[
https://issues.apache.org/jira/browse/BEAM-3972?focusedWorklogId=97734&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-97734
]
ASF GitHub Bot logged work on BEAM-3972:
----------------------------------------
Author: ASF GitHub Bot
Created on: 03/May/18 00:19
Start Date: 03/May/18 00:19
Worklog Time Spent: 10m
Work Description: bsidhom commented on a change in pull request #5226:
[BEAM-3972] Translate portable batch pipelines by proto
URL: https://github.com/apache/beam/pull/5226#discussion_r185671288
##########
File path:
runners/flink/src/main/java/org/apache/beam/runners/flink/FlinkBatchPortablePipelineTranslator.java
##########
@@ -0,0 +1,601 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.beam.runners.flink;
+
+import static com.google.common.base.Preconditions.checkArgument;
+
+import com.google.common.collect.BiMap;
+import com.google.common.collect.ImmutableBiMap;
+import com.google.common.collect.ImmutableMap;
+import com.google.common.collect.Iterables;
+import com.google.common.collect.Lists;
+import com.google.common.collect.Maps;
+import com.google.protobuf.InvalidProtocolBufferException;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.stream.Collectors;
+import org.apache.beam.model.pipeline.v1.RunnerApi;
+import
org.apache.beam.model.pipeline.v1.RunnerApi.ExecutableStagePayload.SideInputId;
+import org.apache.beam.runners.core.construction.CoderTranslation;
+import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.PipelineOptionsTranslation;
+import org.apache.beam.runners.core.construction.RehydratedComponents;
+import org.apache.beam.runners.core.construction.WindowingStrategyTranslation;
+import org.apache.beam.runners.core.construction.graph.ExecutableStage;
+import org.apache.beam.runners.core.construction.graph.PipelineNode;
+import
org.apache.beam.runners.core.construction.graph.PipelineNode.PCollectionNode;
+import org.apache.beam.runners.core.construction.graph.QueryablePipeline;
+import org.apache.beam.runners.flink.translation.functions.FlinkAssignWindows;
+import
org.apache.beam.runners.flink.translation.functions.FlinkExecutableStageFunction;
+import
org.apache.beam.runners.flink.translation.functions.FlinkExecutableStagePruningFunction;
+import
org.apache.beam.runners.flink.translation.functions.FlinkPartialReduceFunction;
+import org.apache.beam.runners.flink.translation.functions.FlinkReduceFunction;
+import org.apache.beam.runners.flink.translation.types.CoderTypeInformation;
+import org.apache.beam.runners.flink.translation.types.KvKeySelector;
+import org.apache.beam.runners.flink.translation.wrappers.ImpulseInputFormat;
+import org.apache.beam.runners.fnexecution.wire.WireCoders;
+import org.apache.beam.sdk.coders.ByteArrayCoder;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.CoderRegistry;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.coders.ListCoder;
+import org.apache.beam.sdk.coders.VoidCoder;
+import org.apache.beam.sdk.transforms.Combine;
+import org.apache.beam.sdk.transforms.GroupByKey;
+import org.apache.beam.sdk.transforms.join.RawUnionValue;
+import org.apache.beam.sdk.transforms.join.UnionCoder;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.GlobalWindow;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.util.WindowedValue.WindowedValueCoder;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.PCollection;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.java.DataSet;
+import org.apache.flink.api.java.ExecutionEnvironment;
+import org.apache.flink.api.java.io.DiscardingOutputFormat;
+import org.apache.flink.api.java.operators.DataSource;
+import org.apache.flink.api.java.operators.FlatMapOperator;
+import org.apache.flink.api.java.operators.GroupCombineOperator;
+import org.apache.flink.api.java.operators.GroupReduceOperator;
+import org.apache.flink.api.java.operators.Grouping;
+import org.apache.flink.api.java.operators.MapPartitionOperator;
+
+/**
+ * A translator that translates bounded portable pipelines into executable
Flink pipelines.
