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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2022/09/16 12:50:59 UTC
[GitHub] [beam] echauchot commented on a diff in pull request #22446: Improved pipeline translation in SparkStructuredStreamingRunner
echauchot commented on code in PR #22446:
URL: https://github.com/apache/beam/pull/22446#discussion_r972073328
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/TransformTranslator.java:
##########
@@ -17,15 +17,197 @@
*/
package org.apache.beam.runners.spark.structuredstreaming.translation;
-import java.io.Serializable;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.encoderFor;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.kvEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.windowedValueEncoder;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkState;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterables.getOnlyElement;
+
+import java.io.IOException;
+import java.util.List;
+import java.util.Map;
+import org.apache.beam.runners.core.construction.SerializablePipelineOptions;
+import org.apache.beam.runners.core.construction.TransformInputs;
+import org.apache.beam.sdk.coders.Coder;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.options.PipelineOptions;
+import org.apache.beam.sdk.runners.AppliedPTransform;
import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.PCollection;
+import org.apache.beam.sdk.values.PCollectionView;
+import org.apache.beam.sdk.values.PInput;
+import org.apache.beam.sdk.values.POutput;
+import org.apache.beam.sdk.values.TupleTag;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.SparkSession;
+import org.checkerframework.checker.nullness.qual.MonotonicNonNull;
+import scala.Tuple2;
+import scala.reflect.ClassTag;
+
+/**
+ * Supports translation between a Beam transform, and Spark's operations on Datasets.
+ *
+ * <p>WARNING: Do not make this class serializable! It could easily hide situations where
+ * unnecessary references leak into Spark closures.
+ */
+public abstract class TransformTranslator<
Review Comment:
you removed all streaming related classes so you don't need the `AbstractTranslationContext` anymore so you can move the all to this abstract class instead of an interface + methods in the context
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/Aggregators.java:
##########
@@ -0,0 +1,590 @@
+/*
+ * 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.batch;
+
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.collectionEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.encoderOf;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mapEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mutablePairEncoder;
+import static org.apache.beam.sdk.transforms.windowing.PaneInfo.NO_FIRING;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterators.peekingIterator;
+
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.function.BiFunction;
+import java.util.function.BinaryOperator;
+import java.util.function.Function;
+import javax.annotation.Nullable;
+import org.apache.beam.runners.spark.structuredstreaming.translation.utils.ScalaInterop.Fun1;
+import org.apache.beam.sdk.transforms.Combine.CombineFn;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.IntervalWindow;
+import org.apache.beam.sdk.transforms.windowing.Sessions;
+import org.apache.beam.sdk.transforms.windowing.TimestampCombiner;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Collections2;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableSet;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.PeekingIterator;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Sets;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.expressions.Aggregator;
+import org.apache.spark.util.MutablePair;
+import org.checkerframework.checker.nullness.qual.MonotonicNonNull;
+import org.checkerframework.checker.nullness.qual.NonNull;
+import org.checkerframework.checker.nullness.qual.PolyNull;
+import org.joda.time.Instant;
+
+public class Aggregators {
+
+ /**
+ * Creates simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT> Aggregator<InT, ?, ResT> value(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ return new ValueAggregator<>(fn, valueFn, accEnc, outEnc);
+ }
+
+ /**
+ * Creates windowed Spark {@link Aggregator} depending on the provided Beam {@link WindowFn}s.
+ *
+ * <p>Specialised implementations are provided for:
+ * <li>{@link Sessions}
+ * <li>Non merging window functions
+ * <li>Merging window functions
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT>
+ Aggregator<WindowedValue<InT>, ?, Collection<WindowedValue<ResT>>> windowedValue(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<BoundedWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ if (!windowing.needsMerge()) {
+ return new NonMergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ } else if (windowing.getWindowFn().getClass().equals(Sessions.class)) {
+ return new SessionsAggregator<>(fn, valueFn, windowing, (Encoder) windowEnc, accEnc, outEnc);
+ }
+ return new MergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ }
+
+ /**
+ * Simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class ValueAggregator<ValT, AccT, ResT, InT>
+ extends CombineFnAggregator<ValT, AccT, ResT, InT, AccT, ResT> {
+
+ public ValueAggregator(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ super(fn, valueFn, accEnc, outEnc);
+ }
+
+ @Override
+ public AccT zero() {
+ return emptyAcc();
+ }
+
+ @Override
+ public AccT reduce(AccT buff, InT in) {
+ return addToAcc(buff, value(in));
+ }
+
+ @Override
+ public AccT merge(AccT b1, AccT b2) {
+ return mergeAccs(b1, b2);
+ }
+
+ @Override
+ public ResT finish(AccT buff) {
+ return extract(buff);
+ }
+ }
+
+ /**
+ * Specialized windowed Spark {@link Aggregator} for Beam {@link WindowFn}s of type {@link
+ * Sessions}. The aggregator uses a {@link TreeMap} as buffer to maintain ordering of the {@link
+ * IntervalWindow}s and merge these more efficiently.
