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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2022/11/17 09:48:19 UTC
[GitHub] [beam] echauchot commented on a diff in pull request #24009: [Spark dataset runner] Cache datasets if used multiple times
echauchot commented on code in PR #24009:
URL: https://github.com/apache/beam/pull/24009#discussion_r1021700719
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/EvaluationContext.java:
##########
@@ -0,0 +1,119 @@
+/*
+ * 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.spark.structuredstreaming.translation;
+
+import java.util.Collection;
+import java.util.concurrent.Callable;
+import javax.annotation.Nullable;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Throwables;
+import org.apache.spark.api.java.function.ForeachFunction;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.execution.ExplainMode;
+import org.apache.spark.util.Utils;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ * The {@link EvaluationContext} is the result of a pipeline {@link PipelineTranslator#translate
+ * translation} and can be used to evaluate / run the pipeline.
+ *
+ * <p>However, in some cases pipeline translation involves the early evaluation of some parts of the
+ * pipeline. For example, this is necessary to materialize side-inputs. The {@link
+ * EvaluationContext} won't re-evaluate such datasets.
+ */
+@Internal
+public final class EvaluationContext {
+ private static final Logger LOG = LoggerFactory.getLogger(EvaluationContext.class);
+
+ interface NamedDataset<T> {
+ String name();
+
+ @Nullable
+ Dataset<WindowedValue<T>> dataset();
+ }
+
+ private final Collection<? extends NamedDataset<?>> leaveDatasets;
+ private final SparkSession session;
+
+ EvaluationContext(Collection<? extends NamedDataset<?>> leaveDatasets, SparkSession session) {
+ this.leaveDatasets = leaveDatasets;
+ this.session = session;
+ }
+
+ /** Trigger evaluation of all leave datasets. */
+ public void evaluate() {
+ for (NamedDataset<?> ds : leaveDatasets) {
+ final Dataset<?> dataset = ds.dataset();
+ if (dataset == null) {
+ continue;
+ }
+ if (LOG.isDebugEnabled()) {
+ ExplainMode explainMode = ExplainMode.fromString("simple");
+ String execPlan = dataset.queryExecution().explainString(explainMode);
+ LOG.debug("Evaluating dataset {}:\n{}", ds.name(), execPlan);
+ }
+ // force evaluation using a dummy foreach action
+ evaluate(ds.name(), () -> dataset.foreach(NOOP));
+ }
+ }
+
+ /**
+ * The purpose of this utility is to mark the evaluation of Spark actions, both during Pipeline
+ * translation, when evaluation is required, and when finally evaluating the pipeline.
+ */
+ public static void evaluate(String name, Runnable action) {
+ long startMs = System.currentTimeMillis();
+ try {
+ action.run();
+ LOG.info("Evaluated dataset {} in {}", name, durationSince(startMs));
+ } catch (RuntimeException e) {
+ LOG.error("Failed to evaluate dataset {}: {}", name, Throwables.getRootCause(e).getMessage());
+ throw new RuntimeException(e);
+ }
+ }
+
+ /**
+ * The purpose of this utility is to mark the evaluation of Spark actions, both during Pipeline
+ * translation, when evaluation is required, and when finally evaluating the pipeline.
+ */
+ public static <T> T evaluate(String name, Callable<T> action) {
Review Comment:
unused
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/PipelineTranslatorBatch.java:
##########
@@ -81,27 +80,13 @@ public class PipelineTranslatorBatch extends PipelineTranslator {
TRANSFORM_TRANSLATORS.put(
SplittableParDo.PrimitiveBoundedRead.class, new ReadSourceTranslatorBatch<>());
-
Review Comment:
It is true that the CreatePCollectionView translation was doing nothing except setting the view inside the translation context. You don't need this anymore ? This is the preparation for [#24035](https://github.com/apache/beam/issues/24035) you mentioned ?
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/TransformTranslator.java:
##########
@@ -118,69 +126,53 @@ public <T> PCollection<T> getOutput(TupleTag<T> tag) {
return pc;
}
- public Map<TupleTag<?>, PCollection<?>> getOutputs() {
- return transform.getOutputs();
- }
-
public AppliedPTransform<InT, OutT, PTransform<InT, OutT>> getCurrentTransform() {
return transform;
}
+ @Override
public <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection) {
- return cxt.getDataset(pCollection);
+ return state.getDataset(pCollection);
}
- public <T> void putDataset(PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset) {
- cxt.putDataset(pCollection, dataset);
+ @Override
+ public <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache) {
Review Comment:
nit: I'm not a big fan of double negations: cache = false seems better than noCache = true
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
Review Comment:
I like this API :+1:
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
+ }
+
+ /**
+ * The correspondence of a {@link PCollection} as result of translating a {@link PTransform}
+ * including additional metadata (such as name and dependents).
+ */
+ private static final class TranslationResult<T> implements EvaluationContext.NamedDataset<T> {
+ private final String name;
+ private @Nullable Dataset<WindowedValue<T>> dataset = null;
+ private final Set<PTransform<?, ?>> dependentTransforms = new HashSet<>();
+
+ private TranslationResult(PCollection<?> pCol) {
+ this.name = pCol.getName();
+ }
+
+ @Override
+ public String name() {
+ return name;
+ }
+
+ @Override
+ public @Nullable Dataset<WindowedValue<T>> dataset() {
+ return dataset;
}
}
- /** The translation mode of the Beam Pipeline. */
- private enum TranslationMode {
+ /** Shared, mutable state during the translation of a pipeline and omitted afterwards. */
+ interface TranslationState extends EncoderProvider {
Review Comment:
elegant use of state and transparent encoder capabilities :+1:
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/helpers/EncoderProvider.java:
##########
@@ -0,0 +1,58 @@
+/*
+ * 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.spark.structuredstreaming.translation.helpers;
+
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.kvEncoder;
+
+import java.util.function.Function;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.values.KV;
+import org.apache.spark.sql.Encoder;
+
+@Internal
+public interface EncoderProvider {
+ interface Factory<T> extends Function<Coder<T>, Encoder<T>> {
+ Factory<?> INSTANCE = EncoderHelpers::encoderFor;
+ }
+
+ <T> Encoder<T> encoderOf(Coder<T> coder, Factory<T> factory);
+
+ default <T> Encoder<T> encoderOf(Coder<T> coder) {
+ return coder instanceof KvCoder
+ ? (Encoder<T>) kvEncoderOf((KvCoder) coder)
+ : encoderOf(coder, encoderFactory());
+ }
+
+ default <K, V> Encoder<KV<K, V>> kvEncoderOf(KvCoder<K, V> coder) {
+ return encoderOf(coder, c -> kvEncoder(keyEncoderOf(coder), valueEncoderOf(coder)));
+ }
+
+ default <K, V> Encoder<K> keyEncoderOf(KvCoder<K, V> coder) {
+ return encoderOf(coder.getKeyCoder(), encoderFactory());
+ }
+
+ default <K, V> Encoder<V> valueEncoderOf(KvCoder<K, V> coder) {
+ return encoderOf(coder.getValueCoder(), encoderFactory());
+ }
+
+ default <T> Factory<T> encoderFactory() {
+ return (Factory<T>) Factory.INSTANCE;
Review Comment:
I would prefer that you inline the INSTANCE here (as it is used only here) and leave Factory as a simple tagging interface over Function. That would remove the need for the cast and the strange Factory containing a Factory.
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
+ }
+
+ /**
+ * The correspondence of a {@link PCollection} as result of translating a {@link PTransform}
+ * including additional metadata (such as name and dependents).
