| /* |
| * 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.sdk.transforms; |
| |
| import java.util.concurrent.ThreadLocalRandom; |
| import org.apache.beam.sdk.annotations.Experimental; |
| import org.apache.beam.sdk.annotations.Internal; |
| import org.apache.beam.sdk.transforms.windowing.BoundedWindow; |
| import org.apache.beam.sdk.transforms.windowing.ReshuffleTrigger; |
| import org.apache.beam.sdk.transforms.windowing.TimestampCombiner; |
| import org.apache.beam.sdk.transforms.windowing.Window; |
| import org.apache.beam.sdk.util.IdentityWindowFn; |
| import org.apache.beam.sdk.values.KV; |
| import org.apache.beam.sdk.values.PCollection; |
| import org.apache.beam.sdk.values.TimestampedValue; |
| import org.apache.beam.sdk.values.WindowingStrategy; |
| import org.joda.time.Duration; |
| |
| /** |
| * <b>For internal use only; no backwards compatibility guarantees.</b> |
| * |
| * <p>A {@link PTransform} that returns a {@link PCollection} equivalent to its input but |
| * operationally provides some of the side effects of a {@link GroupByKey}, in particular preventing |
| * fusion of the surrounding transforms, checkpointing and deduplication by id. |
| * |
| * <p>Performs a {@link GroupByKey} so that the data is key-partitioned. Configures the {@link |
| * WindowingStrategy} so that no data is dropped, but doesn't affect the need for the user to |
| * specify allowed lateness and accumulation mode before a user-inserted GroupByKey. |
| * |
| * @param <K> The type of key being reshuffled on. |
| * @param <V> The type of value being reshuffled. |
| * @deprecated this transform's intended side effects are not portable; it will likely be removed |
| */ |
| @Internal |
| @Deprecated |
| public class Reshuffle<K, V> extends PTransform<PCollection<KV<K, V>>, PCollection<KV<K, V>>> { |
| |
| private Reshuffle() {} |
| |
| public static <K, V> Reshuffle<K, V> of() { |
| return new Reshuffle<>(); |
| } |
| |
| /** |
| * Encapsulates the sequence "pair input with unique key, apply {@link Reshuffle#of}, drop the |
| * key" commonly used to break fusion. |
| */ |
| @Experimental |
| public static <T> ViaRandomKey<T> viaRandomKey() { |
| return new ViaRandomKey<>(); |
| } |
| |
| @Override |
| public PCollection<KV<K, V>> expand(PCollection<KV<K, V>> input) { |
| WindowingStrategy<?, ?> originalStrategy = input.getWindowingStrategy(); |
| // If the input has already had its windows merged, then the GBK that performed the merge |
| // will have set originalStrategy.getWindowFn() to InvalidWindows, causing the GBK contained |
| // here to fail. Instead, we install a valid WindowFn that leaves all windows unchanged. |
| // The TimestampCombiner is set to ensure the GroupByKey does not shift elements forwards in |
| // time. |
| // Because this outputs as fast as possible, this should not hold the watermark. |
| Window<KV<K, V>> rewindow = |
| Window.<KV<K, V>>into(new IdentityWindowFn<>(originalStrategy.getWindowFn().windowCoder())) |
| .triggering(new ReshuffleTrigger<>()) |
| .discardingFiredPanes() |
| .withTimestampCombiner(TimestampCombiner.EARLIEST) |
| .withAllowedLateness(Duration.millis(BoundedWindow.TIMESTAMP_MAX_VALUE.getMillis())); |
| |
| return input |
| .apply(rewindow) |
| .apply("ReifyOriginalTimestamps", Reify.timestampsInValue()) |
| .apply(GroupByKey.create()) |
| // Set the windowing strategy directly, so that it doesn't get counted as the user having |
| // set allowed lateness. |
| .setWindowingStrategyInternal(originalStrategy) |
| .apply( |
| "ExpandIterable", |
| ParDo.of( |
| new DoFn<KV<K, Iterable<TimestampedValue<V>>>, KV<K, TimestampedValue<V>>>() { |
| @ProcessElement |
| public void processElement( |
| @Element KV<K, Iterable<TimestampedValue<V>>> element, |
| OutputReceiver<KV<K, TimestampedValue<V>>> r) { |
| K key = element.getKey(); |
| for (TimestampedValue<V> value : element.getValue()) { |
| r.output(KV.of(key, value)); |
| } |
| } |
| })) |
| .apply("RestoreOriginalTimestamps", ReifyTimestamps.extractFromValues()); |
| } |
| |
| /** Implementation of {@link #viaRandomKey()}. */ |
| public static class ViaRandomKey<T> extends PTransform<PCollection<T>, PCollection<T>> { |
| private ViaRandomKey() {} |
| |
| @Override |
| public PCollection<T> expand(PCollection<T> input) { |
| return input |
| .apply("Pair with random key", ParDo.of(new AssignShardFn<>())) |
| .apply(Reshuffle.of()) |
| .apply(Values.create()); |
| } |
| |
| private static class AssignShardFn<T> extends DoFn<T, KV<Integer, T>> { |
| private int shard; |
| |
| @Setup |
| public void setup() { |
| shard = ThreadLocalRandom.current().nextInt(); |
| } |
| |
| @ProcessElement |
| public void processElement(@Element T element, OutputReceiver<KV<Integer, T>> r) { |
| ++shard; |
| // Smear the shard into something more random-looking, to avoid issues |
| // with runners that don't properly hash the key being shuffled, but rely |
| // on it being random-looking. E.g. Spark takes the Java hashCode() of keys, |
| // which for Integer is a no-op and it is an issue: |
| // http://hydronitrogen.com/poor-hash-partitioning-of-timestamps-integers-and-longs-in- |
| // spark.html |
| // This hashing strategy is copied from |
| // org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.Hashing.smear(). |
| int hashOfShard = 0x1b873593 * Integer.rotateLeft(shard * 0xcc9e2d51, 15); |
| r.output(KV.of(hashOfShard, element)); |
| } |
| } |
| } |
| } |