+ *
+ * <p>For efficiency, this aggregator re-implements {@link
+ * Sessions#mergeWindows(WindowFn.MergeContext)} to leverage the already sorted buffer.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class SessionsAggregator<ValT, AccT, ResT, InT>
+ extends WindowedAggregator<
+ ValT,
+ AccT,
+ ResT,
+ InT,
+ IntervalWindow,
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>>> {
+
+ SessionsAggregator(
+ CombineFn<ValT, AccT, ResT> combineFn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<IntervalWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ super(combineFn, valueFn, windowing, windowEnc, accEnc, outEnc, (Class) TreeMap.class);
+ checkArgument(windowing.getWindowFn().getClass().equals(Sessions.class));
+ }
+
+ @Override
+ public final TreeMap<IntervalWindow, MutablePair<Instant, AccT>> zero() {
+ return new TreeMap<>();
+ }
+
+ @Override
+ @SuppressWarnings("keyfor")
+ public TreeMap<IntervalWindow, MutablePair<Instant, AccT>> reduce(
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> buff, WindowedValue<InT> input) {
+ for (IntervalWindow window : (Collection<IntervalWindow>) input.getWindows()) {
+ @MonotonicNonNull MutablePair<Instant, AccT> acc = null;
+ @MonotonicNonNull IntervalWindow first = null, last = null;
+ // start with window before or equal to new window (if exists)
+ @Nullable Entry<IntervalWindow, MutablePair<Instant, AccT>> lower = buff.floorEntry(window);
+ if (lower != null && window.intersects(lower.getKey())) {
+ // if intersecting, init accumulator and extend window to span both
+ acc = lower.getValue();
+ window = window.span(lower.getKey());
+ first = last = lower.getKey();
+ }
+ // merge following windows in order while intersecting
+ for (Entry<IntervalWindow, MutablePair<Instant, AccT>> entry :
+ buff.tailMap(window, false).entrySet()) {
+ MutablePair<Instant, AccT> entryAcc = entry.getValue();
+ IntervalWindow entryWindow = entry.getKey();
+ if (window.intersects(entryWindow)) {
+ // extend window and merge accumulators
+ window = window.span(entryWindow);
+ acc = acc == null ? entryAcc : mergeAccs(window, acc, entryAcc);
+ if (first == null) {
Review Comment:
add
// there was no window before the input window intersecting it
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/Aggregators.java:
##########
@@ -0,0 +1,590 @@
+/*
+ * 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.batch;
+
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.collectionEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.encoderOf;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mapEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mutablePairEncoder;
+import static org.apache.beam.sdk.transforms.windowing.PaneInfo.NO_FIRING;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterators.peekingIterator;
+
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.function.BiFunction;
+import java.util.function.BinaryOperator;
+import java.util.function.Function;
+import javax.annotation.Nullable;
+import org.apache.beam.runners.spark.structuredstreaming.translation.utils.ScalaInterop.Fun1;
+import org.apache.beam.sdk.transforms.Combine.CombineFn;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.IntervalWindow;
+import org.apache.beam.sdk.transforms.windowing.Sessions;
+import org.apache.beam.sdk.transforms.windowing.TimestampCombiner;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Collections2;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableSet;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.PeekingIterator;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Sets;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.expressions.Aggregator;
+import org.apache.spark.util.MutablePair;
+import org.checkerframework.checker.nullness.qual.MonotonicNonNull;
+import org.checkerframework.checker.nullness.qual.NonNull;
+import org.checkerframework.checker.nullness.qual.PolyNull;
+import org.joda.time.Instant;
+
+public class Aggregators {
+
+ /**
+ * Creates simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT> Aggregator<InT, ?, ResT> value(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ return new ValueAggregator<>(fn, valueFn, accEnc, outEnc);
+ }
+
+ /**
+ * Creates windowed Spark {@link Aggregator} depending on the provided Beam {@link WindowFn}s.
+ *
+ * <p>Specialised implementations are provided for:
+ * <li>{@link Sessions}
+ * <li>Non merging window functions
+ * <li>Merging window functions
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT>
+ Aggregator<WindowedValue<InT>, ?, Collection<WindowedValue<ResT>>> windowedValue(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<BoundedWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ if (!windowing.needsMerge()) {
+ return new NonMergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ } else if (windowing.getWindowFn().getClass().equals(Sessions.class)) {
+ return new SessionsAggregator<>(fn, valueFn, windowing, (Encoder) windowEnc, accEnc, outEnc);
+ }
+ return new MergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ }
+
+ /**
+ * Simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class ValueAggregator<ValT, AccT, ResT, InT>
+ extends CombineFnAggregator<ValT, AccT, ResT, InT, AccT, ResT> {
+
+ public ValueAggregator(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ super(fn, valueFn, accEnc, outEnc);
+ }
+
+ @Override
+ public AccT zero() {
+ return emptyAcc();
+ }
+
+ @Override
+ public AccT reduce(AccT buff, InT in) {
+ return addToAcc(buff, value(in));
+ }
+
+ @Override
+ public AccT merge(AccT b1, AccT b2) {
+ return mergeAccs(b1, b2);
+ }
+
+ @Override
+ public ResT finish(AccT buff) {
+ return extract(buff);
+ }
+ }
+
+ /**
+ * Specialized windowed Spark {@link Aggregator} for Beam {@link WindowFn}s of type {@link
+ * Sessions}. The aggregator uses a {@link TreeMap} as buffer to maintain ordering of the {@link
+ * IntervalWindow}s and merge these more efficiently.