+ */
+ private static final class TranslationResult<T> implements EvaluationContext.NamedDataset<T> {
+ private final String name;
+ private @Nullable Dataset<WindowedValue<T>> dataset = null;
+ private final Set<PTransform<?, ?>> dependentTransforms = new HashSet<>();
+
+ private TranslationResult(PCollection<?> pCol) {
+ this.name = pCol.getName();
+ }
+
+ @Override
+ public String name() {
+ return name;
+ }
+
+ @Override
+ public @Nullable Dataset<WindowedValue<T>> dataset() {
+ return dataset;
}
}
- /** The translation mode of the Beam Pipeline. */
- private enum TranslationMode {
+ /** Shared, mutable state during the translation of a pipeline and omitted afterwards. */
+ interface TranslationState extends EncoderProvider {
Review Comment:
good also to avoid storing all the datasets and just keep the current one and then forget about it
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
+ }
+
+ /**
+ * The correspondence of a {@link PCollection} as result of translating a {@link PTransform}
+ * including additional metadata (such as name and dependents).
+ */
+ private static final class TranslationResult<T> implements EvaluationContext.NamedDataset<T> {
+ private final String name;
+ private @Nullable Dataset<WindowedValue<T>> dataset = null;
+ private final Set<PTransform<?, ?>> dependentTransforms = new HashSet<>();
+
+ private TranslationResult(PCollection<?> pCol) {
+ this.name = pCol.getName();
+ }
+
+ @Override
+ public String name() {
+ return name;
+ }
+
+ @Override
+ public @Nullable Dataset<WindowedValue<T>> dataset() {
+ return dataset;
}
}
- /** The translation mode of the Beam Pipeline. */
- private enum TranslationMode {
+ /** Shared, mutable state during the translation of a pipeline and omitted afterwards. */
+ interface TranslationState extends EncoderProvider {
+ <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection);
+
+ <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache);
- /** Uses the batch mode. */
- BATCH,
+ default <T> void putDataset(PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset) {
+ putDataset(pCollection, dataset, false);
+ }
- /** Uses the streaming mode. */
- STREAMING
+ SerializablePipelineOptions getSerializableOptions();
+
+ SparkSession getSparkSession();
}
- /** Traverses the Pipeline to determine the {@link TranslationMode} for this pipeline. */
- private static class TranslationModeDetector extends Pipeline.PipelineVisitor.Defaults {
- private static final Logger LOG = LoggerFactory.getLogger(TranslationModeDetector.class);
+ /**
+ * {@link PTransformVisitor} that translates supported {@link PTransform PTransforms} into their
+ * Spark correspondence.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted.
+ */
+ private class TranslatingVisitor extends PTransformVisitor implements TranslationState {
+ private final Map<PCollection<?>, TranslationResult<?>> translationResults;
+ private final Map<Coder<?>, ExpressionEncoder<?>> encoders;
+ private final SparkSession sparkSession;
+ private final SerializablePipelineOptions serializableOptions;
+ private final StorageLevel storageLevel;
+
+ private final Set<TranslationResult<?>> leaves;
+
+ public TranslatingVisitor(
+ SparkSession sparkSession,
+ SparkCommonPipelineOptions options,
+ Map<PCollection<?>, TranslationResult<?>> translationResults) {
+ this.sparkSession = sparkSession;
+ this.translationResults = translationResults;
+ this.serializableOptions = new SerializablePipelineOptions(options);
+ this.storageLevel = StorageLevel.fromString(options.getStorageLevel());
+ this.encoders = new HashMap<>();
+ this.leaves = new HashSet<>();
+ }
- private TranslationMode translationMode;
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+
+ AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
+ (AppliedPTransform) node.toAppliedPTransform(getPipeline());
+ try {
+ LOG.info(
+ "Translating {}: {}",
+ node.isCompositeNode() ? "composite" : "primitive",
+ node.getFullName());
+ translator.translate(transform, appliedTransform, this);
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
- TranslationModeDetector(TranslationMode defaultMode) {
- this.translationMode = defaultMode;
+ @Override
+ public <T> Encoder<T> encoderOf(Coder<T> coder, Factory<T> factory) {
+ return (Encoder<T>) encoders.computeIfAbsent(coder, (Factory) factory);
}
- TranslationModeDetector() {
- this(TranslationMode.BATCH);
+ private <T> TranslationResult<T> getResult(PCollection<T> pCollection) {
+ return (TranslationResult<T>) checkStateNotNull(translationResults.get(pCollection));
}
- TranslationMode getTranslationMode() {
- return translationMode;
+ @Override
+ public <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection) {
+ return checkStateNotNull(getResult(pCollection).dataset);
}
@Override
- public void visitValue(PValue value, TransformHierarchy.Node producer) {
- if (translationMode.equals(TranslationMode.BATCH)) {
- if (value instanceof PCollection
- && ((PCollection) value).isBounded() == PCollection.IsBounded.UNBOUNDED) {
- LOG.info(
- "Found unbounded PCollection {}. Switching to streaming execution.", value.getName());
- translationMode = TranslationMode.STREAMING;
+ public <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache) {
+ TranslationResult<T> result = getResult(pCollection);
+ if (!noCache && result.dependentTransforms.size() > 1) {
+ LOG.info("Dataset {} will be cached.", result.name);
+ result.dataset = dataset.persist(storageLevel); // use NONE to disable
+ } else {
+ result.dataset = dataset;
+ if (result.dependentTransforms.isEmpty()) {
+ leaves.add(result);
}
}
}
- }
- // --------------------------------------------------------------------------------------------
- // Pipeline utility methods
- // --------------------------------------------------------------------------------------------
+ @Override
+ public SerializablePipelineOptions getSerializableOptions() {
+ return serializableOptions;
+ }
- /** Get a {@link TransformTranslator} for the given {@link TransformHierarchy.Node}. */
- protected abstract @Nullable <
- InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- TransformTranslator<InT, OutT, TransformT> getTransformTranslator(
- @Nullable TransformT transform);
-
- /** Apply the given TransformTranslator to the given node. */
- private <InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- void applyTransformTranslator(
- TransformHierarchy.Node node,
- TransformT transform,
- TransformTranslator<InT, OutT, TransformT> transformTranslator) {
- // create the applied PTransform on the translationContext
- AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
- (AppliedPTransform) node.toAppliedPTransform(getPipeline());
- try {
- transformTranslator.translate(transform, appliedTransform, translationContext);
- } catch (IOException e) {
- throw new RuntimeException(e);
+ @Override
+ public SparkSession getSparkSession() {
+ return sparkSession;
}
}
- // --------------------------------------------------------------------------------------------
- // Pipeline visitor entry point
- // --------------------------------------------------------------------------------------------
-
/**
- * Translates the pipeline by passing this class as a visitor.
+ * {@link PTransformVisitor} that analyses dependencies of supported {@link PTransform
+ * PTransforms} to help identify cache candidates.
*
- * @param pipeline The pipeline to be translated
+ * <p>The visitor may throw if a {@link PTransform} is observed that uses unsupported features.
*/
- public void translate(Pipeline pipeline) {
- LOG.debug("starting translation of the pipeline using {}", getClass().getName());
- pipeline.traverseTopologically(this);
+ private class DependencyVisitor extends PTransformVisitor {
+ private final Map<PCollection<?>, TranslationResult<?>> results = new HashMap<>();
+
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+ for (PCollection<?> pOut : node.getOutputs().values()) {
+ results.put(pOut, new TranslationResult<>(pOut));
+ for (Map.Entry<TupleTag<?>, PCollection<?>> entry : node.getInputs().entrySet()) {
+ TranslationResult<?> input = checkStateNotNull(results.get(entry.getValue()));
+ input.dependentTransforms.add(transform);
+ }
+ }
+ }
Review Comment:
I don't understand this algo especially the nested loops because `pOut` is not referenced inside the inner loop.
