2013-07-16 20:21:33 -04:00
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#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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2012-08-10 04:10:02 -04:00
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import sys
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from random import Random
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2013-01-01 16:52:14 -05:00
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from pyspark import SparkContext
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2012-08-10 04:10:02 -04:00
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numEdges = 200
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numVertices = 100
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rand = Random(42)
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def generateGraph():
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edges = set()
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while len(edges) < numEdges:
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src = rand.randrange(0, numEdges)
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dst = rand.randrange(0, numEdges)
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if src != dst:
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edges.add((src, dst))
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return edges
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if __name__ == "__main__":
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if len(sys.argv) == 1:
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2013-07-27 21:11:28 -04:00
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print >> sys.stderr, "Usage: transitive_closure <master> [<slices>]"
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2012-08-10 04:10:02 -04:00
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exit(-1)
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2013-07-27 21:11:28 -04:00
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sc = SparkContext(sys.argv[1], "PythonTransitiveClosure")
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2013-03-10 01:16:19 -05:00
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slices = int(sys.argv[2]) if len(sys.argv) > 2 else 2
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2012-08-27 03:13:19 -04:00
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tc = sc.parallelize(generateGraph(), slices).cache()
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2012-08-10 04:10:02 -04:00
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# Linear transitive closure: each round grows paths by one edge,
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# by joining the graph's edges with the already-discovered paths.
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# e.g. join the path (y, z) from the TC with the edge (x, y) from
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# the graph to obtain the path (x, z).
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# Because join() joins on keys, the edges are stored in reversed order.
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2012-08-27 03:13:19 -04:00
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edges = tc.map(lambda (x, y): (y, x))
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2012-08-10 04:10:02 -04:00
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oldCount = 0L
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nextCount = tc.count()
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while True:
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oldCount = nextCount
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# Perform the join, obtaining an RDD of (y, (z, x)) pairs,
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# then project the result to obtain the new (x, z) paths.
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2012-08-27 03:13:19 -04:00
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new_edges = tc.join(edges).map(lambda (_, (a, b)): (b, a))
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2012-08-10 04:10:02 -04:00
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tc = tc.union(new_edges).distinct().cache()
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nextCount = tc.count()
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if nextCount == oldCount:
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break
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print "TC has %i edges" % tc.count()
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