+ *
+ * <p>For efficiency, this aggregator re-implements {@link
+ * Sessions#mergeWindows(WindowFn.MergeContext)} to leverage the already sorted buffer.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class SessionsAggregator<ValT, AccT, ResT, InT>
+ extends WindowedAggregator<
+ ValT,
+ AccT,
+ ResT,
+ InT,
+ IntervalWindow,
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>>> {
Review Comment:
nice that you use a TreeMap for log(n) operations on the map ! And also very convenient for window ranges and avoiding having to sort the windows. Clever !
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/Aggregators.java:
##########
@@ -0,0 +1,590 @@
+/*
+ * 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.batch;
+
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.collectionEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.encoderOf;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mapEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mutablePairEncoder;
+import static org.apache.beam.sdk.transforms.windowing.PaneInfo.NO_FIRING;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterators.peekingIterator;
+
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.function.BiFunction;
+import java.util.function.BinaryOperator;
+import java.util.function.Function;
+import javax.annotation.Nullable;
+import org.apache.beam.runners.spark.structuredstreaming.translation.utils.ScalaInterop.Fun1;
+import org.apache.beam.sdk.transforms.Combine.CombineFn;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.IntervalWindow;
+import org.apache.beam.sdk.transforms.windowing.Sessions;
+import org.apache.beam.sdk.transforms.windowing.TimestampCombiner;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Collections2;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableSet;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.PeekingIterator;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Sets;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.expressions.Aggregator;
+import org.apache.spark.util.MutablePair;
+import org.checkerframework.checker.nullness.qual.MonotonicNonNull;
+import org.checkerframework.checker.nullness.qual.NonNull;
+import org.checkerframework.checker.nullness.qual.PolyNull;
+import org.joda.time.Instant;
+
+public class Aggregators {
+
+ /**
+ * Creates simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT> Aggregator<InT, ?, ResT> value(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ return new ValueAggregator<>(fn, valueFn, accEnc, outEnc);
+ }
+
+ /**
+ * Creates windowed Spark {@link Aggregator} depending on the provided Beam {@link WindowFn}s.
+ *
+ * <p>Specialised implementations are provided for:
+ * <li>{@link Sessions}
+ * <li>Non merging window functions
+ * <li>Merging window functions
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT>
+ Aggregator<WindowedValue<InT>, ?, Collection<WindowedValue<ResT>>> windowedValue(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<BoundedWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ if (!windowing.needsMerge()) {
+ return new NonMergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ } else if (windowing.getWindowFn().getClass().equals(Sessions.class)) {
+ return new SessionsAggregator<>(fn, valueFn, windowing, (Encoder) windowEnc, accEnc, outEnc);
+ }
+ return new MergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ }
+
+ /**
+ * Simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class ValueAggregator<ValT, AccT, ResT, InT>
+ extends CombineFnAggregator<ValT, AccT, ResT, InT, AccT, ResT> {
+
+ public ValueAggregator(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ super(fn, valueFn, accEnc, outEnc);
+ }
+
+ @Override
+ public AccT zero() {
+ return emptyAcc();
+ }
+
+ @Override
+ public AccT reduce(AccT buff, InT in) {
+ return addToAcc(buff, value(in));
+ }
+
+ @Override
+ public AccT merge(AccT b1, AccT b2) {
+ return mergeAccs(b1, b2);
+ }
+
+ @Override
+ public ResT finish(AccT buff) {
+ return extract(buff);
+ }
+ }
+
+ /**
+ * Specialized windowed Spark {@link Aggregator} for Beam {@link WindowFn}s of type {@link
+ * Sessions}. The aggregator uses a {@link TreeMap} as buffer to maintain ordering of the {@link
+ * IntervalWindow}s and merge these more efficiently.
