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)

36 files changed, 625 insertions, 52 deletions

diff --git a/examples/src/main/java/org/apache/spark/mllib/examples/JavaALS.java b/examples/src/main/java/org/apache/spark/examples/mllib/JavaALS.java
index c516199d61..4533c4c5f2 100644
--- a/examples/src/main/java/org/apache/spark/mllib/examples/JavaALS.java
+++ b/examples/src/main/java/org/apache/spark/examples/mllib/JavaALS.java
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.mllib.examples;
+package org.apache.spark.examples.mllib;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
diff --git a/examples/src/main/java/org/apache/spark/mllib/examples/JavaKMeans.java b/examples/src/main/java/org/apache/spark/examples/mllib/JavaKMeans.java
index 7461609ab9..0cfb8e69ed 100644
--- a/examples/src/main/java/org/apache/spark/mllib/examples/JavaKMeans.java
+++ b/examples/src/main/java/org/apache/spark/examples/mllib/JavaKMeans.java
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.mllib.examples;
+package org.apache.spark.examples.mllib;
 
 import java.util.regex.Pattern;
 
diff --git a/examples/src/main/java/org/apache/spark/mllib/examples/JavaLR.java b/examples/src/main/java/org/apache/spark/examples/mllib/JavaLR.java
index e3ab87cc72..f6e48b4987 100644
--- a/examples/src/main/java/org/apache/spark/mllib/examples/JavaLR.java
+++ b/examples/src/main/java/org/apache/spark/examples/mllib/JavaLR.java
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.mllib.examples;
+package org.apache.spark.examples.mllib;
 
 import java.util.regex.Pattern;
 
diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaFlumeEventCount.java b/examples/src/main/java/org/apache/spark/examples/streaming/JavaFlumeEventCount.java
index c59f7538f8..a5ece68cef 100644
--- a/examples/src/main/java/org/apache/spark/streaming/examples/JavaFlumeEventCount.java
+++ b/examples/src/main/java/org/apache/spark/examples/streaming/JavaFlumeEventCount.java
@@ -15,9 +15,10 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples;
+package org.apache.spark.examples.streaming;
 
 import org.apache.spark.api.java.function.Function;
+import org.apache.spark.examples.streaming.StreamingExamples;
 import org.apache.spark.streaming.*;
 import org.apache.spark.streaming.api.java.*;
 import org.apache.spark.streaming.flume.FlumeUtils;
diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaKafkaWordCount.java b/examples/src/main/java/org/apache/spark/examples/streaming/JavaKafkaWordCount.java
index 8da9bcd05a..da51eb189a 100644
--- a/examples/src/main/java/org/apache/spark/streaming/examples/JavaKafkaWordCount.java
+++ b/examples/src/main/java/org/apache/spark/examples/streaming/JavaKafkaWordCount.java
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples;
+package org.apache.spark.examples.streaming;
 
 import java.util.Map;
 import java.util.HashMap;
@@ -26,6 +26,7 @@ import org.apache.spark.api.java.function.FlatMapFunction;
 import org.apache.spark.api.java.function.Function;
 import org.apache.spark.api.java.function.Function2;
 import org.apache.spark.api.java.function.PairFunction;
+import org.apache.spark.examples.streaming.StreamingExamples;
 import org.apache.spark.streaming.Duration;
 import org.apache.spark.streaming.api.java.JavaDStream;
 import org.apache.spark.streaming.api.java.JavaPairDStream;
@@ -44,7 +45,7 @@ import scala.Tuple2;
  *   <numThreads> is the number of threads the kafka consumer should use
  *
  * Example:
- *    `./bin/run-example org.apache.spark.streaming.examples.JavaKafkaWordCount local[2] zoo01,zoo02,
+ *    `./bin/run-example org.apache.spark.examples.streaming.JavaKafkaWordCount local[2] zoo01,zoo02,
  *    zoo03 my-consumer-group topic1,topic2 1`
  */
 
diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaNetworkWordCount.java b/examples/src/main/java/org/apache/spark/examples/streaming/JavaNetworkWordCount.java
index 098c329ff6..ac84991d87 100644
--- a/examples/src/main/java/org/apache/spark/streaming/examples/JavaNetworkWordCount.java
+++ b/examples/src/main/java/org/apache/spark/examples/streaming/JavaNetworkWordCount.java
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples;
+package org.apache.spark.examples.streaming;
 