Why don't you populate `results` based on outputs first and then do the second loop?
There might be something I don't get, if it's the case, please add some comments to the algo for ease of maintenance.
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
+ }
+
+ /**
+ * The correspondence of a {@link PCollection} as result of translating a {@link PTransform}
+ * including additional metadata (such as name and dependents).
+ */
+ private static final class TranslationResult<T> implements EvaluationContext.NamedDataset<T> {
+ private final String name;
+ private @Nullable Dataset<WindowedValue<T>> dataset = null;
+ private final Set<PTransform<?, ?>> dependentTransforms = new HashSet<>();
+
+ private TranslationResult(PCollection<?> pCol) {
+ this.name = pCol.getName();
+ }
+
+ @Override
+ public String name() {
+ return name;
+ }
+
+ @Override
+ public @Nullable Dataset<WindowedValue<T>> dataset() {
+ return dataset;
}
}
- /** The translation mode of the Beam Pipeline. */
- private enum TranslationMode {
+ /** Shared, mutable state during the translation of a pipeline and omitted afterwards. */
+ interface TranslationState extends EncoderProvider {
+ <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection);
+
+ <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache);
- /** Uses the batch mode. */
- BATCH,
+ default <T> void putDataset(PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset) {
+ putDataset(pCollection, dataset, false);
+ }
- /** Uses the streaming mode. */
- STREAMING
+ SerializablePipelineOptions getSerializableOptions();
+
+ SparkSession getSparkSession();
}
- /** Traverses the Pipeline to determine the {@link TranslationMode} for this pipeline. */
- private static class TranslationModeDetector extends Pipeline.PipelineVisitor.Defaults {
- private static final Logger LOG = LoggerFactory.getLogger(TranslationModeDetector.class);
+ /**
+ * {@link PTransformVisitor} that translates supported {@link PTransform PTransforms} into their
+ * Spark correspondence.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted.
+ */
+ private class TranslatingVisitor extends PTransformVisitor implements TranslationState {
+ private final Map<PCollection<?>, TranslationResult<?>> translationResults;
+ private final Map<Coder<?>, ExpressionEncoder<?>> encoders;
+ private final SparkSession sparkSession;
+ private final SerializablePipelineOptions serializableOptions;
+ private final StorageLevel storageLevel;
+
+ private final Set<TranslationResult<?>> leaves;
+
+ public TranslatingVisitor(
+ SparkSession sparkSession,
+ SparkCommonPipelineOptions options,
+ Map<PCollection<?>, TranslationResult<?>> translationResults) {
+ this.sparkSession = sparkSession;
+ this.translationResults = translationResults;
+ this.serializableOptions = new SerializablePipelineOptions(options);
+ this.storageLevel = StorageLevel.fromString(options.getStorageLevel());
+ this.encoders = new HashMap<>();
+ this.leaves = new HashSet<>();
+ }
- private TranslationMode translationMode;
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+
+ AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
+ (AppliedPTransform) node.toAppliedPTransform(getPipeline());
+ try {
+ LOG.info(
+ "Translating {}: {}",
+ node.isCompositeNode() ? "composite" : "primitive",
+ node.getFullName());
+ translator.translate(transform, appliedTransform, this);
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
- TranslationModeDetector(TranslationMode defaultMode) {
- this.translationMode = defaultMode;
+ @Override
+ public <T> Encoder<T> encoderOf(Coder<T> coder, Factory<T> factory) {
+ return (Encoder<T>) encoders.computeIfAbsent(coder, (Factory) factory);
}
- TranslationModeDetector() {
- this(TranslationMode.BATCH);
+ private <T> TranslationResult<T> getResult(PCollection<T> pCollection) {
+ return (TranslationResult<T>) checkStateNotNull(translationResults.get(pCollection));
}
- TranslationMode getTranslationMode() {
- return translationMode;
+ @Override
+ public <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection) {
+ return checkStateNotNull(getResult(pCollection).dataset);
}
@Override
- public void visitValue(PValue value, TransformHierarchy.Node producer) {
- if (translationMode.equals(TranslationMode.BATCH)) {
- if (value instanceof PCollection
- && ((PCollection) value).isBounded() == PCollection.IsBounded.UNBOUNDED) {
- LOG.info(
- "Found unbounded PCollection {}. Switching to streaming execution.", value.getName());
- translationMode = TranslationMode.STREAMING;
+ public <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache) {
+ TranslationResult<T> result = getResult(pCollection);
+ if (!noCache && result.dependentTransforms.size() > 1) {
+ LOG.info("Dataset {} will be cached.", result.name);
+ result.dataset = dataset.persist(storageLevel); // use NONE to disable
+ } else {
+ result.dataset = dataset;
+ if (result.dependentTransforms.isEmpty()) {
+ leaves.add(result);
}
}
}
- }
- // --------------------------------------------------------------------------------------------
- // Pipeline utility methods
- // --------------------------------------------------------------------------------------------
+ @Override
+ public SerializablePipelineOptions getSerializableOptions() {
+ return serializableOptions;
+ }
- /** Get a {@link TransformTranslator} for the given {@link TransformHierarchy.Node}. */
- protected abstract @Nullable <
- InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- TransformTranslator<InT, OutT, TransformT> getTransformTranslator(
- @Nullable TransformT transform);
-
- /** Apply the given TransformTranslator to the given node. */
- private <InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- void applyTransformTranslator(
- TransformHierarchy.Node node,
- TransformT transform,
- TransformTranslator<InT, OutT, TransformT> transformTranslator) {
- // create the applied PTransform on the translationContext
- AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
- (AppliedPTransform) node.toAppliedPTransform(getPipeline());
- try {
- transformTranslator.translate(transform, appliedTransform, translationContext);
- } catch (IOException e) {
- throw new RuntimeException(e);
+ @Override
+ public SparkSession getSparkSession() {
+ return sparkSession;
}
}
- // --------------------------------------------------------------------------------------------
- // Pipeline visitor entry point
- // --------------------------------------------------------------------------------------------
-
/**
- * Translates the pipeline by passing this class as a visitor.
+ * {@link PTransformVisitor} that analyses dependencies of supported {@link PTransform
+ * PTransforms} to help identify cache candidates.
*
- * @param pipeline The pipeline to be translated
+ * <p>The visitor may throw if a {@link PTransform} is observed that uses unsupported features.
*/
- public void translate(Pipeline pipeline) {
- LOG.debug("starting translation of the pipeline using {}", getClass().getName());
- pipeline.traverseTopologically(this);
+ private class DependencyVisitor extends PTransformVisitor {
+ private final Map<PCollection<?>, TranslationResult<?>> results = new HashMap<>();
+
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+ for (PCollection<?> pOut : node.getOutputs().values()) {
+ results.put(pOut, new TranslationResult<>(pOut));
+ for (Map.Entry<TupleTag<?>, PCollection<?>> entry : node.getInputs().entrySet()) {
+ TranslationResult<?> input = checkStateNotNull(results.get(entry.getValue()));
+ input.dependentTransforms.add(transform);
+ }
+ }
+ }
}
- // --------------------------------------------------------------------------------------------
- // Pipeline Visitor Methods
- // --------------------------------------------------------------------------------------------
+ /**
+ * An abstract {@link PipelineVisitor} that visits all translatable {@link PTransform} pipeline
+ * nodes of a pipeline with the respective {@link TransformTranslator}.
