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Dynamically choose number of shards in the InProcessPipelineRunner (a…
…pache#400) * Add Additional Exists check to FileIOChannelFactory#create This ensures that if the folder did not exist when first checked, but did by the time mkdirs was executed (and thus mkdirs returned false) the create will not fail. * Dynamically choose number of shards in the InProcessPipelineRunner Add a Write Override Factory that limits the number of shards if unspecified. This ensures that we will not write an output file per-key due to bundling. Do so by obtaining a count of the elements and obtaining the number of shards based on the number of outputs.
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...c/main/java/com/google/cloud/dataflow/sdk/runners/inprocess/WriteWithShardingFactory.java
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| /* | ||
| * Copyright (C) 2016 Google Inc. | ||
| * | ||
| * Licensed 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 com.google.cloud.dataflow.sdk.runners.inprocess; | ||
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| import static com.google.common.base.Preconditions.checkArgument; | ||
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| import com.google.cloud.dataflow.sdk.io.Write; | ||
| import com.google.cloud.dataflow.sdk.transforms.Count; | ||
| import com.google.cloud.dataflow.sdk.transforms.DoFn; | ||
| import com.google.cloud.dataflow.sdk.transforms.Flatten; | ||
| import com.google.cloud.dataflow.sdk.transforms.GroupByKey; | ||
| import com.google.cloud.dataflow.sdk.transforms.PTransform; | ||
| import com.google.cloud.dataflow.sdk.transforms.ParDo; | ||
| import com.google.cloud.dataflow.sdk.transforms.Values; | ||
| import com.google.cloud.dataflow.sdk.transforms.windowing.DefaultTrigger; | ||
| import com.google.cloud.dataflow.sdk.transforms.windowing.GlobalWindows; | ||
| import com.google.cloud.dataflow.sdk.transforms.windowing.Window; | ||
| import com.google.cloud.dataflow.sdk.values.KV; | ||
| import com.google.cloud.dataflow.sdk.values.PCollection; | ||
| import com.google.cloud.dataflow.sdk.values.PCollectionView; | ||
| import com.google.cloud.dataflow.sdk.values.PDone; | ||
| import com.google.cloud.dataflow.sdk.values.PInput; | ||
| import com.google.cloud.dataflow.sdk.values.POutput; | ||
| import com.google.common.annotations.VisibleForTesting; | ||
| import org.joda.time.Duration; | ||
| import java.util.concurrent.ThreadLocalRandom; | ||
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|
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| /** | ||
| * A {@link PTransformOverrideFactory} that overrides {@link Write} {@link PTransform PTransforms} | ||
| * with an unspecified number of shards with a write with a specified number of shards. The number | ||
| * of shards is the log base 10 of the number of input records, with up to 2 additional shards. | ||
| */ | ||
| class WriteWithShardingFactory implements PTransformOverrideFactory { | ||
| static final int MAX_RANDOM_EXTRA_SHARDS = 3; | ||
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| @Override | ||
| public <InputT extends PInput, OutputT extends POutput> PTransform<InputT, OutputT> override( | ||
| PTransform<InputT, OutputT> transform) { | ||
| if (transform instanceof Write.Bound) { | ||
| Write.Bound<InputT> that = (Write.Bound<InputT>) transform; | ||
| if (that.getNumShards() == 0) { | ||
| return (PTransform<InputT, OutputT>) new DynamicallyReshardedWrite<InputT>(that); | ||
| } | ||
| } | ||
| return transform; | ||
| } | ||
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| private static class DynamicallyReshardedWrite <T> extends PTransform<PCollection<T>, PDone> { | ||
| private final transient Write.Bound<T> original; | ||
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| private DynamicallyReshardedWrite(Write.Bound<T> original) { | ||
| this.original = original; | ||
| } | ||
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| @Override | ||
| public PDone apply(PCollection<T> input) { | ||
| PCollection<T> records = input.apply("RewindowInputs", | ||
| Window.<T>into(new GlobalWindows()).triggering(DefaultTrigger.of()) | ||
| .withAllowedLateness(Duration.ZERO) | ||
| .discardingFiredPanes()); | ||
| final PCollectionView<Long> numRecords = records.apply(Count.<T>globally().asSingletonView()); | ||
| PCollection<T> resharded = | ||
| records | ||
| .apply( | ||
| "ApplySharding", | ||
| ParDo.withSideInputs(numRecords) | ||
| .of( | ||
| new KeyBasedOnCountFn<T>( | ||
| numRecords, | ||
| ThreadLocalRandom.current().nextInt(MAX_RANDOM_EXTRA_SHARDS)))) | ||
| .apply("GroupIntoShards", GroupByKey.<Integer, T>create()) | ||
| .apply("DropShardingKeys", Values.<Iterable<T>>create()) | ||
| .apply("FlattenShardIterables", Flatten.<T>iterables()); | ||
| // This is an inverted application to apply the expansion of the original Write PTransform | ||
| // without adding a new Write Transform Node, which would be overwritten the same way, leading | ||
| // to an infinite recursion. We cannot modify the number of shards, because that is determined | ||
| // at runtime. | ||
| return original.apply(resharded); | ||
| } | ||
| } | ||
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| @VisibleForTesting | ||
| static class KeyBasedOnCountFn<T> extends DoFn<T, KV<Integer, T>> { | ||
| @VisibleForTesting | ||
| static final int MIN_SHARDS_FOR_LOG = 3; | ||
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| private final PCollectionView<Long> numRecords; | ||
| private final int randomExtraShards; | ||
| private int currentShard; | ||
| private int maxShards; | ||
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| KeyBasedOnCountFn(PCollectionView<Long> numRecords, int extraShards) { | ||
| this.numRecords = numRecords; | ||
| this.randomExtraShards = extraShards; | ||
| } | ||
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| @Override | ||
| public void processElement(ProcessContext c) throws Exception { | ||
| if (maxShards == 0L) { | ||
| maxShards = calculateShards(c.sideInput(numRecords)); | ||
| currentShard = ThreadLocalRandom.current().nextInt(maxShards); | ||
| } | ||
| int shard = currentShard; | ||
| currentShard = (currentShard + 1) % maxShards; | ||
| c.output(KV.of(shard, c.element())); | ||
| } | ||
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| private int calculateShards(long totalRecords) { | ||
| checkArgument( | ||
| totalRecords > 0, | ||
| "KeyBasedOnCountFn cannot be invoked on an element if there are no elements"); | ||
| if (totalRecords < MIN_SHARDS_FOR_LOG + randomExtraShards) { | ||
| return (int) totalRecords; | ||
| } | ||
| // 100mil records before >7 output files | ||
| int floorLogRecs = Double.valueOf(Math.log10(totalRecords)).intValue(); | ||
| int shards = Math.max(floorLogRecs, MIN_SHARDS_FOR_LOG) + randomExtraShards; | ||
| return shards; | ||
| } | ||
| } | ||
| } |
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