KV<K,InputT>>, PCollection<KV<K, Iterable<InputT>>>> transform,
KvCoder<K, Iterable<InputT>> accumKvCoder,
Coder<WindowedValue<KV<K, Iterable<Iterable<InputT>>>>> outputCoder,
Map<Integer, PCollectionView<?>> sideInputTagMapping,
List<PCollectionView<?>> sideInputs) {
private static <InputT, K>
WindowDoFnOperator<K, Iterable<InputT>, Iterable<Iterable<InputT>>>
getWindowedAccumulateDoFnOperator(
FlinkStreamingTranslationContext context,
PTransform<PCollection<KV<K, InputT>>, PCollection<KV<K, Iterable<InputT>>>>
transform,
KvCoder<K, Iterable<InputT>> accumKvCoder,
Coder<WindowedValue<KV<K, Iterable<Iterable<InputT>>>>> outputCoder,
Map<Integer, PCollectionView<?>> sideInputTagMapping,
List<PCollectionView<?>> sideInputs) {

// Combining fn
SystemReduceFn<K, Iterable<InputT>, Iterable<Iterable<InputT>>, Iterable<Iterable<InputT>>, BoundedWindow> reduceFn =
SystemReduceFn.buffering(accumKvCoder.getValueCoder());
// Combining fn
SystemReduceFn<
K,
Iterable<InputT>,
Iterable<Iterable<InputT>>,
Iterable<Iterable<InputT>>,
BoundedWindow>
reduceFn = SystemReduceFn.buffering(accumKvCoder.getValueCoder());

return getWindowedAggregateDoFnOperator(
context, transform, accumKvCoder, outputCoder, reduceFn, sideInputTagMapping, sideInputs);
Expand Down Expand Up @@ -482,8 +493,7 @@ SingleOutputStreamOperator<WindowedValue<KV<K, OutputT>>> batchCombinePerKey(
windowedAccumCoder,
combineFn,
finalDoFnOperator,
outputTypeInfo
);
outputTypeInfo);
}

@SuppressWarnings({
Expand Down
1 change: 0 additions & 1 deletion ...s/flink/src/main/java/org/apache/beam/runners/flink/FlinkStreamingPipelineTranslator.java
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,6 @@
import java.util.Objects;
import java.util.concurrent.ThreadLocalRandom;
import java.util.concurrent.TimeUnit;

import org.apache.beam.runners.flink.adapter.FlinkKey;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.coders.Coder;
Expand Down
9 changes: 3 additions & 6 deletions ...src/main/java/org/apache/beam/runners/flink/FlinkStreamingPortablePipelineTranslator.java
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Original file line number Diff line number Diff line change
Expand Up @@ -434,8 +434,7 @@ private <K, V> SingleOutputStreamOperator<WindowedValue<KV<K, Iterable<V>>>> add
new WorkItemKeySelector<>(inputElementCoder.getKeyCoder());

KeyedStream<WindowedValue<KV<K, V>>, FlinkKey> keyedWorkItemStream =
inputDataStream.keyBy(
new KvToFlinkKeyKeySelector(inputElementCoder.getKeyCoder()));
inputDataStream.keyBy(new KvToFlinkKeyKeySelector(inputElementCoder.getKeyCoder()));