+ *
+ * <p>The visitor may throw if a {@link PTransform} is observed that uses unsupported features.
+ */
+ private abstract class PTransformVisitor extends PipelineVisitor.Defaults {
- @Override
- public CompositeBehavior enterCompositeTransform(TransformHierarchy.Node node) {
- PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
- TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> transformTranslator =
- getTransformTranslator(transform);
+ /** Visit the {@link PTransform} with its respective {@link TransformTranslator}. */
+ abstract <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator);
- if (transformTranslator != null) {
- LOG.info("Translating composite: {}", node.getFullName());
- applyTransformTranslator(node, transform, transformTranslator);
- return CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
- } else {
- return CompositeBehavior.ENTER_TRANSFORM;
+ @Override
+ public final CompositeBehavior enterCompositeTransform(Node node) {
+ PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
+ TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> translator =
+ getTranslator(transform);
+ if (transform != null && translator != null) {
+ visit(node, transform, translator);
+ return DO_NOT_ENTER_TRANSFORM;
+ } else {
+ return ENTER_TRANSFORM;
+ }
+ }
+
+ @Override
+ public final void visitPrimitiveTransform(Node node) {
+ PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
+ if (transform == null || transform.getClass().equals(View.CreatePCollectionView.class)) {
+ return; // ignore, nothing to be translated here
+ }
+ TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> translator =
+ getTranslator(transform);
+ if (translator == null) {
+ String urn = PTransformTranslation.urnForTransform(transform);
+ throw new UnsupportedOperationException("Transform " + urn + " is not supported.");
+ }
+ visit(node, transform, translator);
}
- }
- @Override
- public void visitPrimitiveTransform(TransformHierarchy.Node node) {
- LOG.info("Translating primitive: {}", node.getFullName());
- // get the transformation corresponding to the node we are
- // currently visiting and translate it into its Spark alternative.
- PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
- TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> transformTranslator =
- getTransformTranslator(transform);
-
- if (transformTranslator == null) {
- String transformUrn = PTransformTranslation.urnForTransform(node.getTransform());
- throw new UnsupportedOperationException(
- "The transform " + transformUrn + " is currently not supported.");
- }
- applyTransformTranslator(node, transform, transformTranslator);
+ /** {@link TransformTranslator} for {@link PTransform} if translation is known and supported. */
+ private @Nullable TransformTranslator<PInput, POutput, PTransform<PInput, POutput>>
Review Comment:
please rename to getTransformTranslatorIfTranslatable for clarity
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ParDoTranslatorBatch.java:
##########
@@ -220,8 +225,9 @@ private SideInputBroadcast createBroadcastSideInputs(
Coder<WindowedValue<?>> windowedValueCoder =
(Coder<WindowedValue<?>>)
(Coder<?>) WindowedValue.getFullCoder(pc.getCoder(), windowCoder);
- Dataset<WindowedValue<?>> broadcastSet = context.getSideInputDataset(sideInput);
- List<WindowedValue<?>> valuesList = broadcastSet.collectAsList();
+ Dataset<WindowedValue<?>> broadcastSet = context.getDataset((PCollection) pc);
+ List<WindowedValue<?>> valuesList =
Review Comment:
now I see the preparation for side inputs you mentioned. :+1:
You evaluate the associated PCollection when you need to broadcast it for side inputs
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
Review Comment:
Very clear ! :+1:
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/TransformTranslator.java:
##########
@@ -51,22 +48,24 @@
import scala.reflect.ClassTag;
/**
- * Supports translation between a Beam transform, and Spark's operations on Datasets.
+ * A {@link TransformTranslator} provides the capability to translate a specific primitive or
+ * composite {@link PTransform} into its Spark correspondence.
*
- * <p>WARNING: Do not make this class serializable! It could easily hide situations where
- * unnecessary references leak into Spark closures.
+ * <p>WARNING: {@link TransformTranslator TransformTranslators} should never be serializable! This
+ * could easily hide situations where unnecessary references leak into Spark closures.
*/
+@Internal
public abstract class TransformTranslator<
InT extends PInput, OutT extends POutput, TransformT extends PTransform<? extends InT, OutT>> {
protected abstract void translate(TransformT transform, Context cxt) throws IOException;
- public final void translate(
+ protected final void translate(
Review Comment:
can be package local now that this method is no more the one that is overridden
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
+ }
+
+ /**
+ * The correspondence of a {@link PCollection} as result of translating a {@link PTransform}
+ * including additional metadata (such as name and dependents).
+ */
+ private static final class TranslationResult<T> implements EvaluationContext.NamedDataset<T> {
+ private final String name;
+ private @Nullable Dataset<WindowedValue<T>> dataset = null;
+ private final Set<PTransform<?, ?>> dependentTransforms = new HashSet<>();
+
+ private TranslationResult(PCollection<?> pCol) {
+ this.name = pCol.getName();
+ }
+
+ @Override
+ public String name() {
+ return name;
+ }
+
+ @Override
+ public @Nullable Dataset<WindowedValue<T>> dataset() {
+ return dataset;
}
}
- /** The translation mode of the Beam Pipeline. */
- private enum TranslationMode {
+ /** Shared, mutable state during the translation of a pipeline and omitted afterwards. */
+ interface TranslationState extends EncoderProvider {
+ <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection);
+
+ <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache);
- /** Uses the batch mode. */
- BATCH,
+ default <T> void putDataset(PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset) {
+ putDataset(pCollection, dataset, false);
+ }
- /** Uses the streaming mode. */
- STREAMING
+ SerializablePipelineOptions getSerializableOptions();
+
+ SparkSession getSparkSession();
}
- /** Traverses the Pipeline to determine the {@link TranslationMode} for this pipeline. */
- private static class TranslationModeDetector extends Pipeline.PipelineVisitor.Defaults {
- private static final Logger LOG = LoggerFactory.getLogger(TranslationModeDetector.class);
+ /**
+ * {@link PTransformVisitor} that translates supported {@link PTransform PTransforms} into their
+ * Spark correspondence.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted.
+ */
+ private class TranslatingVisitor extends PTransformVisitor implements TranslationState {
+ private final Map<PCollection<?>, TranslationResult<?>> translationResults;
+ private final Map<Coder<?>, ExpressionEncoder<?>> encoders;
+ private final SparkSession sparkSession;
+ private final SerializablePipelineOptions serializableOptions;
+ private final StorageLevel storageLevel;
+
+ private final Set<TranslationResult<?>> leaves;
+
+ public TranslatingVisitor(
+ SparkSession sparkSession,
+ SparkCommonPipelineOptions options,
+ Map<PCollection<?>, TranslationResult<?>> translationResults) {
+ this.sparkSession = sparkSession;
+ this.translationResults = translationResults;
+ this.serializableOptions = new SerializablePipelineOptions(options);
+ this.storageLevel = StorageLevel.fromString(options.getStorageLevel());
+ this.encoders = new HashMap<>();
+ this.leaves = new HashSet<>();
+ }
- private TranslationMode translationMode;
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+
+ AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
Review Comment:
Better use of types :+1:
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/PipelineTranslatorBatch.java:
##########
@@ -81,27 +80,13 @@ public class PipelineTranslatorBatch extends PipelineTranslator {
TRANSFORM_TRANSLATORS.put(
SplittableParDo.PrimitiveBoundedRead.class, new ReadSourceTranslatorBatch<>());
-
- TRANSFORM_TRANSLATORS.put(
- View.CreatePCollectionView.class, new CreatePCollectionViewTranslatorBatch<>());
- }
-
- public PipelineTranslatorBatch(SparkStructuredStreamingPipelineOptions options) {
- translationContext = new TranslationContext(options);
}
- /** Returns a translator for the given node, if it is possible, otherwise null. */
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
@Override
@Nullable
protected <InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- TransformTranslator<InT, OutT, TransformT> getTransformTranslator(
- @Nullable TransformT transform) {
- // Root of the graph is null
- if (transform == null) {
- return null;
- }
- TransformTranslator<InT, OutT, TransformT> translator =
- TRANSFORM_TRANSLATORS.get(transform.getClass());
- return translator != null && translator.canTranslate(transform) ? translator : null;
Review Comment:
you no more check that the transform can be translated here but you rather do it in the visitor. Right?