+ *
+ * <p>Example usage:
+ *
+ * <pre>
+ * FlinkBatchPortablePipelineTranslator translator =
+ * FlinkBatchPortablePipelineTranslator.createTranslator();
+ * BatchTranslationContext context =
+ *
FlinkBatchPortablePipelineTranslator.createTranslationContext(options);
+ * translator.translate(context, pipeline);
+ * ExecutionEnvironment executionEnvironment =
context.getExecutionEnvironment();
+ * // Do something with executionEnvironment...
+ * </pre>
+ *
+ * <p>After translation the {@link ExecutionEnvironment} in the translation
context will contain the
+ * full not-yet-executed pipeline DAG corresponding to the input pipeline.
+ */
+public class FlinkBatchPortablePipelineTranslator
+ implements FlinkPortablePipelineTranslator<
+ FlinkBatchPortablePipelineTranslator.BatchTranslationContext> {
+
+ /**
+ * Creates a batch translation context. The resulting Flink execution dag
will live in a new
+ * {@link ExecutionEnvironment}.
+ */
+ public static BatchTranslationContext
createTranslationContext(FlinkPipelineOptions options) {
+ ExecutionEnvironment executionEnvironment =
+ FlinkExecutionEnvironments.createBatchExecutionEnvironment(options);
+ return new BatchTranslationContext(options, executionEnvironment);
+ }
+
+ /** Creates a batch translator. */
+ public static FlinkBatchPortablePipelineTranslator createTranslator() {
+ ImmutableMap.Builder<String,
PTransformTranslator<BatchTranslationContext>> translatorMap =
+ ImmutableMap.builder();
+ translatorMap.put(
+ PTransformTranslation.FLATTEN_TRANSFORM_URN,
+ FlinkBatchPortablePipelineTranslator::translateFlatten);
+ translatorMap.put(
+ PTransformTranslation.GROUP_BY_KEY_TRANSFORM_URN,
+ FlinkBatchPortablePipelineTranslator::translateGroupByKey);
+ translatorMap.put(
+ PTransformTranslation.IMPULSE_TRANSFORM_URN,
+ FlinkBatchPortablePipelineTranslator::translateImpulse);
+ translatorMap.put(
+ PTransformTranslation.ASSIGN_WINDOWS_TRANSFORM_URN,
+ FlinkBatchPortablePipelineTranslator::translateAssignWindows);
+ translatorMap.put(
+ ExecutableStage.URN,
FlinkBatchPortablePipelineTranslator::translateExecutableStage);
+ translatorMap.put(
+ PTransformTranslation.RESHUFFLE_URN,
+ FlinkBatchPortablePipelineTranslator::translateReshuffle);
+ translatorMap.put(
+ PTransformTranslation.CREATE_VIEW_TRANSFORM_URN,
+ FlinkBatchPortablePipelineTranslator::translateView);
+ return new FlinkBatchPortablePipelineTranslator(translatorMap.build());
+ }
+
+ /**
+ * Batch translation context. Stores metadata about known
PCollections/DataSets and holds the
+ * flink {@link ExecutionEnvironment} that the execution plan will be
applied to.
