/*

  * 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> {

 }