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
+ }
+
+ /**
+ * The correspondence of a {@link PCollection} as result of translating a {@link PTransform}
+ * including additional metadata (such as name and dependents).
+ */
+ private static final class TranslationResult<T> implements EvaluationContext.NamedDataset<T> {
+ private final String name;
+ private @Nullable Dataset<WindowedValue<T>> dataset = null;
+ private final Set<PTransform<?, ?>> dependentTransforms = new HashSet<>();
+
+ private TranslationResult(PCollection<?> pCol) {
+ this.name = pCol.getName();
+ }
+
+ @Override
+ public String name() {
+ return name;
+ }
+
+ @Override
+ public @Nullable Dataset<WindowedValue<T>> dataset() {
+ return dataset;
}
}
- /** The translation mode of the Beam Pipeline. */
- private enum TranslationMode {
+ /** Shared, mutable state during the translation of a pipeline and omitted afterwards. */
+ interface TranslationState extends EncoderProvider {
+ <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection);
+
+ <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache);
- /** Uses the batch mode. */
- BATCH,
+ default <T> void putDataset(PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset) {
+ putDataset(pCollection, dataset, false);
+ }
- /** Uses the streaming mode. */
- STREAMING
+ SerializablePipelineOptions getSerializableOptions();
+
+ SparkSession getSparkSession();
}
- /** Traverses the Pipeline to determine the {@link TranslationMode} for this pipeline. */
- private static class TranslationModeDetector extends Pipeline.PipelineVisitor.Defaults {
- private static final Logger LOG = LoggerFactory.getLogger(TranslationModeDetector.class);
+ /**
+ * {@link PTransformVisitor} that translates supported {@link PTransform PTransforms} into their
+ * Spark correspondence.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted.
+ */
+ private class TranslatingVisitor extends PTransformVisitor implements TranslationState {
+ private final Map<PCollection<?>, TranslationResult<?>> translationResults;
+ private final Map<Coder<?>, ExpressionEncoder<?>> encoders;
+ private final SparkSession sparkSession;
+ private final SerializablePipelineOptions serializableOptions;
+ private final StorageLevel storageLevel;
+
+ private final Set<TranslationResult<?>> leaves;
+
+ public TranslatingVisitor(
+ SparkSession sparkSession,
+ SparkCommonPipelineOptions options,
+ Map<PCollection<?>, TranslationResult<?>> translationResults) {
+ this.sparkSession = sparkSession;
+ this.translationResults = translationResults;
+ this.serializableOptions = new SerializablePipelineOptions(options);
+ this.storageLevel = StorageLevel.fromString(options.getStorageLevel());
+ this.encoders = new HashMap<>();
+ this.leaves = new HashSet<>();
+ }
- private TranslationMode translationMode;
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+
+ AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
+ (AppliedPTransform) node.toAppliedPTransform(getPipeline());
+ try {
+ LOG.info(
+ "Translating {}: {}",
+ node.isCompositeNode() ? "composite" : "primitive",
+ node.getFullName());
+ translator.translate(transform, appliedTransform, this);
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
- TranslationModeDetector(TranslationMode defaultMode) {
- this.translationMode = defaultMode;
+ @Override
+ public <T> Encoder<T> encoderOf(Coder<T> coder, Factory<T> factory) {
+ return (Encoder<T>) encoders.computeIfAbsent(coder, (Factory) factory);
}
- TranslationModeDetector() {
- this(TranslationMode.BATCH);
+ private <T> TranslationResult<T> getResult(PCollection<T> pCollection) {
+ return (TranslationResult<T>) checkStateNotNull(translationResults.get(pCollection));
}
- TranslationMode getTranslationMode() {
- return translationMode;
+ @Override
+ public <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection) {
+ return checkStateNotNull(getResult(pCollection).dataset);
}
@Override
- public void visitValue(PValue value, TransformHierarchy.Node producer) {
- if (translationMode.equals(TranslationMode.BATCH)) {
- if (value instanceof PCollection
- && ((PCollection) value).isBounded() == PCollection.IsBounded.UNBOUNDED) {
- LOG.info(
- "Found unbounded PCollection {}. Switching to streaming execution.", value.getName());
- translationMode = TranslationMode.STREAMING;
+ public <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache) {
+ TranslationResult<T> result = getResult(pCollection);
+ if (!noCache && result.dependentTransforms.size() > 1) {
+ LOG.info("Dataset {} will be cached.", result.name);
+ result.dataset = dataset.persist(storageLevel); // use NONE to disable
+ } else {
+ result.dataset = dataset;
+ if (result.dependentTransforms.isEmpty()) {
+ leaves.add(result);
}
}
}
- }
- // --------------------------------------------------------------------------------------------
- // Pipeline utility methods
- // --------------------------------------------------------------------------------------------
+ @Override
+ public SerializablePipelineOptions getSerializableOptions() {
+ return serializableOptions;
+ }
- /** Get a {@link TransformTranslator} for the given {@link TransformHierarchy.Node}. */
- protected abstract @Nullable <
- InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- TransformTranslator<InT, OutT, TransformT> getTransformTranslator(
- @Nullable TransformT transform);
-
- /** Apply the given TransformTranslator to the given node. */
- private <InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- void applyTransformTranslator(
- TransformHierarchy.Node node,
- TransformT transform,
- TransformTranslator<InT, OutT, TransformT> transformTranslator) {
- // create the applied PTransform on the translationContext
- AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
- (AppliedPTransform) node.toAppliedPTransform(getPipeline());
- try {
- transformTranslator.translate(transform, appliedTransform, translationContext);
- } catch (IOException e) {
- throw new RuntimeException(e);
+ @Override
+ public SparkSession getSparkSession() {
+ return sparkSession;
}
}
- // --------------------------------------------------------------------------------------------
- // Pipeline visitor entry point
- // --------------------------------------------------------------------------------------------
-
/**
- * Translates the pipeline by passing this class as a visitor.
+ * {@link PTransformVisitor} that analyses dependencies of supported {@link PTransform
+ * PTransforms} to help identify cache candidates.
*
- * @param pipeline The pipeline to be translated
+ * <p>The visitor may throw if a {@link PTransform} is observed that uses unsupported features.
*/
- public void translate(Pipeline pipeline) {
- LOG.debug("starting translation of the pipeline using {}", getClass().getName());
- pipeline.traverseTopologically(this);
+ private class DependencyVisitor extends PTransformVisitor {
+ private final Map<PCollection<?>, TranslationResult<?>> results = new HashMap<>();
+
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+ for (PCollection<?> pOut : node.getOutputs().values()) {
+ results.put(pOut, new TranslationResult<>(pOut));
+ for (Map.Entry<TupleTag<?>, PCollection<?>> entry : node.getInputs().entrySet()) {
+ TranslationResult<?> input = checkStateNotNull(results.get(entry.getValue()));
+ input.dependentTransforms.add(transform);
+ }
+ }
+ }
}
- // --------------------------------------------------------------------------------------------
- // Pipeline Visitor Methods
- // --------------------------------------------------------------------------------------------
+ /**
+ * An abstract {@link PipelineVisitor} that visits all translatable {@link PTransform} pipeline
+ * nodes of a pipeline with the respective {@link TransformTranslator}.