+ */
+ public static class BatchTranslationContext
+ implements FlinkPortablePipelineTranslator.TranslationContext {
+
+ private final FlinkPipelineOptions options;
+ private final ExecutionEnvironment executionEnvironment;
+ private final Map<String, DataSet<?>> dataSets;
+ private final Set<String> danglingDataSets;
+
+ private BatchTranslationContext(
+ FlinkPipelineOptions options, ExecutionEnvironment
executionEnvironment) {
+ this.options = options;
+ this.executionEnvironment = executionEnvironment;
+ dataSets = new HashMap<>();
+ danglingDataSets = new HashSet<>();
+ }
+
+ @Override
+ public FlinkPipelineOptions getPipelineOptions() {
+ return options;
+ }
+
+ public ExecutionEnvironment getExecutionEnvironment() {
+ return executionEnvironment;
+ }
+
+ public <T> void addDataSet(String pCollectionId, DataSet<T> dataSet) {
+ checkArgument(!dataSets.containsKey(pCollectionId));
+ dataSets.put(pCollectionId, dataSet);
+ danglingDataSets.add(pCollectionId);
+ }
+
+ public <T> DataSet<T> getDataSetOrThrow(String pCollectionId) {
+ DataSet<T> dataSet = (DataSet<T>) dataSets.get(pCollectionId);
+ if (dataSet == null) {
+ throw new IllegalArgumentException(
+ String.format("Unknown dataset for id %s.", pCollectionId));
+ }
+
+ // Assume that the DataSet is consumed if requested. We use this as a
proxy for consumption
+ // because Flink does not expose its internal execution plan.
+ danglingDataSets.remove(pCollectionId);
+ return dataSet;
+ }
+
+ public Collection<DataSet<?>> getDanglingDataSets() {
+ return danglingDataSets.stream().map(id ->
dataSets.get(id)).collect(Collectors.toList());
+ }
+ }
+
+ private interface PTransformTranslator<T> {
+ void translate(String id, RunnerApi.Pipeline pipeline, T t);
+ }
+
+ private final Map<String, PTransformTranslator<BatchTranslationContext>>
urnToTransformTranslator;
+
+ private FlinkBatchPortablePipelineTranslator(
+ Map<String, PTransformTranslator<BatchTranslationContext>>
urnToTransformTranslator) {
+ this.urnToTransformTranslator = urnToTransformTranslator;
+ }
+
+ @Override
+ public void translate(BatchTranslationContext context, RunnerApi.Pipeline
pipeline) {
+ // Use a QueryablePipeline to traverse transforms topologically.
+ QueryablePipeline p =
+ QueryablePipeline.forTransforms(
+ pipeline.getRootTransformIdsList(), pipeline.getComponents());
+ for (PipelineNode.PTransformNode transform :
p.getTopologicallyOrderedTransforms()) {
+ urnToTransformTranslator
+ .getOrDefault(
+ transform.getTransform().getSpec().getUrn(),
+ FlinkBatchPortablePipelineTranslator::urnNotFound)
+ .translate(transform.getId(), pipeline, context);
+ }
+
+ // Ensure that side effects are performed for unconsumed DataSets.
+ for (DataSet<?> dataSet : context.getDanglingDataSets()) {
+ dataSet.output(new DiscardingOutputFormat<>());
+ }
+ }
+
+ private static <InputT> void translateView(
+ String id, RunnerApi.Pipeline pipeline, BatchTranslationContext context)
{
+ RunnerApi.PTransform transform =
pipeline.getComponents().getTransformsOrThrow(id);
+
+ DataSet<WindowedValue<InputT>> inputDataSet =
+
context.getDataSetOrThrow(Iterables.getOnlyElement(transform.getInputsMap().values()));
+
+
context.addDataSet(Iterables.getOnlyElement(transform.getOutputsMap().values()),
inputDataSet);
+ }
+
+ private static <K, V> void translateReshuffle(
+ String id, RunnerApi.Pipeline pipeline, BatchTranslationContext context)
{
+ RunnerApi.PTransform transform =
pipeline.getComponents().getTransformsOrThrow(id);
+ DataSet<WindowedValue<KV<K, V>>> inputDataSet =
+
context.getDataSetOrThrow(Iterables.getOnlyElement(transform.getInputsMap().values()));
+ context.addDataSet(
+ Iterables.getOnlyElement(transform.getOutputsMap().values()),
inputDataSet.rebalance());
+ }
+
+ private static <T> void translateAssignWindows(