 import com.google.common.collect.Lists;
 import org.apache.spark.streaming.api.java.JavaReceiverInputDStream;
@@ -23,6 +23,7 @@ import scala.Tuple2;
 import org.apache.spark.api.java.function.FlatMapFunction;
 import org.apache.spark.api.java.function.Function2;
 import org.apache.spark.api.java.function.PairFunction;
+import org.apache.spark.examples.streaming.StreamingExamples;
 import org.apache.spark.streaming.Duration;
 import org.apache.spark.streaming.api.java.JavaDStream;
 import org.apache.spark.streaming.api.java.JavaPairDStream;
@@ -39,7 +40,7 @@ import java.util.regex.Pattern;
  * To run this on your local machine, you need to first run a Netcat server
  *    `$ nc -lk 9999`
  * and then run the example
- *    `$ ./run org.apache.spark.streaming.examples.JavaNetworkWordCount local[2] localhost 9999`
+ *    `$ ./run org.apache.spark.examples.streaming.JavaNetworkWordCount local[2] localhost 9999`
  */
 public final class JavaNetworkWordCount {
   private static final Pattern SPACE = Pattern.compile(" ");
diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaQueueStream.java b/examples/src/main/java/org/apache/spark/examples/streaming/JavaQueueStream.java
index 88ad341641..819311968f 100644
--- a/examples/src/main/java/org/apache/spark/streaming/examples/JavaQueueStream.java
+++ b/examples/src/main/java/org/apache/spark/examples/streaming/JavaQueueStream.java
@@ -15,13 +15,14 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples;
+package org.apache.spark.examples.streaming;
 