+ *
+ * <p>For efficiency, this aggregator re-implements {@link
+ * Sessions#mergeWindows(WindowFn.MergeContext)} to leverage the already sorted buffer.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class SessionsAggregator<ValT, AccT, ResT, InT>
+ extends WindowedAggregator<
+ ValT,
+ AccT,
+ ResT,
+ InT,
+ IntervalWindow,
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>>> {
+
+ SessionsAggregator(
+ CombineFn<ValT, AccT, ResT> combineFn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<IntervalWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ super(combineFn, valueFn, windowing, windowEnc, accEnc, outEnc, (Class) TreeMap.class);
+ checkArgument(windowing.getWindowFn().getClass().equals(Sessions.class));
+ }
+
+ @Override
+ public final TreeMap<IntervalWindow, MutablePair<Instant, AccT>> zero() {
+ return new TreeMap<>();
+ }
+
+ @Override
+ @SuppressWarnings("keyfor")
+ public TreeMap<IntervalWindow, MutablePair<Instant, AccT>> reduce(
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> buff, WindowedValue<InT> input) {
+ for (IntervalWindow window : (Collection<IntervalWindow>) input.getWindows()) {
+ @MonotonicNonNull MutablePair<Instant, AccT> acc = null;
+ @MonotonicNonNull IntervalWindow first = null, last = null;
+ // start with window before or equal to new window (if exists)
+ @Nullable Entry<IntervalWindow, MutablePair<Instant, AccT>> lower = buff.floorEntry(window);
+ if (lower != null && window.intersects(lower.getKey())) {
+ // if intersecting, init accumulator and extend window to span both
+ acc = lower.getValue();
+ window = window.span(lower.getKey());
+ first = last = lower.getKey();
+ }
+ // merge following windows in order while intersecting
+ for (Entry<IntervalWindow, MutablePair<Instant, AccT>> entry :
+ buff.tailMap(window, false).entrySet()) {
+ MutablePair<Instant, AccT> entryAcc = entry.getValue();
+ IntervalWindow entryWindow = entry.getKey();
+ if (window.intersects(entryWindow)) {
+ // extend window and merge accumulators
+ window = window.span(entryWindow);
+ acc = acc == null ? entryAcc : mergeAccs(window, acc, entryAcc);
+ if (first == null) {
+ first = last = entryWindow;
+ } else {
+ last = entryWindow;
+ }
+ } else {
+ break; // stop, later windows won't intersect either
+ }
+ }
+ if (first != null && last != null) {
+ // remove entire merged subset from first to last
Review Comment:
reword: remove entire subset from first to last because me merged it into acc
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/Aggregators.java:
##########
@@ -0,0 +1,590 @@
+/*
+ * 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.batch;
+
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.collectionEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.encoderOf;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mapEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mutablePairEncoder;
+import static org.apache.beam.sdk.transforms.windowing.PaneInfo.NO_FIRING;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterators.peekingIterator;
+
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.function.BiFunction;
+import java.util.function.BinaryOperator;
+import java.util.function.Function;
+import javax.annotation.Nullable;
+import org.apache.beam.runners.spark.structuredstreaming.translation.utils.ScalaInterop.Fun1;
+import org.apache.beam.sdk.transforms.Combine.CombineFn;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.IntervalWindow;
+import org.apache.beam.sdk.transforms.windowing.Sessions;
+import org.apache.beam.sdk.transforms.windowing.TimestampCombiner;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Collections2;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableSet;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.PeekingIterator;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Sets;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.expressions.Aggregator;
+import org.apache.spark.util.MutablePair;
+import org.checkerframework.checker.nullness.qual.MonotonicNonNull;
+import org.checkerframework.checker.nullness.qual.NonNull;
+import org.checkerframework.checker.nullness.qual.PolyNull;
+import org.joda.time.Instant;
+
+public class Aggregators {
+
+ /**
+ * Creates simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT> Aggregator<InT, ?, ResT> value(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ return new ValueAggregator<>(fn, valueFn, accEnc, outEnc);
+ }
+
+ /**
+ * Creates windowed Spark {@link Aggregator} depending on the provided Beam {@link WindowFn}s.
+ *
+ * <p>Specialised implementations are provided for:
+ * <li>{@link Sessions}
+ * <li>Non merging window functions
+ * <li>Merging window functions
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT>
+ Aggregator<WindowedValue<InT>, ?, Collection<WindowedValue<ResT>>> windowedValue(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<BoundedWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ if (!windowing.needsMerge()) {
+ return new NonMergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ } else if (windowing.getWindowFn().getClass().equals(Sessions.class)) {
+ return new SessionsAggregator<>(fn, valueFn, windowing, (Encoder) windowEnc, accEnc, outEnc);
+ }
+ return new MergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ }
+
+ /**
+ * Simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class ValueAggregator<ValT, AccT, ResT, InT>
+ extends CombineFnAggregator<ValT, AccT, ResT, InT, AccT, ResT> {
+
+ public ValueAggregator(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ super(fn, valueFn, accEnc, outEnc);
+ }
+
+ @Override
+ public AccT zero() {
+ return emptyAcc();
+ }
+
+ @Override
+ public AccT reduce(AccT buff, InT in) {
+ return addToAcc(buff, value(in));
+ }
+
+ @Override
+ public AccT merge(AccT b1, AccT b2) {
+ return mergeAccs(b1, b2);
+ }
+
+ @Override
+ public ResT finish(AccT buff) {
+ return extract(buff);
+ }
+ }
+
+ /**
+ * Specialized windowed Spark {@link Aggregator} for Beam {@link WindowFn}s of type {@link
+ * Sessions}. The aggregator uses a {@link TreeMap} as buffer to maintain ordering of the {@link
+ * IntervalWindow}s and merge these more efficiently.
