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* 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,
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* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.kafka.streams.processor;
import org.apache.kafka.common.Cluster;
import org.apache.kafka.common.Node;
import org.apache.kafka.common.PartitionInfo;
import org.apache.kafka.common.TopicPartition;
import org.junit.Test;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import static org.apache.kafka.common.utils.Utils.mkSet;
import static org.junit.Assert.assertEquals;
public class DefaultPartitionGrouperTest {
private final List<PartitionInfo> infos = Arrays.asList(
new PartitionInfo("topic1", 0, Node.noNode(), new Node[0], new Node[0]),
new PartitionInfo("topic1", 1, Node.noNode(), new Node[0], new Node[0]),
new PartitionInfo("topic1", 2, Node.noNode(), new Node[0], new Node[0]),
new PartitionInfo("topic2", 0, Node.noNode(), new Node[0], new Node[0]),
new PartitionInfo("topic2", 1, Node.noNode(), new Node[0], new Node[0])
);
private final Cluster metadata = new Cluster(
"cluster",
Collections.singletonList(Node.noNode()),
infos,
Collections.<String>emptySet(),
Collections.<String>emptySet());
@Test
public void shouldComputeGroupingForTwoGroups() {
final PartitionGrouper grouper = new DefaultPartitionGrouper();
final Map<TaskId, Set<TopicPartition>> expectedPartitionsForTask = new HashMap<>();
final Map<Integer, Set<String>> topicGroups = new HashMap<>();
int topicGroupId = 0;
topicGroups.put(topicGroupId, mkSet("topic1"));
expectedPartitionsForTask.put(new TaskId(topicGroupId, 0), mkSet(new TopicPartition("topic1", 0)));
expectedPartitionsForTask.put(new TaskId(topicGroupId, 1), mkSet(new TopicPartition("topic1", 1)));
expectedPartitionsForTask.put(new TaskId(topicGroupId, 2), mkSet(new TopicPartition("topic1", 2)));
topicGroups.put(++topicGroupId, mkSet("topic2"));
expectedPartitionsForTask.put(new TaskId(topicGroupId, 0), mkSet(new TopicPartition("topic2", 0)));
expectedPartitionsForTask.put(new TaskId(topicGroupId, 1), mkSet(new TopicPartition("topic2", 1)));
assertEquals(expectedPartitionsForTask, grouper.partitionGroups(topicGroups, metadata));
}
@Test
public void shouldComputeGroupingForSingleGroupWithMultipleTopics() {
final PartitionGrouper grouper = new DefaultPartitionGrouper();
final Map<TaskId, Set<TopicPartition>> expectedPartitionsForTask = new HashMap<>();
final Map<Integer, Set<String>> topicGroups = new HashMap<>();
final int topicGroupId = 0;
topicGroups.put(topicGroupId, mkSet("topic1", "topic2"));
expectedPartitionsForTask.put(
new TaskId(topicGroupId, 0),
mkSet(new TopicPartition("topic1", 0), new TopicPartition("topic2", 0)));
expectedPartitionsForTask.put(
new TaskId(topicGroupId, 1),
mkSet(new TopicPartition("topic1", 1), new TopicPartition("topic2", 1)));
expectedPartitionsForTask.put(
new TaskId(topicGroupId, 2),
mkSet(new TopicPartition("topic1", 2)));
assertEquals(expectedPartitionsForTask, grouper.partitionGroups(topicGroups, metadata));
}
@Test
public void shouldNotCreateAnyTasksBecauseOneTopicHasUnknownPartitions() {
final PartitionGrouper grouper = new DefaultPartitionGrouper();
final Map<TaskId, Set<TopicPartition>> expectedPartitionsForTask = new HashMap<>();
final Map<Integer, Set<String>> topicGroups = new HashMap<>();
final int topicGroupId = 0;
topicGroups.put(topicGroupId, mkSet("topic1", "unknownTopic", "topic2"));
assertEquals(expectedPartitionsForTask, grouper.partitionGroups(topicGroups, metadata));
}
}