 import com.google.common.collect.Lists;
 import scala.Tuple2;
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.function.Function2;
 import org.apache.spark.api.java.function.PairFunction;
+import org.apache.spark.examples.streaming.StreamingExamples;
 import org.apache.spark.streaming.Duration;
 import org.apache.spark.streaming.api.java.JavaDStream;
 import org.apache.spark.streaming.api.java.JavaPairDStream;
diff --git a/examples/src/main/python/als.py b/examples/src/main/python/als.py
new file mode 100755
index 0000000000..a77dfb2577
--- /dev/null
+++ b/examples/src/main/python/als.py
@@ -0,0 +1,87 @@
+#
+# 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.
+#
+
+"""
+This example requires numpy (http://www.numpy.org/)
+"""
+from os.path import realpath
+import sys
+
+import numpy as np
+from numpy.random import rand
+from numpy import matrix
+from pyspark import SparkContext
+
+LAMBDA = 0.01   # regularization
+np.random.seed(42)
+
+def rmse(R, ms, us):
+    diff = R - ms * us.T
+    return np.sqrt(np.sum(np.power(diff, 2)) / M * U)
+
+def update(i, vec, mat, ratings):
+    uu = mat.shape[0]
+    ff = mat.shape[1]
+    XtX = matrix(np.zeros((ff, ff)))
+    Xty = np.zeros((ff, 1))
+
+    for j in range(uu):
+        v = mat[j, :]
+        XtX += v.T * v
+        Xty += v.T * ratings[i, j]
+    XtX += np.eye(ff, ff) * LAMBDA * uu
+    return np.linalg.solve(XtX, Xty)
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        print >> sys.stderr, "Usage: als <master> <M> <U> <F> <iters> <slices>"
+        exit(-1)
+    sc = SparkContext(sys.argv[1], "PythonALS", pyFiles=[realpath(__file__)])
+    M = int(sys.argv[2]) if len(sys.argv) > 2 else 100
+    U = int(sys.argv[3]) if len(sys.argv) > 3 else 500
+    F = int(sys.argv[4]) if len(sys.argv) > 4 else 10
+    ITERATIONS = int(sys.argv[5]) if len(sys.argv) > 5 else 5
+    slices = int(sys.argv[6]) if len(sys.argv) > 6 else 2
+
+    print "Running ALS with M=%d, U=%d, F=%d, iters=%d, slices=%d\n" % \
+            (M, U, F, ITERATIONS, slices)
+
+    R = matrix(rand(M, F)) * matrix(rand(U, F).T)
+    ms = matrix(rand(M ,F))
+    us = matrix(rand(U, F))
+
+    Rb = sc.broadcast(R)
+    msb = sc.broadcast(ms)
+    usb = sc.broadcast(us)
+
+    for i in range(ITERATIONS):
+        ms = sc.parallelize(range(M), slices) \
+               .map(lambda x: update(x, msb.value[x, :], usb.value, Rb.value)) \
+               .collect()
+        ms = matrix(np.array(ms)[:, :, 0])      # collect() returns a list, so array ends up being
+                                                # a 3-d array, we take the first 2 dims for the matrix
+        msb = sc.broadcast(ms)
+
+        us = sc.parallelize(range(U), slices) \
+               .map(lambda x: update(x, usb.value[x, :], msb.value, Rb.value.T)) \
+               .collect()
+        us = matrix(np.array(us)[:, :, 0])
+        usb = sc.broadcast(us)
+
+        error = rmse(R, ms, us)
+        print "Iteration %d:" % i
+        print "\nRMSE: %5.4f\n" % error
diff --git a/examples/src/main/python/kmeans.py b/examples/src/main/python/kmeans.py
new file mode 100755
index 0000000000..e3596488fa
--- /dev/null
+++ b/examples/src/main/python/kmeans.py
@@ -0,0 +1,73 @@
+#
+# 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)
diff --git a/examples/src/main/python/logistic_regression.py b/examples/src/main/python/logistic_regression.py
new file mode 100755
index 0000000000..fe5373cf79
--- /dev/null
+++ b/examples/src/main/python/logistic_regression.py
@@ -0,0 +1,76 @@
+#
+# 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.
+#
+
+"""
+A logistic regression implementation that uses NumPy (http://www.numpy.org)
+to act on batches of input data using efficient matrix operations.
+
+In practice, one may prefer to use the LogisticRegression algorithm in
+MLlib, as shown in examples/src/main/python/mllib/logistic_regression.py.
+"""
+
+from collections import namedtuple
+from math import exp
+from os.path import realpath
+import sys
+
+import numpy as np
+from pyspark import SparkContext
+
+
+D = 10  # Number of dimensions
+
+
+# Read a batch of points from the input file into a NumPy matrix object. We operate on batches to
+# make further computations faster.
+# The data file contains lines of the form <label> <x1> <x2> ... <xD>. We load each block of these
+# into a NumPy array of size numLines * (D + 1) and pull out column 0 vs the others in gradient().
+def readPointBatch(iterator):
+    strs = list(iterator)
+    matrix = np.zeros((len(strs), D + 1))
+    for i in xrange(len(strs)):
+        matrix[i] = np.fromstring(strs[i].replace(',', ' '), dtype=np.float32, sep=' ')
+    return [matrix]
+
+if __name__ == "__main__":
+    if len(sys.argv) != 4:
+        print >> sys.stderr, "Usage: logistic_regression <master> <file> <iters>"
+        exit(-1)
+    sc = SparkContext(sys.argv[1], "PythonLR", pyFiles=[realpath(__file__)])
+    points = sc.textFile(sys.argv[2]).mapPartitions(readPointBatch).cache()
+    iterations = int(sys.argv[3])
+
+    # Initialize w to a random value
+    w = 2 * np.random.ranf(size=D) - 1
+    print "Initial w: " + str(w)
+
+    # Compute logistic regression gradient for a matrix of data points
+    def gradient(matrix, w):
+        Y = matrix[:,0]    # point labels (first column of input file)
+        X = matrix[:,1:]   # point coordinates
+        # For each point (x, y), compute gradient function, then sum these up
+        return ((1.0 / (1.0 + np.exp(-Y * X.dot(w))) - 1.0) * Y * X.T).sum(1)
+
+    def add(x, y):
+        x += y
+        return x
+
+    for i in range(iterations):
+        print "On iteration %i" % (i + 1)
+        w -= points.map(lambda m: gradient(m, w)).reduce(add)
+
+    print "Final w: " + str(w)
diff --git a/examples/src/main/python/mllib/kmeans.py b/examples/src/main/python/mllib/kmeans.py
new file mode 100755
index 0000000000..dec82ff34f
--- /dev/null
+++ b/examples/src/main/python/mllib/kmeans.py
@@ -0,0 +1,44 @@
+#
+# 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.
+#
+
+"""
+A K-means clustering program using MLlib.
+
+This example requires NumPy (http://www.numpy.org/).
+"""
+
+import sys
+
+import numpy as np
+from pyspark import SparkContext
+from pyspark.mllib.clustering import KMeans
+
+
+def parseVector(line):
+    return np.array([float(x) for x in line.split(' ')])
+
+
+if __name__ == "__main__":
+    if len(sys.argv) < 4:
+        print >> sys.stderr, "Usage: kmeans <master> <file> <k>"
+        exit(-1)
+    sc = SparkContext(sys.argv[1], "KMeans")
+    lines = sc.textFile(sys.argv[2])
+    data = lines.map(parseVector)
+    k = int(sys.argv[3])
+    model = KMeans.train(data, k)
+    print "Final centers: " + str(model.clusterCenters)