+ *
+ * <p>For efficiency, this aggregator re-implements {@link
+ * Sessions#mergeWindows(WindowFn.MergeContext)} to leverage the already sorted buffer.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class SessionsAggregator<ValT, AccT, ResT, InT>
+ extends WindowedAggregator<
+ ValT,
+ AccT,
+ ResT,
+ InT,
+ IntervalWindow,
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>>> {
+
+ SessionsAggregator(
+ CombineFn<ValT, AccT, ResT> combineFn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<IntervalWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ super(combineFn, valueFn, windowing, windowEnc, accEnc, outEnc, (Class) TreeMap.class);
+ checkArgument(windowing.getWindowFn().getClass().equals(Sessions.class));
+ }
+
+ @Override
+ public final TreeMap<IntervalWindow, MutablePair<Instant, AccT>> zero() {
+ return new TreeMap<>();
+ }
+
+ @Override
+ @SuppressWarnings("keyfor")
+ public TreeMap<IntervalWindow, MutablePair<Instant, AccT>> reduce(
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> buff, WindowedValue<InT> input) {
+ for (IntervalWindow window : (Collection<IntervalWindow>) input.getWindows()) {
+ @MonotonicNonNull MutablePair<Instant, AccT> acc = null;
+ @MonotonicNonNull IntervalWindow first = null, last = null;
+ // start with window before or equal to new window (if exists)
+ @Nullable Entry<IntervalWindow, MutablePair<Instant, AccT>> lower = buff.floorEntry(window);
+ if (lower != null && window.intersects(lower.getKey())) {
+ // if intersecting, init accumulator and extend window to span both
+ acc = lower.getValue();
+ window = window.span(lower.getKey());
+ first = last = lower.getKey();
+ }
+ // merge following windows in order while intersecting
Review Comment:
sed s/while intersecting/if they intersect/g
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/Aggregators.java:
##########
@@ -0,0 +1,590 @@
+/*
+ * 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.batch;
+
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.collectionEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.encoderOf;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mapEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mutablePairEncoder;
+import static org.apache.beam.sdk.transforms.windowing.PaneInfo.NO_FIRING;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterators.peekingIterator;
+
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.function.BiFunction;
+import java.util.function.BinaryOperator;
+import java.util.function.Function;
+import javax.annotation.Nullable;
+import org.apache.beam.runners.spark.structuredstreaming.translation.utils.ScalaInterop.Fun1;
+import org.apache.beam.sdk.transforms.Combine.CombineFn;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.IntervalWindow;
+import org.apache.beam.sdk.transforms.windowing.Sessions;
+import org.apache.beam.sdk.transforms.windowing.TimestampCombiner;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Collections2;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableSet;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.PeekingIterator;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Sets;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.expressions.Aggregator;
+import org.apache.spark.util.MutablePair;
+import org.checkerframework.checker.nullness.qual.MonotonicNonNull;
+import org.checkerframework.checker.nullness.qual.NonNull;
+import org.checkerframework.checker.nullness.qual.PolyNull;
+import org.joda.time.Instant;
+
+public class Aggregators {
+
+ /**
+ * Creates simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT> Aggregator<InT, ?, ResT> value(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ return new ValueAggregator<>(fn, valueFn, accEnc, outEnc);
+ }
+
+ /**
+ * Creates windowed Spark {@link Aggregator} depending on the provided Beam {@link WindowFn}s.
+ *
+ * <p>Specialised implementations are provided for:
+ * <li>{@link Sessions}
+ * <li>Non merging window functions
+ * <li>Merging window functions
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT>
+ Aggregator<WindowedValue<InT>, ?, Collection<WindowedValue<ResT>>> windowedValue(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<BoundedWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ if (!windowing.needsMerge()) {
+ return new NonMergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ } else if (windowing.getWindowFn().getClass().equals(Sessions.class)) {
+ return new SessionsAggregator<>(fn, valueFn, windowing, (Encoder) windowEnc, accEnc, outEnc);
+ }
+ return new MergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ }
+
+ /**
+ * Simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class ValueAggregator<ValT, AccT, ResT, InT>
+ extends CombineFnAggregator<ValT, AccT, ResT, InT, AccT, ResT> {
+
+ public ValueAggregator(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ super(fn, valueFn, accEnc, outEnc);
+ }
+
+ @Override
+ public AccT zero() {
+ return emptyAcc();
+ }
+
+ @Override
+ public AccT reduce(AccT buff, InT in) {
+ return addToAcc(buff, value(in));
+ }
+
+ @Override
+ public AccT merge(AccT b1, AccT b2) {
+ return mergeAccs(b1, b2);
+ }
+
+ @Override
+ public ResT finish(AccT buff) {
+ return extract(buff);
+ }
+ }
+
+ /**
+ * Specialized windowed Spark {@link Aggregator} for Beam {@link WindowFn}s of type {@link
+ * Sessions}. The aggregator uses a {@link TreeMap} as buffer to maintain ordering of the {@link
+ * IntervalWindow}s and merge these more efficiently.