+ String id, RunnerApi.Pipeline pipeline, BatchTranslationContext context)
{
+ RunnerApi.Components components = pipeline.getComponents();
+ RunnerApi.PTransform transform = components.getTransformsOrThrow(id);
+ RunnerApi.WindowIntoPayload payload;
+ try {
+ payload =
RunnerApi.WindowIntoPayload.parseFrom(transform.getSpec().getPayload());
+ } catch (InvalidProtocolBufferException e) {
+ throw new IllegalArgumentException(e);
+ }
+ WindowFn<T, ? extends BoundedWindow> windowFn =
+ (WindowFn<T, ? extends BoundedWindow>)
+
WindowingStrategyTranslation.windowFnFromProto(payload.getWindowFn());
+
+ String inputCollectionId =
Iterables.getOnlyElement(transform.getInputsMap().values());
+ String outputCollectionId =
Iterables.getOnlyElement(transform.getOutputsMap().values());
+ Coder<WindowedValue<T>> outputCoder = instantiateCoder(outputCollectionId,
components);
+ TypeInformation<WindowedValue<T>> resultTypeInfo = new
CoderTypeInformation<>(outputCoder);
+
+ DataSet<WindowedValue<T>> inputDataSet =
context.getDataSetOrThrow(inputCollectionId);
+
+ FlinkAssignWindows<T, ? extends BoundedWindow> assignWindowsFunction =
+ new FlinkAssignWindows<>(windowFn);
+
+ DataSet<WindowedValue<T>> resultDataSet =
+ inputDataSet
+ .flatMap(assignWindowsFunction)
+ .name(transform.getUniqueName())
+ .returns(resultTypeInfo);
+
+ context.addDataSet(outputCollectionId, resultDataSet);
+ }
+
+ private static <InputT> void translateExecutableStage(
+ String id, RunnerApi.Pipeline pipeline, BatchTranslationContext context)
{
+ // TODO: Fail on stateful DoFns for now.
+ // TODO: Support stateful DoFns by inserting group-by-keys where necessary.
+ // TODO: Fail on splittable DoFns.
+ // TODO: Special-case single outputs to avoid multiplexing PCollections.
+
+ RunnerApi.Components components = pipeline.getComponents();
+ RunnerApi.PTransform transform = components.getTransformsOrThrow(id);
+ Map<String, String> outputs = transform.getOutputsMap();
+ // Mapping from PCollection id to coder tag id.
+ BiMap<String, Integer> outputMap = createOutputMap(outputs.values());
+ // Collect all output Coders and create a UnionCoder for our tagged
outputs.
+ List<Coder<?>> unionCoders = Lists.newArrayList();
+ // Enforce tuple tag sorting by union tag index.
+ Map<String, Coder<WindowedValue<?>>> outputCoders = Maps.newHashMap();
+ for (String collectionId : new TreeMap<>(outputMap.inverse()).values()) {
+ Coder<WindowedValue<?>> windowCoder = (Coder)
instantiateCoder(collectionId, components);
+ outputCoders.put(collectionId, windowCoder);
+ unionCoders.add(windowCoder);
+ }
+ UnionCoder unionCoder = UnionCoder.of(unionCoders);
+ TypeInformation<RawUnionValue> typeInformation = new
CoderTypeInformation<>(unionCoder);
+
+ RunnerApi.ExecutableStagePayload stagePayload;
+ try {
+ stagePayload =
RunnerApi.ExecutableStagePayload.parseFrom(transform.getSpec().getPayload());
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ FlinkExecutableStageFunction<InputT> function =
+ new FlinkExecutableStageFunction<>(
+ stagePayload,
+ PipelineOptionsTranslation.toProto(context.getPipelineOptions()),
+ outputMap);
+
+ DataSet<WindowedValue<InputT>> inputDataSet =
+ context.getDataSetOrThrow(stagePayload.getInput());
+
+ MapPartitionOperator<WindowedValue<InputT>, RawUnionValue> taggedDataset =
+ new MapPartitionOperator<>(
+ inputDataSet, typeInformation, function,
transform.getUniqueName());
+
+ for (SideInputId sideInputId : stagePayload.getSideInputsList()) {
+ String collectionId =
+ components
+ .getTransformsOrThrow(sideInputId.getTransformId())
+ .getInputsOrThrow(sideInputId.getLocalName());
+ // Register under the global PCollection name. Only
ExecutableStageFunction needs to know the
+ // mapping from local name to global name and how to translate the
broadcast data to a state
+ // API view.