diff --git a/examples/src/main/python/mllib/logistic_regression.py b/examples/src/main/python/mllib/logistic_regression.py
new file mode 100755
index 0000000000..8631051d00
--- /dev/null
+++ b/examples/src/main/python/mllib/logistic_regression.py
@@ -0,0 +1,50 @@
+#
+# 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.
+#
+
+"""
+Logistic regression using MLlib.
+
+This example requires NumPy (http://www.numpy.org/).
+"""
+
+from math import exp
+import sys
+
+import numpy as np
+from pyspark import SparkContext
+from pyspark.mllib.regression import LabeledPoint
+from pyspark.mllib.classification import LogisticRegressionWithSGD
+
+
+# Parse a line of text into an MLlib LabeledPoint object
+def parsePoint(line):
+    values = [float(s) for s in line.split(' ')]
+    if values[0] == -1:   # Convert -1 labels to 0 for MLlib
+        values[0] = 0
+    return LabeledPoint(values[0], values[1:])
+
+
+if __name__ == "__main__":
+    if len(sys.argv) != 4:
+        print >> sys.stderr, "Usage: logistic_regression <master> <file> <iters>"
+        exit(-1)
+    sc = SparkContext(sys.argv[1], "PythonLR")
+    points = sc.textFile(sys.argv[2]).map(parsePoint)
+    iterations = int(sys.argv[3])
+    model = LogisticRegressionWithSGD.train(points, iterations)
+    print "Final weights: " + str(model.weights)
+    print "Final intercept: " + str(model.intercept)
diff --git a/examples/src/main/python/pagerank.py b/examples/src/main/python/pagerank.py
new file mode 100755
index 0000000000..cd774cf3a3
--- /dev/null
+++ b/examples/src/main/python/pagerank.py
@@ -0,0 +1,70 @@
+#
+# 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.
+#
+
+#!/usr/bin/env python
+
+import re, sys
+from operator import add
+
+from pyspark import SparkContext
+
+
+def computeContribs(urls, rank):
+    """Calculates URL contributions to the rank of other URLs."""
+    num_urls = len(urls)
+    for url in urls: yield (url, rank / num_urls)
+
+
+def parseNeighbors(urls):
+    """Parses a urls pair string into urls pair."""
+    parts = re.split(r'\s+', urls)
+    return parts[0], parts[1]
+
+
+if __name__ == "__main__":
+    if len(sys.argv) < 3:
+        print >> sys.stderr, "Usage: pagerank <master> <file> <number_of_iterations>"
+        exit(-1)
+
+    # Initialize the spark context.
+    sc = SparkContext(sys.argv[1], "PythonPageRank")
+
+    # Loads in input file. It should be in format of:
+    #     URL         neighbor URL
+    #     URL         neighbor URL
+    #     URL         neighbor URL
+    #     ...
+    lines = sc.textFile(sys.argv[2], 1)
+
+    # Loads all URLs from input file and initialize their neighbors.
+    links = lines.map(lambda urls: parseNeighbors(urls)).distinct().groupByKey().cache()
+
+    # Loads all URLs with other URL(s) link to from input file and initialize ranks of them to one.
+    ranks = links.map(lambda (url, neighbors): (url, 1.0))
+
+    # Calculates and updates URL ranks continuously using PageRank algorithm.
+    for iteration in xrange(int(sys.argv[3])):
+        # Calculates URL contributions to the rank of other URLs.
+        contribs = links.join(ranks).flatMap(lambda (url, (urls, rank)):
+            computeContribs(urls, rank))
+
+        # Re-calculates URL ranks based on neighbor contributions.
+        ranks = contribs.reduceByKey(add).mapValues(lambda rank: rank * 0.85 + 0.15)
+
+    # Collects all URL ranks and dump them to console.
+    for (link, rank) in ranks.collect():
+        print "%s has rank: %s." % (link, rank)
diff --git a/examples/src/main/python/pi.py b/examples/src/main/python/pi.py
new file mode 100755
index 0000000000..ab0645fc2f
--- /dev/null
+++ b/examples/src/main/python/pi.py
@@ -0,0 +1,37 @@
+#
+# 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 operator import add
+
+from pyspark import SparkContext
+
+
+if __name__ == "__main__":
+    if len(sys.argv) == 1:
+        print >> sys.stderr, "Usage: pi <master> [<slices>]"
+        exit(-1)
+    sc = SparkContext(sys.argv[1], "PythonPi")
+    slices = int(sys.argv[2]) if len(sys.argv) > 2 else 2
+    n = 100000 * slices
+    def f(_):
+        x = random() * 2 - 1
+        y = random() * 2 - 1
+        return 1 if x ** 2 + y ** 2 < 1 else 0
+    count = sc.parallelize(xrange(1, n+1), slices).map(f).reduce(add)
+    print "Pi is roughly %f" % (4.0 * count / n)
diff --git a/examples/src/main/python/sort.py b/examples/src/main/python/sort.py
new file mode 100755
index 0000000000..5de20a6d98
--- /dev/null
+++ b/examples/src/main/python/sort.py
@@ -0,0 +1,36 @@
+#
+# 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 pyspark import SparkContext
+
+
+if __name__ == "__main__":
+    if len(sys.argv) < 3:
+        print >> sys.stderr, "Usage: sort <master> <file>"
+        exit(-1)
+    sc = SparkContext(sys.argv[1], "PythonSort")
+    lines = sc.textFile(sys.argv[2], 1)
+    sortedCount = lines.flatMap(lambda x: x.split(' ')) \
+                  .map(lambda x: (int(x), 1)) \
+                  .sortByKey(lambda x: x)
+    # This is just a demo on how to bring all the sorted data back to a single node.
+    # In reality, we wouldn't want to collect all the data to the driver node.
+    output = sortedCount.collect()
+    for (num, unitcount) in output:
+        print num
diff --git a/examples/src/main/python/transitive_closure.py b/examples/src/main/python/transitive_closure.py
new file mode 100755
index 0000000000..744cce6651
--- /dev/null
+++ b/examples/src/main/python/transitive_closure.py
@@ -0,0 +1,66 @@
+#
+# 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()
diff --git a/examples/src/main/python/wordcount.py b/examples/src/main/python/wordcount.py
new file mode 100755
index 0000000000..b9139b9d76
--- /dev/null
+++ b/examples/src/main/python/wordcount.py
@@ -0,0 +1,35 @@
+#
+# 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 operator import add
+
+from pyspark import SparkContext
+
+
+if __name__ == "__main__":
+    if len(sys.argv) < 3:
+        print >> sys.stderr, "Usage: wordcount <master> <file>"
+        exit(-1)
+    sc = SparkContext(sys.argv[1], "PythonWordCount")
+    lines = sc.textFile(sys.argv[2], 1)
+    counts = lines.flatMap(lambda x: x.split(' ')) \
+                  .map(lambda x: (x, 1)) \
+                  .reduceByKey(add)
+    output = counts.collect()
+    for (word, count) in output:
+        print "%s: %i" % (word, count)
diff --git a/examples/src/main/scala/org/apache/spark/sql/examples/RDDRelation.scala b/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
index 8210ad977f..ff9254b044 100644
--- a/examples/src/main/scala/org/apache/spark/sql/examples/RDDRelation.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/RDDRelation.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.sql.examples
+package org.apache.spark.examples.sql
 