+ *
+ * <p>The visitor may throw if a {@link PTransform} is observed that uses unsupported features.
+ */
+ private abstract class PTransformVisitor extends PipelineVisitor.Defaults {
- @Override
- public CompositeBehavior enterCompositeTransform(TransformHierarchy.Node node) {
- PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
- TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> transformTranslator =
- getTransformTranslator(transform);
+ /** Visit the {@link PTransform} with its respective {@link TransformTranslator}. */
+ abstract <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator);
- if (transformTranslator != null) {
- LOG.info("Translating composite: {}", node.getFullName());
- applyTransformTranslator(node, transform, transformTranslator);
- return CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
- } else {
- return CompositeBehavior.ENTER_TRANSFORM;
+ @Override
+ public final CompositeBehavior enterCompositeTransform(Node node) {
+ PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
+ TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> translator =
+ getTranslator(transform);
+ if (transform != null && translator != null) {
+ visit(node, transform, translator);
+ return DO_NOT_ENTER_TRANSFORM;
+ } else {
+ return ENTER_TRANSFORM;
+ }
+ }
+
+ @Override
+ public final void visitPrimitiveTransform(Node node) {
+ PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
+ if (transform == null || transform.getClass().equals(View.CreatePCollectionView.class)) {
+ return; // ignore, nothing to be translated here
Review Comment:
cf question on [PipelineTranslatorBatch.java](https://github.com/apache/beam/pull/24009/files#diff-135056b6cae8cfffc97af038ebe5d427e0ce4f58a0c947e510a748e0879cb2b3). Can you put a comment to elaborate the PCollectionView case ?
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
+ }
+
+ /**
+ * The correspondence of a {@link PCollection} as result of translating a {@link PTransform}
+ * including additional metadata (such as name and dependents).
+ */
+ private static final class TranslationResult<T> implements EvaluationContext.NamedDataset<T> {
+ private final String name;
+ private @Nullable Dataset<WindowedValue<T>> dataset = null;
+ private final Set<PTransform<?, ?>> dependentTransforms = new HashSet<>();
+
+ private TranslationResult(PCollection<?> pCol) {
+ this.name = pCol.getName();
+ }
+
+ @Override
+ public String name() {
+ return name;
+ }
+
+ @Override
+ public @Nullable Dataset<WindowedValue<T>> dataset() {
+ return dataset;
}
}
- /** The translation mode of the Beam Pipeline. */
- private enum TranslationMode {
+ /** Shared, mutable state during the translation of a pipeline and omitted afterwards. */
+ interface TranslationState extends EncoderProvider {
+ <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection);
+
+ <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache);
- /** Uses the batch mode. */
- BATCH,
+ default <T> void putDataset(PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset) {
+ putDataset(pCollection, dataset, false);
+ }
- /** Uses the streaming mode. */
- STREAMING
+ SerializablePipelineOptions getSerializableOptions();
+
+ SparkSession getSparkSession();
}
- /** Traverses the Pipeline to determine the {@link TranslationMode} for this pipeline. */
- private static class TranslationModeDetector extends Pipeline.PipelineVisitor.Defaults {
- private static final Logger LOG = LoggerFactory.getLogger(TranslationModeDetector.class);
+ /**
+ * {@link PTransformVisitor} that translates supported {@link PTransform PTransforms} into their
+ * Spark correspondence.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted.
+ */
+ private class TranslatingVisitor extends PTransformVisitor implements TranslationState {
+ private final Map<PCollection<?>, TranslationResult<?>> translationResults;
+ private final Map<Coder<?>, ExpressionEncoder<?>> encoders;
+ private final SparkSession sparkSession;
+ private final SerializablePipelineOptions serializableOptions;
+ private final StorageLevel storageLevel;
+
+ private final Set<TranslationResult<?>> leaves;
+
+ public TranslatingVisitor(
+ SparkSession sparkSession,
+ SparkCommonPipelineOptions options,
+ Map<PCollection<?>, TranslationResult<?>> translationResults) {
+ this.sparkSession = sparkSession;
+ this.translationResults = translationResults;
+ this.serializableOptions = new SerializablePipelineOptions(options);
+ this.storageLevel = StorageLevel.fromString(options.getStorageLevel());
+ this.encoders = new HashMap<>();
+ this.leaves = new HashSet<>();
+ }
- private TranslationMode translationMode;
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+
+ AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
+ (AppliedPTransform) node.toAppliedPTransform(getPipeline());
+ try {
+ LOG.info(
+ "Translating {}: {}",
+ node.isCompositeNode() ? "composite" : "primitive",
+ node.getFullName());
+ translator.translate(transform, appliedTransform, this);
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
- TranslationModeDetector(TranslationMode defaultMode) {
- this.translationMode = defaultMode;
+ @Override
+ public <T> Encoder<T> encoderOf(Coder<T> coder, Factory<T> factory) {
+ return (Encoder<T>) encoders.computeIfAbsent(coder, (Factory) factory);
}
- TranslationModeDetector() {
- this(TranslationMode.BATCH);
+ private <T> TranslationResult<T> getResult(PCollection<T> pCollection) {
+ return (TranslationResult<T>) checkStateNotNull(translationResults.get(pCollection));
}
- TranslationMode getTranslationMode() {
- return translationMode;
+ @Override
+ public <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection) {
+ return checkStateNotNull(getResult(pCollection).dataset);
}
@Override
- public void visitValue(PValue value, TransformHierarchy.Node producer) {
- if (translationMode.equals(TranslationMode.BATCH)) {
- if (value instanceof PCollection
- && ((PCollection) value).isBounded() == PCollection.IsBounded.UNBOUNDED) {
- LOG.info(
- "Found unbounded PCollection {}. Switching to streaming execution.", value.getName());
- translationMode = TranslationMode.STREAMING;
+ public <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache) {
+ TranslationResult<T> result = getResult(pCollection);
+ if (!noCache && result.dependentTransforms.size() > 1) {
Review Comment:
nit: for symmetry with else branch: use `!result.dependentTransforms.isEmpty()`
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/PipelineTranslator.java:
##########
@@ -17,170 +17,336 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
+import static org.apache.beam.sdk.Pipeline.PipelineVisitor.CompositeBehavior.ENTER_TRANSFORM;
+import static org.apache.beam.sdk.util.Preconditions.checkStateNotNull;
+import static org.apache.beam.sdk.values.PCollection.IsBounded.UNBOUNDED;
+
import java.io.IOException;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import javax.annotation.Nullable;
import org.apache.beam.runners.core.construction.PTransformTranslation;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.spark.SparkCommonPipelineOptions;
+import org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderProvider;
import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.Pipeline.PipelineVisitor;
+import org.apache.beam.sdk.annotations.Internal;
+import org.apache.beam.sdk.coders.Coder;
import org.apache.beam.sdk.options.StreamingOptions;
import org.apache.beam.sdk.runners.AppliedPTransform;
-import org.apache.beam.sdk.runners.TransformHierarchy;
+import org.apache.beam.sdk.runners.TransformHierarchy.Node;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.View;
+import org.apache.beam.sdk.util.WindowedValue;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PInput;
import org.apache.beam.sdk.values.POutput;
import org.apache.beam.sdk.values.PValue;
-import org.checkerframework.checker.nullness.qual.Nullable;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
+import org.apache.spark.storage.StorageLevel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
- * {@link Pipeline.PipelineVisitor} that translates the Beam operators to their Spark counterparts.
