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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://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.giraph.graph.partition;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.io.WritableComparable;
/**
* Range partitioning will split the vertices by a key range based on a generic
* type. This allows vertices that have some locality with the vertex ids
* to reduce the amount of messages sent. The tradeoffs are that
* range partitioning is more susceptible to hot spots if the keys
* are not randomly distributed. Another negative is the user must implement
* some of the functionality around how to split the key range.
*
* See {@link RangeWorkerPartitioner}
*
* @param <I> Vertex index value
* @param <V> Vertex value
* @param <E> Edge value
* @param <M> Message value
*/
@SuppressWarnings("rawtypes")
public abstract class RangePartitionerFactory<I extends WritableComparable,
V extends Writable, E extends Writable, M extends Writable>
implements GraphPartitionerFactory<I, V, E, M> {
}