 import org.apache.spark.SparkContext
 import org.apache.spark.sql.SQLContext
diff --git a/examples/src/main/scala/org/apache/spark/sql/examples/HiveFromSpark.scala b/examples/src/main/scala/org/apache/spark/examples/sql/hive/HiveFromSpark.scala
index 62329bde84..66ce93a26e 100644
--- a/examples/src/main/scala/org/apache/spark/sql/examples/HiveFromSpark.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/sql/hive/HiveFromSpark.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.sql.hive.examples
+package org.apache.spark.examples.sql.hive
 
 import org.apache.spark.SparkContext
 import org.apache.spark.sql._
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/ActorWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/ActorWordCount.scala
index c845dd8904..84cf43df0f 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/ActorWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/ActorWordCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import scala.collection.mutable.LinkedList
 import scala.reflect.ClassTag
@@ -78,7 +78,7 @@ class FeederActor extends Actor {
  * goes and subscribe to a typical publisher/feeder actor and receives
  * data.
  *
- * @see [[org.apache.spark.streaming.examples.FeederActor]]
+ * @see [[org.apache.spark.examples.streaming.FeederActor]]
  */
 class SampleActorReceiver[T: ClassTag](urlOfPublisher: String)
 extends Actor with ActorHelper {
@@ -131,9 +131,9 @@ object FeederActor {
  *   <hostname> and <port> describe the AkkaSystem that Spark Sample feeder is running on.
  *
  * To run this example locally, you may run Feeder Actor as
- *    `$ ./bin/run-example org.apache.spark.streaming.examples.FeederActor 127.0.1.1 9999`
+ *    `$ ./bin/run-example org.apache.spark.examples.streaming.FeederActor 127.0.1.1 9999`
  * and then run the example
- *    `./bin/run-example org.apache.spark.streaming.examples.ActorWordCount local[2] 127.0.1.1 9999`
+ *    `./bin/run-example org.apache.spark.examples.streaming.ActorWordCount local[2] 127.0.1.1 9999`
  */
 object ActorWordCount {
   def main(args: Array[String]) {
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/FlumeEventCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/FlumeEventCount.scala
index 26b6024534..5b2a1035fc 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/FlumeEventCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/FlumeEventCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.apache.spark.storage.StorageLevel
 import org.apache.spark.streaming._
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/HdfsWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/HdfsWordCount.scala
index 7f86fc792a..b440956ba3 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/HdfsWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/HdfsWordCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.apache.spark.streaming.{Seconds, StreamingContext}
 import org.apache.spark.streaming.StreamingContext._
@@ -27,7 +27,7 @@ import org.apache.spark.streaming.StreamingContext._
  *   <directory> is the directory that Spark Streaming will use to find and read new text files.
  *
  * To run this on your local machine on directory `localdir`, run this example
- *    `$ ./bin/run-example org.apache.spark.streaming.examples.HdfsWordCount local[2] localdir`
+ *    `$ ./bin/run-example org.apache.spark.examples.streaming.HdfsWordCount local[2] localdir`
  * Then create a text file in `localdir` and the words in the file will get counted.
  */
 object HdfsWordCount {
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala
index 2aa4f1474a..c3aae5af05 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/KafkaWordCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import java.util.Properties
 