- * It also does the pipeline preparation: mode detection, transforms replacement, classpath
- * preparation.
+ * The pipeline translator translates a Beam {@link Pipeline} into a Spark correspondence, that can
+ * then be evaluated.
+ *
+ * <p>The translation involves traversing the hierarchy of a pipeline multiple times:
+ *
+ * <ol>
+ * <li>Detect if {@link StreamingOptions#setStreaming streaming} mode is required.
+ * <li>Identify datasets that are repeatedly used as input and should be cached.
+ * <li>And finally, translate each primitive or composite {@link PTransform} that is {@link
+ * #getTransformTranslator known} and {@link TransformTranslator#canTranslate supported} into
+ * its Spark correspondence. If a composite is not supported, it will be expanded further into
+ * its parts and translated then.
+ * </ol>
*/
-@SuppressWarnings({
- "nullness" // TODO(https://github.com/apache/beam/issues/20497)
-})
-public abstract class PipelineTranslator extends Pipeline.PipelineVisitor.Defaults {
+@Internal
+public abstract class PipelineTranslator {
private static final Logger LOG = LoggerFactory.getLogger(PipelineTranslator.class);
- protected TranslationContext translationContext;
- // --------------------------------------------------------------------------------------------
- // Pipeline preparation methods
- // --------------------------------------------------------------------------------------------
public static void replaceTransforms(Pipeline pipeline, StreamingOptions options) {
pipeline.replaceAll(SparkTransformOverrides.getDefaultOverrides(options.isStreaming()));
}
/**
- * Visit the pipeline to determine the translation mode (batch/streaming) and update options
- * accordingly.
+ * Analyse the pipeline to determine if we have to switch to streaming mode for the pipeline
+ * translation and update {@link StreamingOptions} accordingly.
*/
- public static void detectTranslationMode(Pipeline pipeline, StreamingOptions options) {
- TranslationModeDetector detector = new TranslationModeDetector();
+ public static void detectStreamingMode(Pipeline pipeline, StreamingOptions options) {
+ StreamingModeDetector detector = new StreamingModeDetector(options.isStreaming());
pipeline.traverseTopologically(detector);
- if (detector.getTranslationMode().equals(TranslationMode.STREAMING)) {
- options.setStreaming(true);
+ options.setStreaming(detector.streaming);
+ }
+
+ /** Returns a {@link TransformTranslator} for the given {@link PTransform} if known. */
+ protected abstract @Nullable <
+ InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
+ TransformTranslator<InT, OutT, TransformT> getTransformTranslator(TransformT transform);
+
+ /**
+ * Translates a Beam pipeline into its Spark correspondence using the Spark SQL / Dataset API.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted to be able to continue with the translation.
+ *
+ * @return The result of the translation is an {@link EvaluationContext} that can trigger the
+ * evaluation of the Spark pipeline.
+ */
+ public EvaluationContext translate(
+ Pipeline pipeline, SparkSession session, SparkCommonPipelineOptions options) {
+ LOG.debug("starting translation of the pipeline using {}", getClass().getName());
+ DependencyVisitor dependencies = new DependencyVisitor();
+ pipeline.traverseTopologically(dependencies);
+
+ TranslatingVisitor translator = new TranslatingVisitor(session, options, dependencies.results);
+ pipeline.traverseTopologically(translator);
+
+ return new EvaluationContext(translator.leaves, session);
+ }
+
+ /**
+ * The correspondence of a {@link PCollection} as result of translating a {@link PTransform}
+ * including additional metadata (such as name and dependents).
+ */
+ private static final class TranslationResult<T> implements EvaluationContext.NamedDataset<T> {
+ private final String name;
+ private @Nullable Dataset<WindowedValue<T>> dataset = null;
+ private final Set<PTransform<?, ?>> dependentTransforms = new HashSet<>();
+
+ private TranslationResult(PCollection<?> pCol) {
+ this.name = pCol.getName();
+ }
+
+ @Override
+ public String name() {
+ return name;
+ }
+
+ @Override
+ public @Nullable Dataset<WindowedValue<T>> dataset() {
+ return dataset;
}
}
- /** The translation mode of the Beam Pipeline. */
- private enum TranslationMode {
+ /** Shared, mutable state during the translation of a pipeline and omitted afterwards. */
+ interface TranslationState extends EncoderProvider {
+ <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection);
+
+ <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache);
- /** Uses the batch mode. */
- BATCH,
+ default <T> void putDataset(PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset) {
+ putDataset(pCollection, dataset, false);
+ }
- /** Uses the streaming mode. */
- STREAMING
+ SerializablePipelineOptions getSerializableOptions();
+
+ SparkSession getSparkSession();
}
- /** Traverses the Pipeline to determine the {@link TranslationMode} for this pipeline. */
- private static class TranslationModeDetector extends Pipeline.PipelineVisitor.Defaults {
- private static final Logger LOG = LoggerFactory.getLogger(TranslationModeDetector.class);
+ /**
+ * {@link PTransformVisitor} that translates supported {@link PTransform PTransforms} into their
+ * Spark correspondence.
+ *
+ * <p>Note, in some cases this involves the early evaluation of some parts of the pipeline. For
+ * example, in order to use a side-input {@link org.apache.beam.sdk.values.PCollectionView
+ * PCollectionView} in a translation the corresponding Spark {@link
+ * org.apache.beam.runners.spark.translation.Dataset Dataset} might have to be collected and
+ * broadcasted.
