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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.spark.graphx.lib
import org.apache.spark.{SparkContext, SparkFunSuite}
import org.apache.spark.SparkContext._
import org.apache.spark.graphx._
import org.apache.spark.graphx.lib._
import org.apache.spark.graphx.util.GraphGenerators
import org.apache.spark.rdd._
class ShortestPathsSuite extends SparkFunSuite with LocalSparkContext {
test("Shortest Path Computations") {
withSpark { sc =>
val shortestPaths = Set(
(1, Map(1 -> 0, 4 -> 2)), (2, Map(1 -> 1, 4 -> 2)), (3, Map(1 -> 2, 4 -> 1)),
(4, Map(1 -> 2, 4 -> 0)), (5, Map(1 -> 1, 4 -> 1)), (6, Map(1 -> 3, 4 -> 1)))
val edgeSeq = Seq((1, 2), (1, 5), (2, 3), (2, 5), (3, 4), (4, 5), (4, 6)).flatMap {
case e => Seq(e, e.swap)
}
val edges = sc.parallelize(edgeSeq).map { case (v1, v2) => (v1.toLong, v2.toLong) }
val graph = Graph.fromEdgeTuples(edges, 1)
val landmarks = Seq(1, 4).map(_.toLong)
val results = ShortestPaths.run(graph, landmarks).vertices.collect.map {
case (v, spMap) => (v, spMap.mapValues(i => i))
}
assert(results.toSet === shortestPaths)
}
}
}
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