@@ -24,7 +24,6 @@ import kafka.producer._
 import org.apache.spark.streaming._
 import org.apache.spark.streaming.StreamingContext._
 import org.apache.spark.streaming.kafka._
-import org.apache.spark.streaming.util.RawTextHelper._
 
 // scalastyle:off
 /**
@@ -37,7 +36,7 @@ import org.apache.spark.streaming.util.RawTextHelper._
  *   <numThreads> is the number of threads the kafka consumer should use
  *
  * Example:
- *    `./bin/run-example org.apache.spark.streaming.examples.KafkaWordCount local[2] zoo01,zoo02,zoo03 my-consumer-group topic1,topic2 1`
+ *    `./bin/run-example org.apache.spark.examples.streaming.KafkaWordCount local[2] zoo01,zoo02,zoo03 my-consumer-group topic1,topic2 1`
  */
 // scalastyle:on
 object KafkaWordCount {
@@ -59,7 +58,7 @@ object KafkaWordCount {
     val lines = KafkaUtils.createStream(ssc, zkQuorum, group, topicpMap).map(_._2)
     val words = lines.flatMap(_.split(" "))
     val wordCounts = words.map(x => (x, 1L))
-      .reduceByKeyAndWindow(add _, subtract _, Minutes(10), Seconds(2), 2)
+      .reduceByKeyAndWindow(_ + _, _ - _, Minutes(10), Seconds(2), 2)
     wordCounts.print()
 
     ssc.start()
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/MQTTWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/MQTTWordCount.scala
index 62aef0fb47..47bf1e5a06 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/MQTTWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/MQTTWordCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.eclipse.paho.client.mqttv3.{MqttClient, MqttClientPersistence, MqttException, MqttMessage, MqttTopic}
 import org.eclipse.paho.client.mqttv3.persist.MqttDefaultFilePersistence
@@ -79,9 +79,9 @@ object MQTTPublisher {
  *   <MqttbrokerUrl> and <topic> describe where Mqtt publisher is running.
  *
  * To run this example locally, you may run publisher as
- *    `$ ./bin/run-example org.apache.spark.streaming.examples.MQTTPublisher tcp://localhost:1883 foo`
+ *    `$ ./bin/run-example org.apache.spark.examples.streaming.MQTTPublisher tcp://localhost:1883 foo`
  * and run the example as
- *    `$ ./bin/run-example org.apache.spark.streaming.examples.MQTTWordCount local[2] tcp://localhost:1883 foo`
+ *    `$ ./bin/run-example org.apache.spark.examples.streaming.MQTTWordCount local[2] tcp://localhost:1883 foo`
  */
 // scalastyle:on
 object MQTTWordCount {
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/NetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/NetworkWordCount.scala
index 272ab11212..acfe9a4da3 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/NetworkWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/NetworkWordCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.apache.spark.streaming.{Seconds, StreamingContext}
 import org.apache.spark.streaming.StreamingContext._
@@ -32,7 +32,7 @@ import org.apache.spark.storage.StorageLevel
  * To run this on your local machine, you need to first run a Netcat server
  *    `$ nc -lk 9999`
  * and then run the example
- *    `$ ./bin/run-example org.apache.spark.streaming.examples.NetworkWordCount local[2] localhost 9999`
+ *    `$ ./bin/run-example org.apache.spark.examples.streaming.NetworkWordCount local[2] localhost 9999`
  */
 // scalastyle:on
 object NetworkWordCount {
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/QueueStream.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/QueueStream.scala
index ff2a205ec1..f92f72f2de 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/QueueStream.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/QueueStream.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import scala.collection.mutable.SynchronizedQueue
 
