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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.
+#
+
+import sys
+from random import Random
+
+from pyspark import SparkContext
+
+numEdges = 200
+numVertices = 100
+rand = Random(42)
+
+
+def generateGraph():
+ edges = set()
+ while len(edges) < numEdges:
+ src = rand.randrange(0, numEdges)
+ dst = rand.randrange(0, numEdges)
+ if src != dst:
+ edges.add((src, dst))
+ return edges
+
+
+if __name__ == "__main__":
+ if len(sys.argv) == 1:
+ print >> sys.stderr, "Usage: transitive_closure <master> [<slices>]"
+ exit(-1)
+ sc = SparkContext(sys.argv[1], "PythonTransitiveClosure")
+ slices = int(sys.argv[2]) if len(sys.argv) > 2 else 2
+ tc = sc.parallelize(generateGraph(), slices).cache()
+
+ # Linear transitive closure: each round grows paths by one edge,
+ # by joining the graph's edges with the already-discovered paths.
+ # e.g. join the path (y, z) from the TC with the edge (x, y) from
+ # the graph to obtain the path (x, z).
+
+ # Because join() joins on keys, the edges are stored in reversed order.
+ edges = tc.map(lambda (x, y): (y, x))
+
+ oldCount = 0L
+ nextCount = tc.count()
+ while True:
+ oldCount = nextCount
+ # Perform the join, obtaining an RDD of (y, (z, x)) pairs,
+ # then project the result to obtain the new (x, z) paths.
+ new_edges = tc.join(edges).map(lambda (_, (a, b)): (b, a))
+ tc = tc.union(new_edges).distinct().cache()
+ nextCount = tc.count()
+ if nextCount == oldCount:
+ break
+
+ print "TC has %i edges" % tc.count()