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[FLINK-8974] Run all-round DataSet job with failures in HA mode
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...sts/flink-dataset-allround-test/src/main/java/org/apache/flink/batch/tests/Generator.java
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| /* | ||
| * 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:https://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. | ||
| */ | ||
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| package org.apache.flink.batch.tests; | ||
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| import org.apache.flink.api.common.io.DefaultInputSplitAssigner; | ||
| import org.apache.flink.api.common.io.InputFormat; | ||
| import org.apache.flink.api.common.io.statistics.BaseStatistics; | ||
| import org.apache.flink.api.java.tuple.Tuple2; | ||
| import org.apache.flink.configuration.Configuration; | ||
| import org.apache.flink.core.io.GenericInputSplit; | ||
| import org.apache.flink.core.io.InputSplitAssigner; | ||
| import org.apache.flink.util.Preconditions; | ||
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| import java.io.IOException; | ||
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| /** | ||
| * InputFormat that generates a deterministic DataSet of Tuple2(String, Integer) | ||
| * <ul> | ||
| * <li>String: key, can be repeated.</li> | ||
| * <li>Integer: uniformly distributed int between 0 and 127</li> | ||
| * </ul> | ||
| */ | ||
| public class Generator implements InputFormat<Tuple2<String, Integer>, GenericInputSplit> { | ||
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| // total number of records | ||
| private final long numRecords; | ||
| // total number of keys | ||
| private final long numKeys; | ||
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| // records emitted per partition | ||
| private long recordsPerPartition; | ||
| // number of keys per partition | ||
| private long keysPerPartition; | ||
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| // number of currently emitted records | ||
| private long recordCnt; | ||
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| // id of current partition | ||
| private int partitionId; | ||
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| private final boolean infinite; | ||
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| public static Generator generate(long numKeys, int recordsPerKey) { | ||
| return new Generator(numKeys, recordsPerKey, false); | ||
| } | ||
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| public static Generator generateInfinitely(long numKeys) { | ||
| return new Generator(numKeys, 0, true); | ||
| } | ||
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| private Generator(long numKeys, int recordsPerKey, boolean infinite) { | ||
| this.numKeys = numKeys; | ||
| if (infinite) { | ||
| this.numRecords = Long.MAX_VALUE; | ||
| } else { | ||
| this.numRecords = numKeys * recordsPerKey; | ||
| } | ||
| this.infinite = infinite; | ||
| } | ||
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| @Override | ||
| public void configure(Configuration parameters) { | ||
| } | ||
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| @Override | ||
| public BaseStatistics getStatistics(BaseStatistics cachedStatistics) { | ||
| return null; | ||
| } | ||
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| @Override | ||
| public GenericInputSplit[] createInputSplits(int minNumSplits) { | ||
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| GenericInputSplit[] splits = new GenericInputSplit[minNumSplits]; | ||
| for (int i = 0; i < minNumSplits; i++) { | ||
| splits[i] = new GenericInputSplit(i, minNumSplits); | ||
| } | ||
| return splits; | ||
| } | ||
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| @Override | ||
| public InputSplitAssigner getInputSplitAssigner(GenericInputSplit[] inputSplits) { | ||
| return new DefaultInputSplitAssigner(inputSplits); | ||
| } | ||
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| @Override | ||
| public void open(GenericInputSplit split) throws IOException { | ||
| this.partitionId = split.getSplitNumber(); | ||
| // total number of partitions | ||
| int numPartitions = split.getTotalNumberOfSplits(); | ||
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| // ensure even distribution of records and keys | ||
| Preconditions.checkArgument( | ||
| numRecords % numPartitions == 0, | ||
| "Records cannot be evenly distributed among partitions"); | ||
| Preconditions.checkArgument( | ||
| numKeys % numPartitions == 0, | ||
| "Keys cannot be evenly distributed among partitions"); | ||
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| this.recordsPerPartition = numRecords / numPartitions; | ||
| this.keysPerPartition = numKeys / numPartitions; | ||
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| this.recordCnt = 0; | ||
| } | ||
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| @Override | ||
| public boolean reachedEnd() { | ||
| return !infinite && this.recordCnt >= this.recordsPerPartition; | ||
| } | ||
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| @Override | ||
| public Tuple2<String, Integer> nextRecord(Tuple2<String, Integer> reuse) throws IOException { | ||
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| // build key from partition id and count per partition | ||
| String key = String.format( | ||
| "%d-%d", | ||
| this.partitionId, | ||
| this.recordCnt % this.keysPerPartition); | ||
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| // 128 values to filter on | ||
| int filterVal = (int) this.recordCnt % 128; | ||
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| this.recordCnt++; | ||
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| reuse.f0 = key; | ||
| reuse.f1 = filterVal; | ||
| return reuse; | ||
| } | ||
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| @Override | ||
| public void close() { | ||
| } | ||
| } |
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