+ *
+ * <p>For efficiency, this aggregator re-implements {@link
+ * Sessions#mergeWindows(WindowFn.MergeContext)} to leverage the already sorted buffer.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class SessionsAggregator<ValT, AccT, ResT, InT>
+ extends WindowedAggregator<
+ ValT,
+ AccT,
+ ResT,
+ InT,
+ IntervalWindow,
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>>> {
+
+ SessionsAggregator(
+ CombineFn<ValT, AccT, ResT> combineFn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<IntervalWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ super(combineFn, valueFn, windowing, windowEnc, accEnc, outEnc, (Class) TreeMap.class);
+ checkArgument(windowing.getWindowFn().getClass().equals(Sessions.class));
+ }
+
+ @Override
+ public final TreeMap<IntervalWindow, MutablePair<Instant, AccT>> zero() {
+ return new TreeMap<>();
+ }
+
+ @Override
+ @SuppressWarnings("keyfor")
+ public TreeMap<IntervalWindow, MutablePair<Instant, AccT>> reduce(
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> buff, WindowedValue<InT> input) {
+ for (IntervalWindow window : (Collection<IntervalWindow>) input.getWindows()) {
+ @MonotonicNonNull MutablePair<Instant, AccT> acc = null;
+ @MonotonicNonNull IntervalWindow first = null, last = null;
+ // start with window before or equal to new window (if exists)
+ @Nullable Entry<IntervalWindow, MutablePair<Instant, AccT>> lower = buff.floorEntry(window);
+ if (lower != null && window.intersects(lower.getKey())) {
+ // if intersecting, init accumulator and extend window to span both
+ acc = lower.getValue();
+ window = window.span(lower.getKey());
+ first = last = lower.getKey();
+ }
+ // merge following windows in order while intersecting
+ for (Entry<IntervalWindow, MutablePair<Instant, AccT>> entry :
+ buff.tailMap(window, false).entrySet()) {
+ MutablePair<Instant, AccT> entryAcc = entry.getValue();
+ IntervalWindow entryWindow = entry.getKey();
+ if (window.intersects(entryWindow)) {
+ // extend window and merge accumulators
+ window = window.span(entryWindow);
+ acc = acc == null ? entryAcc : mergeAccs(window, acc, entryAcc);
+ if (first == null) {
+ first = last = entryWindow;
+ } else {
+ last = entryWindow;
+ }
+ } else {
+ break; // stop, later windows won't intersect either
+ }
+ }
+ if (first != null && last != null) {
+ // remove entire merged subset from first to last
+ buff.navigableKeySet().subSet(first, true, last, true).clear();
+ }
+ // add input and get accumulator for new (potentially merged) window
+ buff.put(window, addToAcc(window, acc, value(input), input.getTimestamp()));
+ }
+ return buff;
+ }
+
+ @Override
+ public TreeMap<IntervalWindow, MutablePair<Instant, AccT>> merge(
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> b1,
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> b2) {
+ if (b1.isEmpty()) {
+ return b2;
+ } else if (b2.isEmpty()) {
+ return b1;
+ }
+ // Init new tree map to merge both buffers
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> res = zero();
+ PeekingIterator<Entry<IntervalWindow, MutablePair<Instant, AccT>>> it1 =
+ peekingIterator(b1.entrySet().iterator());
+ PeekingIterator<Entry<IntervalWindow, MutablePair<Instant, AccT>>> it2 =
+ peekingIterator(b2.entrySet().iterator());
+
+ @Nullable MutablePair<Instant, AccT> acc = null;
Review Comment:
`@MonotonicNonNull`?
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/Aggregators.java:
##########
@@ -0,0 +1,590 @@
+/*
+ * 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.batch;
+
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.collectionEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.encoderOf;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mapEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mutablePairEncoder;
+import static org.apache.beam.sdk.transforms.windowing.PaneInfo.NO_FIRING;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterators.peekingIterator;
+
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.function.BiFunction;
+import java.util.function.BinaryOperator;
+import java.util.function.Function;
+import javax.annotation.Nullable;
+import org.apache.beam.runners.spark.structuredstreaming.translation.utils.ScalaInterop.Fun1;
+import org.apache.beam.sdk.transforms.Combine.CombineFn;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.IntervalWindow;
+import org.apache.beam.sdk.transforms.windowing.Sessions;
+import org.apache.beam.sdk.transforms.windowing.TimestampCombiner;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Collections2;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableSet;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.PeekingIterator;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Sets;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.expressions.Aggregator;
+import org.apache.spark.util.MutablePair;
+import org.checkerframework.checker.nullness.qual.MonotonicNonNull;
+import org.checkerframework.checker.nullness.qual.NonNull;
+import org.checkerframework.checker.nullness.qual.PolyNull;
+import org.joda.time.Instant;
+
+public class Aggregators {
+
+ /**
+ * Creates simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT> Aggregator<InT, ?, ResT> value(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ return new ValueAggregator<>(fn, valueFn, accEnc, outEnc);
+ }
+
+ /**
+ * Creates windowed Spark {@link Aggregator} depending on the provided Beam {@link WindowFn}s.