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/RawNetworkGrep.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/RawNetworkGrep.scala
index d915c0c39b..1b0319a046 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/RawNetworkGrep.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/RawNetworkGrep.scala
@@ -15,11 +15,10 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.apache.spark.storage.StorageLevel
 import org.apache.spark.streaming._
-import org.apache.spark.streaming.util.RawTextHelper
 import org.apache.spark.util.IntParam
 
 /**
@@ -52,9 +51,6 @@ object RawNetworkGrep {
     val ssc = new StreamingContext(master, "RawNetworkGrep", Milliseconds(batchMillis),
       System.getenv("SPARK_HOME"), StreamingContext.jarOfClass(this.getClass).toSeq)
 
-    // Warm up the JVMs on master and slave for JIT compilation to kick in
-    RawTextHelper.warmUp(ssc.sparkContext)
-
     val rawStreams = (1 to numStreams).map(_ =>
       ssc.rawSocketStream[String](host, port, StorageLevel.MEMORY_ONLY_SER_2)).toArray
     val union = ssc.union(rawStreams)
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/RecoverableNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala
index 4aacbb1991..b0bc31cc66 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/RecoverableNetworkWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/RecoverableNetworkWordCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.apache.spark.streaming.{Time, Seconds, StreamingContext}
 import org.apache.spark.streaming.StreamingContext._
@@ -44,7 +44,7 @@ import java.nio.charset.Charset
  *
  * and run the example as
  *
- *      `$ ./run-example org.apache.spark.streaming.examples.RecoverableNetworkWordCount \
+ *      `$ ./run-example org.apache.spark.examples.streaming.RecoverableNetworkWordCount \
  *              local[2] localhost 9999 ~/checkpoint/ ~/out`
  *
  * If the directory ~/checkpoint/ does not exist (e.g. running for the first time), it will create
@@ -56,7 +56,7 @@ import java.nio.charset.Charset
  *
  *      `$ ./spark-class org.apache.spark.deploy.Client -s launch <cluster-url> \
  *              <path-to-examples-jar> \
- *              org.apache.spark.streaming.examples.RecoverableNetworkWordCount <cluster-url> \
+ *              org.apache.spark.examples.streaming.RecoverableNetworkWordCount <cluster-url> \
  *              localhost 9999 ~/checkpoint ~/out`
  *
  * <path-to-examples-jar> would typically be
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/StatefulNetworkWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala
index ef94c9298d..8001d56c98 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/StatefulNetworkWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.apache.spark.streaming._
 import org.apache.spark.streaming.StreamingContext._
@@ -31,7 +31,7 @@ import org.apache.spark.streaming.StreamingContext._
  * To run this on your local machine, you need to first run a Netcat server
  *    `$ nc -lk 9999`
  * and then run the example
- *    `$ ./bin/run-example org.apache.spark.streaming.examples.StatefulNetworkWordCount local[2] localhost 9999`
+ *    `$ ./bin/run-example org.apache.spark.examples.streaming.StatefulNetworkWordCount local[2] localhost 9999`
  */
 // scalastyle:on
 object StatefulNetworkWordCount {
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/StreamingExamples.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/StreamingExamples.scala
index 99f1502046..8396e65d0d 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/StreamingExamples.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/StreamingExamples.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.apache.spark.Logging
 
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/TwitterAlgebirdCMS.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterAlgebirdCMS.scala
index c38905e8f3..b12617d881 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/TwitterAlgebirdCMS.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterAlgebirdCMS.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import com.twitter.algebird._
 
