
org.apache.apex.malhar.kafka.OneToOnePartitioner Maven / Gradle / Ivy
/**
* 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.apex.malhar.kafka;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Set;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.kafka.common.PartitionInfo;
import com.google.common.collect.Sets;
/**
* An one-to-one partitioner implementation that always returns same amount of operator partitions as
* Kafka partitions for the topics that operator subscribe
*
* @since 3.3.0
*/
@InterfaceStability.Evolving
public class OneToOnePartitioner extends AbstractKafkaPartitioner
{
public OneToOnePartitioner(String[] clusters, String[] topics, AbstractKafkaInputOperator prototypeOperator)
{
super(clusters, topics, prototypeOperator);
}
@Override
List> assign(Map>> metadata)
{
List> currentAssignment = new LinkedList<>();
for (Map.Entry>> clusterMap : metadata.entrySet()) {
for (Map.Entry> topicPartition : clusterMap.getValue().entrySet()) {
for (PartitionInfo pif : topicPartition.getValue()) {
currentAssignment.add(Sets.newHashSet(new PartitionMeta(clusterMap.getKey(), topicPartition.getKey(), pif.partition())));
}
}
}
return currentAssignment;
}
}
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