+ *
+ * <p>Specialised implementations are provided for:
+ * <li>{@link Sessions}
+ * <li>Non merging window functions
+ * <li>Merging window functions
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT>
+ Aggregator<WindowedValue<InT>, ?, Collection<WindowedValue<ResT>>> windowedValue(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<BoundedWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ if (!windowing.needsMerge()) {
+ return new NonMergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ } else if (windowing.getWindowFn().getClass().equals(Sessions.class)) {
+ return new SessionsAggregator<>(fn, valueFn, windowing, (Encoder) windowEnc, accEnc, outEnc);
+ }
+ return new MergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ }
+
+ /**
+ * Simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class ValueAggregator<ValT, AccT, ResT, InT>
+ extends CombineFnAggregator<ValT, AccT, ResT, InT, AccT, ResT> {
+
+ public ValueAggregator(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ super(fn, valueFn, accEnc, outEnc);
+ }
+
+ @Override
+ public AccT zero() {
+ return emptyAcc();
+ }
+
+ @Override
+ public AccT reduce(AccT buff, InT in) {
+ return addToAcc(buff, value(in));
+ }
+
+ @Override
+ public AccT merge(AccT b1, AccT b2) {
+ return mergeAccs(b1, b2);
+ }
+
+ @Override
+ public ResT finish(AccT buff) {
+ return extract(buff);
+ }
+ }
+
+ /**
+ * Specialized windowed Spark {@link Aggregator} for Beam {@link WindowFn}s of type {@link
+ * Sessions}. The aggregator uses a {@link TreeMap} as buffer to maintain ordering of the {@link
+ * IntervalWindow}s and merge these more efficiently.
+ *
+ * <p>For efficiency, this aggregator re-implements {@link
+ * Sessions#mergeWindows(WindowFn.MergeContext)} to leverage the already sorted buffer.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class SessionsAggregator<ValT, AccT, ResT, InT>
+ extends WindowedAggregator<
+ ValT,
+ AccT,
+ ResT,
+ InT,
+ IntervalWindow,
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>>> {
+
+ SessionsAggregator(
+ CombineFn<ValT, AccT, ResT> combineFn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<IntervalWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ super(combineFn, valueFn, windowing, windowEnc, accEnc, outEnc, (Class) TreeMap.class);
+ checkArgument(windowing.getWindowFn().getClass().equals(Sessions.class));
+ }
+
+ @Override
+ public final TreeMap<IntervalWindow, MutablePair<Instant, AccT>> zero() {
+ return new TreeMap<>();
+ }
+
+ @Override
+ @SuppressWarnings("keyfor")
+ public TreeMap<IntervalWindow, MutablePair<Instant, AccT>> reduce(
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> buff, WindowedValue<InT> input) {
+ for (IntervalWindow window : (Collection<IntervalWindow>) input.getWindows()) {
+ @MonotonicNonNull MutablePair<Instant, AccT> acc = null;
+ @MonotonicNonNull IntervalWindow first = null, last = null;
+ // start with window before or equal to new window (if exists)
+ @Nullable Entry<IntervalWindow, MutablePair<Instant, AccT>> lower = buff.floorEntry(window);
+ if (lower != null && window.intersects(lower.getKey())) {
+ // if intersecting, init accumulator and extend window to span both
+ acc = lower.getValue();
+ window = window.span(lower.getKey());
+ first = last = lower.getKey();
+ }
+ // merge following windows in order while intersecting
+ for (Entry<IntervalWindow, MutablePair<Instant, AccT>> entry :
+ buff.tailMap(window, false).entrySet()) {
+ MutablePair<Instant, AccT> entryAcc = entry.getValue();
+ IntervalWindow entryWindow = entry.getKey();
+ if (window.intersects(entryWindow)) {
+ // extend window and merge accumulators
+ window = window.span(entryWindow);
+ acc = acc == null ? entryAcc : mergeAccs(window, acc, entryAcc);
+ if (first == null) {
+ first = last = entryWindow;
+ } else {
+ last = entryWindow;
+ }
+ } else {
+ break; // stop, later windows won't intersect either
+ }
+ }
+ if (first != null && last != null) {
+ // remove entire merged subset from first to last
+ buff.navigableKeySet().subSet(first, true, last, true).clear();
+ }
+ // add input and get accumulator for new (potentially merged) window
+ buff.put(window, addToAcc(window, acc, value(input), input.getTimestamp()));
+ }
+ return buff;
+ }
+
+ @Override
+ public TreeMap<IntervalWindow, MutablePair<Instant, AccT>> merge(
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> b1,
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> b2) {
+ if (b1.isEmpty()) {
+ return b2;
+ } else if (b2.isEmpty()) {
+ return b1;
+ }
+ // Init new tree map to merge both buffers
+ TreeMap<IntervalWindow, MutablePair<Instant, AccT>> res = zero();
+ PeekingIterator<Entry<IntervalWindow, MutablePair<Instant, AccT>>> it1 =
+ peekingIterator(b1.entrySet().iterator());
+ PeekingIterator<Entry<IntervalWindow, MutablePair<Instant, AccT>>> it2 =
+ peekingIterator(b2.entrySet().iterator());
+
+ @Nullable MutablePair<Instant, AccT> acc = null;
+ @Nullable IntervalWindow window = null;
Review Comment:
`@MonotonicNonNull`?