+ taggedDataset.withBroadcastSet(context.getDataSetOrThrow(collectionId),
collectionId);
+ }
+
+ for (String collectionId : outputs.values()) {
+ pruneOutput(
+ taggedDataset,
+ context,
+ outputMap.get(collectionId),
+ (Coder) outputCoders.get(collectionId),
+ transform.getUniqueName(),
+ collectionId);
+ }
+ if (outputs.isEmpty()) {
+ // NOTE: After pipeline translation, we traverse the set of unconsumed
PCollections and add a
+ // no-op sink to each to make sure they are materialized by Flink.
However, some SDK-executed
+ // stages have no runner-visible output after fusion. We handle this
case by adding a sink
+ // here.
+ taggedDataset.output(new DiscardingOutputFormat());
+ }
+ }
+
+ private static <T> void translateFlatten(
+ String id, RunnerApi.Pipeline pipeline, BatchTranslationContext context)
{
+ Map<String, String> allInputs =
+ pipeline.getComponents().getTransformsOrThrow(id).getInputsMap();
+ DataSet<WindowedValue<T>> result = null;
+
+ if (allInputs.isEmpty()) {
+
+ // Create an empty dummy source to satisfy downstream operations. We
cannot create an empty
+ // source in Flink, so we send the DataSet to a flatMap that never
forwards its element.
+ DataSource<String> dummySource =
context.getExecutionEnvironment().fromElements("dummy");
+ result =
+ dummySource
+ .<WindowedValue<T>>flatMap(
+ (s, collector) -> {
+ // never return anything
+ })
+ .returns(
+ new CoderTypeInformation<>(
+ WindowedValue.getFullCoder(
+ (Coder<T>) VoidCoder.of(),
GlobalWindow.Coder.INSTANCE)));
+ } else {
+ for (String pCollectionId : allInputs.values()) {
+ DataSet<WindowedValue<T>> current =
context.getDataSetOrThrow(pCollectionId);
+ if (result == null) {
+ result = current;
+ } else {
+ result = result.union(current);
+ }
+ }
+ }
+
+ // Insert a dummy filter. Flink produces duplicate elements after the
union in some cases if we
+ // don't do so.
+ result = result.filter(tWindowedValue -> true).name("UnionFixFilter");
+ context.addDataSet(
+ Iterables.getOnlyElement(
+
pipeline.getComponents().getTransformsOrThrow(id).getOutputsMap().values()),
+ result);
+ }
+
+ private static <K, V> void translateGroupByKey(
+ String id, RunnerApi.Pipeline pipeline, BatchTranslationContext context)
{
+ RunnerApi.PTransform pTransform =
pipeline.getComponents().getTransformsOrThrow(id);
+ String inputPCollectionId =
Iterables.getOnlyElement(pTransform.getInputsMap().values());
+ DataSet<WindowedValue<KV<K, V>>> inputDataSet =
context.getDataSetOrThrow(inputPCollectionId);
+ RunnerApi.WindowingStrategy windowingStrategyProto =
+ pipeline
+ .getComponents()
+ .getWindowingStrategiesOrThrow(
+ pipeline
+ .getComponents()
+ .getPcollectionsOrThrow(inputPCollectionId)
+ .getWindowingStrategyId());
+
+ RehydratedComponents rehydratedComponents =
+ RehydratedComponents.forComponents(pipeline.getComponents());
+
+ WindowingStrategy<Object, BoundedWindow> windowingStrategy;
+ try {
+ windowingStrategy =
+ (WindowingStrategy<Object, BoundedWindow>)
+ WindowingStrategyTranslation.fromProto(windowingStrategyProto,
rehydratedComponents);
+ } catch (InvalidProtocolBufferException e) {
