Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/1776#discussion_r56961903
--- Diff:
flink-tests/src/test/java/org/apache/flink/test/javaApiOperators/CustomDistributionITCase.java
---
@@ -0,0 +1,184 @@
+/*
+ * 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.flink.test.javaApiOperators;
+
+import org.apache.flink.api.common.distributions.DataDistribution;
+import org.apache.flink.api.common.functions.MapFunction;
+import org.apache.flink.api.common.functions.RichMapPartitionFunction;
+import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.java.DataSet;
+import org.apache.flink.api.java.ExecutionEnvironment;
+import org.apache.flink.api.java.io.DiscardingOutputFormat;
+import org.apache.flink.api.java.tuple.Tuple3;
+import org.apache.flink.api.java.utils.DataSetUtils;
+import org.apache.flink.core.memory.DataInputView;
+import org.apache.flink.core.memory.DataOutputView;
+import org.apache.flink.test.javaApiOperators.util.CollectionDataSets;
+import org.apache.flink.util.Collector;
+import org.junit.Test;
+
+
+import java.io.IOException;
+
+import static org.junit.Assert.fail;
+
+
+public class CustomDistributionITCase {
+
+ @Test
+ public void testPartitionWithDistribution1() throws Exception{
+ /*
+ * Test the record partitioned rightly with one field according
to the customized data distribution
+ */
+
+ ExecutionEnvironment env =
ExecutionEnvironment.createLocalEnvironment();
+
+ DataSet<Tuple3<Integer, Long, String>> input1 =
CollectionDataSets.get3TupleDataSet(env);
+ final TestDataDist dist = new TestDataDist(1);
+
+ env.setParallelism(dist.getParallelism());
+
+ DataSet<Boolean> result = DataSetUtils.partitionByRange(input1,
dist, 0).mapPartition(new RichMapPartitionFunction<Tuple3<Integer, Long,
String>, Boolean>() {
+ @Override
+ public void mapPartition(Iterable<Tuple3<Integer, Long,
String>> values, Collector<Boolean> out) throws Exception {
+ int partitionIndex =
getRuntimeContext().getIndexOfThisSubtask();
+
+ for (Tuple3<Integer, Long, String> s : values) {
+ if ((s.f0 - 1) / 7 != partitionIndex) {
+ fail("Record was not correctly
partitioned: " + s.toString());
+ }
+ }
+ }
+ });
+
+ result.output(new DiscardingOutputFormat());
+ env.execute();
+ }
+
+ @Test
+ public void testRangeWithDistribution2() throws Exception{
+ /*
+ * Test the record partitioned rightly with two fields
according to the customized data distribution
+ */
+
+ ExecutionEnvironment env =
ExecutionEnvironment.createLocalEnvironment();
+
+ DataSet<Tuple3<Integer, Long, String>> input1 =
CollectionDataSets.get3TupleDataSet(env);
+ final TestDataDist dist = new TestDataDist(2);
+
+ env.setParallelism(dist.getParallelism());
+
+ DataSet<Boolean> result =
DataSetUtils.partitionByRange(input1.map(new MapFunction<Tuple3<Integer, Long,
String>, Tuple3<Integer, Integer, String>>() {
+ @Override
+ public Tuple3<Integer, Integer, String>
map(Tuple3<Integer, Long, String> value) throws Exception {
+ return new Tuple3<>(value.f0,
value.f1.intValue(), value.f2);
+ }
+ }), dist, 0, 1).mapPartition(new
RichMapPartitionFunction<Tuple3<Integer, Integer, String>, Boolean>() {
+ @Override
+ public void mapPartition(Iterable<Tuple3<Integer,
Integer, String>> values, Collector<Boolean> out) throws Exception {
+ int partitionIndex =
getRuntimeContext().getIndexOfThisSubtask();
+
+ for (Tuple3<Integer, Integer, String> s :
values) {
+ if (s.f0 <= partitionIndex *
(partitionIndex + 1) / 2 ||
+ s.f0 > (partitionIndex
+ 1) * (partitionIndex + 2) / 2 ||
+ s.f1 - 1 !=
partitionIndex) {
+ fail("Record was not correctly
partitioned: " + s.toString());
+ }
+ }
+ }
+ });
+
+ result.output(new DiscardingOutputFormat());
+ env.execute();
+ }
+
+ /**
+ * The class is used to do the tests of range partition with customed
data distribution.
+ */
+ public static class TestDataDist implements DataDistribution {
+
+ private int dim;
+
+ public TestDataDist() {}
+
+ /**
+ * Constructor of the customized distribution for range
partition.
+ * @param dim the number of the fields.
+ */
+ public TestDataDist(int dim) {
+ this.dim = dim;
+ }
+
+ public int getParallelism() {
+ if (dim == 1) {
+ return 3;
+ }
+ return 6;
+ }
+
+ @Override
+ public Object[] getBucketBoundary(int bucketNum, int
totalNumBuckets) {
+ if (dim == 1) {
+ /*
+ for the first test, the boundary is just like :
+ (0, 7]
+ (7, 14]
+ (14, 21]
+ */
+
+ return new Integer[]{(bucketNum + 1) * 7};
+ }
+ /*
+ for the second test, the boundary is just like :
+ (0, 1], (0, 1]
--- End diff --
This is not a common distribution for composite range partition keys. It
should look similar to this one:
```
( (1, 2), (1, 7) ]
( (1, 7), (3, 2) ]
( (3, 2), (4, 8) ]
...
```
This would result in 4 partitions:
- Partition 1: `(0,2), (1,1), (0,10), ...`
- Partition 2: `(1,3), (2,20), (1,8), ...`
- Partition 3: `(4,10), (3,5), ...`
- Partition 4: `(5,3), (8,20), (4,12), ...`
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