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authorSandeep <sandeep@techaddict.me>2014-05-06 17:27:52 -0700
committerMatei Zaharia <matei@databricks.com>2014-05-06 17:27:52 -0700
commita000b5c3b0438c17e9973df4832c320210c29c27 (patch)
tree446bbe902ecd6de05072357f7ef25aaeb0687b73 /examples/src/main/python/kmeans.py
parent39b8b1489ff92697e4aeec997cdc436c7079d6f8 (diff)
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SPARK-1637: Clean up examples for 1.0
- [x] Move all of them into subpackages of org.apache.spark.examples (right now some are in org.apache.spark.streaming.examples, for instance, and others are in org.apache.spark.examples.mllib) - [x] Move Python examples into examples/src/main/python - [x] Update docs to reflect these changes Author: Sandeep <sandeep@techaddict.me> This patch had conflicts when merged, resolved by Committer: Matei Zaharia <matei@databricks.com> Closes #571 from techaddict/SPARK-1637 and squashes the following commits: 47ef86c [Sandeep] Changes based on Discussions on PR, removing use of RawTextHelper from examples 8ed2d3f [Sandeep] Docs Updated for changes, Change for java examples 5f96121 [Sandeep] Move Python examples into examples/src/main/python 0a8dd77 [Sandeep] Move all Scala Examples to org.apache.spark.examples (some are in org.apache.spark.streaming.examples, for instance, and others are in org.apache.spark.examples.mllib)
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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.
+#
+
+"""
+The K-means algorithm written from scratch against PySpark. In practice,
+one may prefer to use the KMeans algorithm in MLlib, as shown in
+examples/src/main/python/mllib/kmeans.py.
+
+This example requires NumPy (http://www.numpy.org/).
+"""
+
+import sys
+
+import numpy as np
+from pyspark import SparkContext
+
+
+def parseVector(line):
+ return np.array([float(x) for x in line.split(' ')])
+
+
+def closestPoint(p, centers):
+ bestIndex = 0
+ closest = float("+inf")
+ for i in range(len(centers)):
+ tempDist = np.sum((p - centers[i]) ** 2)
+ if tempDist < closest:
+ closest = tempDist
+ bestIndex = i
+ return bestIndex
+
+
+if __name__ == "__main__":
+ if len(sys.argv) < 5:
+ print >> sys.stderr, "Usage: kmeans <master> <file> <k> <convergeDist>"
+ exit(-1)
+ sc = SparkContext(sys.argv[1], "PythonKMeans")
+ lines = sc.textFile(sys.argv[2])
+ data = lines.map(parseVector).cache()
+ K = int(sys.argv[3])
+ convergeDist = float(sys.argv[4])
+
+ kPoints = data.takeSample(False, K, 1)
+ tempDist = 1.0
+
+ while tempDist > convergeDist:
+ closest = data.map(
+ lambda p : (closestPoint(p, kPoints), (p, 1)))
+ pointStats = closest.reduceByKey(
+ lambda (x1, y1), (x2, y2): (x1 + x2, y1 + y2))
+ newPoints = pointStats.map(
+ lambda (x, (y, z)): (x, y / z)).collect()
+
+ tempDist = sum(np.sum((kPoints[x] - y) ** 2) for (x, y) in newPoints)
+
+ for (x, y) in newPoints:
+ kPoints[x] = y
+
+ print "Final centers: " + str(kPoints)