##########
runners/spark/3/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/Aggregators.java:
##########
@@ -0,0 +1,590 @@
+/*
+ * 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.batch;
+
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.collectionEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.encoderOf;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mapEncoder;
+import static org.apache.beam.runners.spark.structuredstreaming.translation.helpers.EncoderHelpers.mutablePairEncoder;
+import static org.apache.beam.sdk.transforms.windowing.PaneInfo.NO_FIRING;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.Preconditions.checkArgument;
+import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Iterators.peekingIterator;
+
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.function.BiFunction;
+import java.util.function.BinaryOperator;
+import java.util.function.Function;
+import javax.annotation.Nullable;
+import org.apache.beam.runners.spark.structuredstreaming.translation.utils.ScalaInterop.Fun1;
+import org.apache.beam.sdk.transforms.Combine.CombineFn;
+import org.apache.beam.sdk.transforms.windowing.BoundedWindow;
+import org.apache.beam.sdk.transforms.windowing.IntervalWindow;
+import org.apache.beam.sdk.transforms.windowing.Sessions;
+import org.apache.beam.sdk.transforms.windowing.TimestampCombiner;
+import org.apache.beam.sdk.transforms.windowing.WindowFn;
+import org.apache.beam.sdk.util.WindowedValue;
+import org.apache.beam.sdk.values.WindowingStrategy;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Collections2;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableList;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableSet;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.PeekingIterator;
+import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Sets;
+import org.apache.spark.sql.Encoder;
+import org.apache.spark.sql.expressions.Aggregator;
+import org.apache.spark.util.MutablePair;
+import org.checkerframework.checker.nullness.qual.MonotonicNonNull;
+import org.checkerframework.checker.nullness.qual.NonNull;
+import org.checkerframework.checker.nullness.qual.PolyNull;
+import org.joda.time.Instant;
+
+public class Aggregators {
+
+ /**
+ * Creates simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT> Aggregator<InT, ?, ResT> value(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ return new ValueAggregator<>(fn, valueFn, accEnc, outEnc);
+ }
+
+ /**
+ * Creates windowed Spark {@link Aggregator} depending on the provided Beam {@link WindowFn}s.
+ *
+ * <p>Specialised implementations are provided for:
+ * <li>{@link Sessions}
+ * <li>Non merging window functions
+ * <li>Merging window functions
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ public static <ValT, AccT, ResT, InT>
+ Aggregator<WindowedValue<InT>, ?, Collection<WindowedValue<ResT>>> windowedValue(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<WindowedValue<InT>, ValT> valueFn,
+ WindowingStrategy<?, ?> windowing,
+ Encoder<BoundedWindow> windowEnc,
+ Encoder<AccT> accEnc,
+ Encoder<WindowedValue<ResT>> outEnc) {
+ if (!windowing.needsMerge()) {
+ return new NonMergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ } else if (windowing.getWindowFn().getClass().equals(Sessions.class)) {
+ return new SessionsAggregator<>(fn, valueFn, windowing, (Encoder) windowEnc, accEnc, outEnc);
+ }
+ return new MergingWindowedAggregator<>(fn, valueFn, windowing, windowEnc, accEnc, outEnc);
+ }
+
+ /**
+ * Simple value {@link Aggregator} that is not window aware.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class ValueAggregator<ValT, AccT, ResT, InT>
+ extends CombineFnAggregator<ValT, AccT, ResT, InT, AccT, ResT> {
+
+ public ValueAggregator(
+ CombineFn<ValT, AccT, ResT> fn,
+ Fun1<InT, ValT> valueFn,
+ Encoder<AccT> accEnc,
+ Encoder<ResT> outEnc) {
+ super(fn, valueFn, accEnc, outEnc);
+ }
+
+ @Override
+ public AccT zero() {
+ return emptyAcc();
+ }
+
+ @Override
+ public AccT reduce(AccT buff, InT in) {
+ return addToAcc(buff, value(in));
+ }
+
+ @Override
+ public AccT merge(AccT b1, AccT b2) {
+ return mergeAccs(b1, b2);
+ }
+
+ @Override
+ public ResT finish(AccT buff) {
+ return extract(buff);
+ }
+ }
+
+ /**
+ * Specialized windowed Spark {@link Aggregator} for Beam {@link WindowFn}s of type {@link
+ * Sessions}. The aggregator uses a {@link TreeMap} as buffer to maintain ordering of the {@link
+ * IntervalWindow}s and merge these more efficiently.
+ *
+ * <p>For efficiency, this aggregator re-implements {@link
+ * Sessions#mergeWindows(WindowFn.MergeContext)} to leverage the already sorted buffer.
+ *
+ * @param <ValT> {@link CombineFn} input type
+ * @param <AccT> {@link CombineFn} accumulator type
+ * @param <ResT> {@link CombineFn} / {@link Aggregator} result type
+ * @param <InT> {@link Aggregator} input type
+ */
+ private static class SessionsAggregator<ValT, AccT, ResT, InT>
Review Comment:
SessionsAggregator LGTM you managed to write clean code on a complex use case. Thanks !
And the VR tests pass on session windows, so good work !
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