SystemReduceFn<K, V, Iterable<V>, Iterable<V>, BoundedWindow> reduceFn =
SystemReduceFn.buffering(inputElementCoder.getValueCoder());
Expand Down Expand Up @@ -829,8 +828,7 @@ private <InputT, OutputT> void translateExecutableStage(
}
if (stateful) {
keyCoder = ((KvCoder) valueCoder).getKeyCoder();
keySelector =
new KvToFlinkKeyKeySelector(keyCoder);
keySelector = new KvToFlinkKeyKeySelector(keyCoder);
} else {
// For an SDF, we know that the input element should be
// KV<KV<element, KV<restriction, watermarkState>>, size>. We are going to use the element
Expand All @@ -844,8 +842,7 @@ private <InputT, OutputT> void translateExecutableStage(
valueCoder.getClass().getSimpleName()));
}
keyCoder = ((KvCoder) ((KvCoder) valueCoder).getKeyCoder()).getKeyCoder();
keySelector =
new SdfFlinkKeyKeySelector(keyCoder);
keySelector = new SdfFlinkKeyKeySelector(keyCoder);
}
inputDataStream = inputDataStream.keyBy(keySelector);
}
Expand Down
18 changes: 5 additions & 13 deletions ...flink/src/main/java/org/apache/beam/runners/flink/FlinkStreamingTransformTranslators.java
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Original file line number Diff line number Diff line change
Expand Up @@ -105,7 +105,6 @@
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.functions.KeySelector;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.api.java.typeutils.GenericTypeInfo;
import org.apache.flink.api.java.typeutils.ResultTypeQueryable;
import org.apache.flink.api.java.typeutils.ValueTypeInfo;
import org.apache.flink.configuration.Configuration;
Expand Down Expand Up @@ -591,8 +590,7 @@ static <InputT, OutputT> void translateParDo(
// Based on the fact that the signature is stateful, DoFnSignatures ensures
// that it is also keyed
keyCoder = ((KvCoder) input.getCoder()).getKeyCoder();
keySelector =
new KvToFlinkKeyKeySelector<>(keyCoder);
keySelector = new KvToFlinkKeyKeySelector<>(keyCoder);
final PTransform<?, PCollection<InputT>> producer = context.getProducer(input);
final String previousUrn =
producer != null
Expand All @@ -609,8 +607,7 @@ static <InputT, OutputT> void translateParDo(
} else if (doFn instanceof SplittableParDoViaKeyedWorkItems.ProcessFn) {
// we know that it is keyed on byte[]
keyCoder = ByteArrayCoder.of();
keySelector =
new WorkItemKeySelector<>(keyCoder);
keySelector = new WorkItemKeySelector<>(keyCoder);
stateful = true;
}

Expand Down Expand Up @@ -962,10 +959,7 @@ public void translateNode(
SingleOutputStreamOperator<WindowedValue<KV<K, Iterable<InputT>>>> outDataStream;
// Pre-aggregate before shuffle similar to group combine
if (!context.isStreaming()) {
outDataStream =
FlinkStreamingAggregationsTranslators.batchGroupByKey(
context,
transform);
outDataStream = FlinkStreamingAggregationsTranslators.batchGroupByKey(context, transform);
} else {
// No pre-aggregation in Streaming mode.
KvToFlinkKeyKeySelector<K, InputT> keySelector =
Expand Down Expand Up @@ -1046,8 +1040,7 @@ public void translateNode(
List<PCollectionView<?>> sideInputs = ((Combine.PerKey) transform).getSideInputs();

KeyedStream<WindowedValue<KV<K, InputT>>, FlinkKey> keyedStream =
inputDataStream.keyBy(
new KvToFlinkKeyKeySelector<>(keyCoder));
inputDataStream.keyBy(new KvToFlinkKeyKeySelector<>(keyCoder));

if (sideInputs.isEmpty()) {
SingleOutputStreamOperator<WindowedValue<KV<K, OutputT>>> outDataStream;
Expand Down Expand Up @@ -1147,8 +1140,7 @@ public void translateNode(
.name("ToKeyedWorkItem");

KeyedStream<WindowedValue<KeyedWorkItem<K, InputT>>, FlinkKey> keyedWorkItemStream =
workItemStream.keyBy(
new WorkItemKeySelector<>(inputKvCoder.getKeyCoder()));
workItemStream.keyBy(new WorkItemKeySelector<>(inputKvCoder.getKeyCoder()));

context.setOutputDataStream(context.getOutput(transform), keyedWorkItemStream);
}
Expand Down
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