+ */
+ private class TranslatingVisitor extends PTransformVisitor implements TranslationState {
+ private final Map<PCollection<?>, TranslationResult<?>> translationResults;
+ private final Map<Coder<?>, ExpressionEncoder<?>> encoders;
+ private final SparkSession sparkSession;
+ private final SerializablePipelineOptions serializableOptions;
+ private final StorageLevel storageLevel;
+
+ private final Set<TranslationResult<?>> leaves;
+
+ public TranslatingVisitor(
+ SparkSession sparkSession,
+ SparkCommonPipelineOptions options,
+ Map<PCollection<?>, TranslationResult<?>> translationResults) {
+ this.sparkSession = sparkSession;
+ this.translationResults = translationResults;
+ this.serializableOptions = new SerializablePipelineOptions(options);
+ this.storageLevel = StorageLevel.fromString(options.getStorageLevel());
+ this.encoders = new HashMap<>();
+ this.leaves = new HashSet<>();
+ }
- private TranslationMode translationMode;
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+
+ AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
+ (AppliedPTransform) node.toAppliedPTransform(getPipeline());
+ try {
+ LOG.info(
+ "Translating {}: {}",
+ node.isCompositeNode() ? "composite" : "primitive",
+ node.getFullName());
+ translator.translate(transform, appliedTransform, this);
+ } catch (IOException e) {
+ throw new RuntimeException(e);
+ }
+ }
- TranslationModeDetector(TranslationMode defaultMode) {
- this.translationMode = defaultMode;
+ @Override
+ public <T> Encoder<T> encoderOf(Coder<T> coder, Factory<T> factory) {
+ return (Encoder<T>) encoders.computeIfAbsent(coder, (Factory) factory);
}
- TranslationModeDetector() {
- this(TranslationMode.BATCH);
+ private <T> TranslationResult<T> getResult(PCollection<T> pCollection) {
+ return (TranslationResult<T>) checkStateNotNull(translationResults.get(pCollection));
}
- TranslationMode getTranslationMode() {
- return translationMode;
+ @Override
+ public <T> Dataset<WindowedValue<T>> getDataset(PCollection<T> pCollection) {
+ return checkStateNotNull(getResult(pCollection).dataset);
}
@Override
- public void visitValue(PValue value, TransformHierarchy.Node producer) {
- if (translationMode.equals(TranslationMode.BATCH)) {
- if (value instanceof PCollection
- && ((PCollection) value).isBounded() == PCollection.IsBounded.UNBOUNDED) {
- LOG.info(
- "Found unbounded PCollection {}. Switching to streaming execution.", value.getName());
- translationMode = TranslationMode.STREAMING;
+ public <T> void putDataset(
+ PCollection<T> pCollection, Dataset<WindowedValue<T>> dataset, boolean noCache) {
+ TranslationResult<T> result = getResult(pCollection);
+ if (!noCache && result.dependentTransforms.size() > 1) {
+ LOG.info("Dataset {} will be cached.", result.name);
+ result.dataset = dataset.persist(storageLevel); // use NONE to disable
+ } else {
+ result.dataset = dataset;
+ if (result.dependentTransforms.isEmpty()) {
+ leaves.add(result);
}
}
}
- }
- // --------------------------------------------------------------------------------------------
- // Pipeline utility methods
- // --------------------------------------------------------------------------------------------
+ @Override
+ public SerializablePipelineOptions getSerializableOptions() {
+ return serializableOptions;
+ }
- /** Get a {@link TransformTranslator} for the given {@link TransformHierarchy.Node}. */
- protected abstract @Nullable <
- InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- TransformTranslator<InT, OutT, TransformT> getTransformTranslator(
- @Nullable TransformT transform);
-
- /** Apply the given TransformTranslator to the given node. */
- private <InT extends PInput, OutT extends POutput, TransformT extends PTransform<InT, OutT>>
- void applyTransformTranslator(
- TransformHierarchy.Node node,
- TransformT transform,
- TransformTranslator<InT, OutT, TransformT> transformTranslator) {
- // create the applied PTransform on the translationContext
- AppliedPTransform<InT, OutT, PTransform<InT, OutT>> appliedTransform =
- (AppliedPTransform) node.toAppliedPTransform(getPipeline());
- try {
- transformTranslator.translate(transform, appliedTransform, translationContext);
- } catch (IOException e) {
- throw new RuntimeException(e);
+ @Override
+ public SparkSession getSparkSession() {
+ return sparkSession;
}
}
- // --------------------------------------------------------------------------------------------
- // Pipeline visitor entry point
- // --------------------------------------------------------------------------------------------
-
/**
- * Translates the pipeline by passing this class as a visitor.
+ * {@link PTransformVisitor} that analyses dependencies of supported {@link PTransform
+ * PTransforms} to help identify cache candidates.
*
- * @param pipeline The pipeline to be translated
+ * <p>The visitor may throw if a {@link PTransform} is observed that uses unsupported features.
*/
- public void translate(Pipeline pipeline) {
- LOG.debug("starting translation of the pipeline using {}", getClass().getName());
- pipeline.traverseTopologically(this);
+ private class DependencyVisitor extends PTransformVisitor {
+ private final Map<PCollection<?>, TranslationResult<?>> results = new HashMap<>();
+
+ @Override
+ <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator) {
+ for (PCollection<?> pOut : node.getOutputs().values()) {
+ results.put(pOut, new TranslationResult<>(pOut));
+ for (Map.Entry<TupleTag<?>, PCollection<?>> entry : node.getInputs().entrySet()) {
+ TranslationResult<?> input = checkStateNotNull(results.get(entry.getValue()));
+ input.dependentTransforms.add(transform);
+ }
+ }
+ }
}
- // --------------------------------------------------------------------------------------------
- // Pipeline Visitor Methods
- // --------------------------------------------------------------------------------------------
+ /**
+ * An abstract {@link PipelineVisitor} that visits all translatable {@link PTransform} pipeline
+ * nodes of a pipeline with the respective {@link TransformTranslator}.
+ *
+ * <p>The visitor may throw if a {@link PTransform} is observed that uses unsupported features.
+ */
+ private abstract class PTransformVisitor extends PipelineVisitor.Defaults {
- @Override
- public CompositeBehavior enterCompositeTransform(TransformHierarchy.Node node) {
- PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
- TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> transformTranslator =
- getTransformTranslator(transform);
+ /** Visit the {@link PTransform} with its respective {@link TransformTranslator}. */
+ abstract <InT extends PInput, OutT extends POutput> void visit(
+ Node node,
+ PTransform<InT, OutT> transform,
+ TransformTranslator<InT, OutT, PTransform<InT, OutT>> translator);
- if (transformTranslator != null) {
- LOG.info("Translating composite: {}", node.getFullName());
- applyTransformTranslator(node, transform, transformTranslator);
- return CompositeBehavior.DO_NOT_ENTER_TRANSFORM;
- } else {
- return CompositeBehavior.ENTER_TRANSFORM;
+ @Override
+ public final CompositeBehavior enterCompositeTransform(Node node) {
+ PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
+ TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> translator =
+ getTranslator(transform);
+ if (transform != null && translator != null) {
+ visit(node, transform, translator);
+ return DO_NOT_ENTER_TRANSFORM;
+ } else {
+ return ENTER_TRANSFORM;
+ }
+ }
+
+ @Override
+ public final void visitPrimitiveTransform(Node node) {
+ PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
+ if (transform == null || transform.getClass().equals(View.CreatePCollectionView.class)) {
+ return; // ignore, nothing to be translated here
+ }
+ TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> translator =
+ getTranslator(transform);
+ if (translator == null) {
+ String urn = PTransformTranslation.urnForTransform(transform);
+ throw new UnsupportedOperationException("Transform " + urn + " is not supported.");
+ }
+ visit(node, transform, translator);
}
- }
- @Override
- public void visitPrimitiveTransform(TransformHierarchy.Node node) {
- LOG.info("Translating primitive: {}", node.getFullName());
- // get the transformation corresponding to the node we are
- // currently visiting and translate it into its Spark alternative.
- PTransform<PInput, POutput> transform = (PTransform<PInput, POutput>) node.getTransform();
- TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> transformTranslator =
- getTransformTranslator(transform);
-
- if (transformTranslator == null) {
- String transformUrn = PTransformTranslation.urnForTransform(node.getTransform());
- throw new UnsupportedOperationException(
- "The transform " + transformUrn + " is currently not supported.");
- }
- applyTransformTranslator(node, transform, transformTranslator);
+ /** {@link TransformTranslator} for {@link PTransform} if translation is known and supported. */
+ private @Nullable TransformTranslator<PInput, POutput, PTransform<PInput, POutput>>
+ getTranslator(@Nullable PTransform<PInput, POutput> transform) {
+ if (transform == null) {
+ return null;
+ }
+ TransformTranslator<PInput, POutput, PTransform<PInput, POutput>> translator =
+ getTransformTranslator(transform);
+ return translator != null && translator.canTranslate(transform) ? translator : null;
+ }
}
- public TranslationContext getTranslationContext() {
- return translationContext;
+ /**
+ * Traverse the pipeline to check for unbounded {@link PCollection PCollections} that would
+ * require streaming mode unless streaming mode is already enabled.
+ */
+ private static class StreamingModeDetector extends PipelineVisitor.Defaults {
+ private boolean streaming;
+
+ StreamingModeDetector(boolean streaming) {
+ this.streaming = streaming;
+ }
+
+ @Override
+ public CompositeBehavior enterCompositeTransform(Node node) {
+ return streaming ? DO_NOT_ENTER_TRANSFORM : ENTER_TRANSFORM; // stop if in streaming mode
Review Comment:
good improvement to stop traversing the hierarchy if the streaming mode is already forced !
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