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/TwitterAlgebirdHLL.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterAlgebirdHLL.scala
index c067046f90..22f232c725 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/TwitterAlgebirdHLL.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterAlgebirdHLL.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import com.twitter.algebird.HyperLogLogMonoid
 import com.twitter.algebird.HyperLogLog._
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/TwitterPopularTags.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala
index 2597c81788..5b58e94600 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/TwitterPopularTags.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/TwitterPopularTags.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import org.apache.spark.streaming.{Seconds, StreamingContext}
 import StreamingContext._
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/ZeroMQWordCount.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/ZeroMQWordCount.scala
index 109ff855b5..de46e5f5b1 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/ZeroMQWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/ZeroMQWordCount.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples
+package org.apache.spark.examples.streaming
 
 import akka.actor.ActorSystem
 import akka.actor.actorRef2Scala
@@ -68,9 +68,9 @@ object SimpleZeroMQPublisher {
  *   <zeroMQurl> and <topic> describe where zeroMq publisher is running.
  *
  * To run this example locally, you may run publisher as
- *    `$ ./bin/run-example org.apache.spark.streaming.examples.SimpleZeroMQPublisher tcp://127.0.1.1:1234 foo.bar`
+ *    `$ ./bin/run-example org.apache.spark.examples.streaming.SimpleZeroMQPublisher tcp://127.0.1.1:1234 foo.bar`
  * and run the example as
- *    `$ ./bin/run-example org.apache.spark.streaming.examples.ZeroMQWordCount local[2] tcp://127.0.1.1:1234 foo`
+ *    `$ ./bin/run-example org.apache.spark.examples.streaming.ZeroMQWordCount local[2] tcp://127.0.1.1:1234 foo`
  */
 // scalastyle:on
 object ZeroMQWordCount {
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/clickstream/PageViewGenerator.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewGenerator.scala
index 251f65fe4d..97e0cb9207 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/clickstream/PageViewGenerator.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewGenerator.scala
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples.clickstream
+package org.apache.spark.examples.streaming.clickstream
 
 import java.net.ServerSocket
 import java.io.PrintWriter
@@ -40,8 +40,8 @@ object PageView extends Serializable {
 /** Generates streaming events to simulate page views on a website.
   *
   * This should be used in tandem with PageViewStream.scala. Example:
-  * $ ./bin/run-example org.apache.spark.streaming.examples.clickstream.PageViewGenerator 44444 10
-  * $ ./bin/run-example org.apache.spark.streaming.examples.clickstream.PageViewStream errorRatePerZipCode localhost 44444
+  * $ ./bin/run-example org.apache.spark.examples.streaming.clickstream.PageViewGenerator 44444 10
+  * $ ./bin/run-example org.apache.spark.examples.streaming.clickstream.PageViewStream errorRatePerZipCode localhost 44444
   *
   * When running this, you may want to set the root logging level to ERROR in
   * conf/log4j.properties to reduce the verbosity of the output.
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/clickstream/PageViewStream.scala b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala
index 673013f7cf..d30ceffbe2 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/clickstream/PageViewStream.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/streaming/clickstream/PageViewStream.scala
@@ -15,19 +15,19 @@
  * limitations under the License.
  */
 
-package org.apache.spark.streaming.examples.clickstream
+package org.apache.spark.examples.streaming.clickstream
 
 import org.apache.spark.SparkContext._
 import org.apache.spark.streaming.{Seconds, StreamingContext}
 import org.apache.spark.streaming.StreamingContext._
-import org.apache.spark.streaming.examples.StreamingExamples
+import org.apache.spark.examples.streaming.StreamingExamples
 // scalastyle:off
 /** Analyses a streaming dataset of web page views. This class demonstrates several types of
   * operators available in Spark streaming.
   *
   * This should be used in tandem with PageViewStream.scala. Example:
-  * $ ./bin/run-example org.apache.spark.streaming.examples.clickstream.PageViewGenerator 44444 10
-  * $ ./bin/run-example org.apache.spark.streaming.examples.clickstream.PageViewStream errorRatePerZipCode localhost 44444
+  * $ ./bin/run-example org.apache.spark.examples.streaming.clickstream.PageViewGenerator 44444 10
+  * $ ./bin/run-example org.apache.spark.examples.streaming.clickstream.PageViewStream errorRatePerZipCode localhost 44444
   */
 // scalastyle:on
 object PageViewStream {