+ throw new IllegalStateException(
+ String.format(
+ "Unable to hydrate GroupByKey windowing strategy %s.",
windowingStrategyProto),
+ e);
+ }
+
+ WindowedValueCoder<KV<K, V>> inputCoder =
+ instantiateCoder(inputPCollectionId, pipeline.getComponents());
+
+ KvCoder<K, V> inputElementCoder = (KvCoder<K, V>)
inputCoder.getValueCoder();
+
+ Concatenate combineFn = new Concatenate<>();
+ Coder<List<V>> accumulatorCoder =
+ combineFn.getAccumulatorCoder(
+ CoderRegistry.createDefault(), inputElementCoder.getValueCoder());
+
+ Coder<WindowedValue<KV<K, List<V>>>> outputCoder =
+ WindowedValue.getFullCoder(
+ KvCoder.of(inputElementCoder.getKeyCoder(), accumulatorCoder),
+ windowingStrategy.getWindowFn().windowCoder());
+
+ TypeInformation<WindowedValue<KV<K, List<V>>>> partialReduceTypeInfo =
+ new CoderTypeInformation<>(outputCoder);
+
+ Grouping<WindowedValue<KV<K, V>>> inputGrouping =
+ inputDataSet.groupBy(new
KvKeySelector<>(inputElementCoder.getKeyCoder()));
+
+ FlinkPartialReduceFunction<K, V, List<V>, ?> partialReduceFunction =
+ new FlinkPartialReduceFunction<>(
+ combineFn, windowingStrategy, Collections.emptyMap(),
context.getPipelineOptions());
+
+ FlinkReduceFunction<K, List<V>, List<V>, ?> reduceFunction =
+ new FlinkReduceFunction<>(
+ combineFn, windowingStrategy, Collections.emptyMap(),
context.getPipelineOptions());
+
+ // Partially GroupReduce the values into the intermediate format AccumT
(combine)
+ GroupCombineOperator<WindowedValue<KV<K, V>>, WindowedValue<KV<K,
List<V>>>> groupCombine =
+ new GroupCombineOperator<>(
+ inputGrouping,
+ partialReduceTypeInfo,
+ partialReduceFunction,
+ "GroupCombine: " + pTransform.getUniqueName());
+
+ Grouping<WindowedValue<KV<K, List<V>>>> intermediateGrouping =
+ groupCombine.groupBy(new
KvKeySelector<>(inputElementCoder.getKeyCoder()));
+
+ // Fully reduce the values and create output format VO
Review comment:
The precombine does not offer much, especially since it requires local
buffering in order to get key grouping. I'm not sure if this is the case with
Flink, but Spark does not usually see benefits from map-side grouping. On the
other hand, Spark also has explicit off-heap grouping/sorting post-shuffle,
which may make the post-combines cheaper. I'll leave this as is for now and we
can revisit it when we tackle the referenced bug.
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Issue Time Tracking
-------------------
Worklog Id: (was: 97734)
Time Spent: 8h 20m (was: 8h 10m)
> Flink runner translates batch pipelines directly by proto
> ---------------------------------------------------------
>
> Key: BEAM-3972
> URL: https://issues.apache.org/jira/browse/BEAM-3972
> Project: Beam
> Issue Type: Bug
> Components: runner-flink
> Reporter: Ben Sidhom
> Assignee: Ben Sidhom
> Priority: Major
> Time Spent: 8h 20m
> Remaining Estimate: 0h
>
> The non-portable runner uses reydrated pipelines which lack necessary
> information. The portable Flink runner needs to translate pipelines directly
> by proto in order to wire components into individual executable stages
> correctly.
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