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author | Matei Zaharia <matei@eecs.berkeley.edu> | 2013-08-31 19:27:07 -0700 |
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committer | Matei Zaharia <matei@eecs.berkeley.edu> | 2013-09-01 14:13:13 -0700 |
commit | 46eecd110a4017ea0c86cbb1010d0ccd6a5eb2ef (patch) | |
tree | 4a46971b36680bc5ef51be81ada8eb47670f6b22 /examples/src/main/java/org | |
parent | a30fac16ca0525f2001b127e5f9518c9680844c9 (diff) | |
download | spark-46eecd110a4017ea0c86cbb1010d0ccd6a5eb2ef.tar.gz spark-46eecd110a4017ea0c86cbb1010d0ccd6a5eb2ef.tar.bz2 spark-46eecd110a4017ea0c86cbb1010d0ccd6a5eb2ef.zip |
Initial work to rename package to org.apache.spark
Diffstat (limited to 'examples/src/main/java/org')
13 files changed, 1225 insertions, 0 deletions
diff --git a/examples/src/main/java/org/apache/spark/examples/JavaHdfsLR.java b/examples/src/main/java/org/apache/spark/examples/JavaHdfsLR.java new file mode 100644 index 0000000000..be0d38589c --- /dev/null +++ b/examples/src/main/java/org/apache/spark/examples/JavaHdfsLR.java @@ -0,0 +1,140 @@ +/* + * 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.examples; + +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.Function; +import org.apache.spark.api.java.function.Function2; + +import java.io.Serializable; +import java.util.Arrays; +import java.util.StringTokenizer; +import java.util.Random; + +/** + * Logistic regression based classification. + */ +public class JavaHdfsLR { + + static int D = 10; // Number of dimensions + static Random rand = new Random(42); + + static class DataPoint implements Serializable { + public DataPoint(double[] x, double y) { + this.x = x; + this.y = y; + } + + double[] x; + double y; + } + + static class ParsePoint extends Function<String, DataPoint> { + public DataPoint call(String line) { + StringTokenizer tok = new StringTokenizer(line, " "); + double y = Double.parseDouble(tok.nextToken()); + double[] x = new double[D]; + int i = 0; + while (i < D) { + x[i] = Double.parseDouble(tok.nextToken()); + i += 1; + } + return new DataPoint(x, y); + } + } + + static class VectorSum extends Function2<double[], double[], double[]> { + public double[] call(double[] a, double[] b) { + double[] result = new double[D]; + for (int j = 0; j < D; j++) { + result[j] = a[j] + b[j]; + } + return result; + } + } + + static class ComputeGradient extends Function<DataPoint, double[]> { + double[] weights; + + public ComputeGradient(double[] weights) { + this.weights = weights; + } + + public double[] call(DataPoint p) { + double[] gradient = new double[D]; + for (int i = 0; i < D; i++) { + double dot = dot(weights, p.x); + gradient[i] = (1 / (1 + Math.exp(-p.y * dot)) - 1) * p.y * p.x[i]; + } + return gradient; + } + } + + public static double dot(double[] a, double[] b) { + double x = 0; + for (int i = 0; i < D; i++) { + x += a[i] * b[i]; + } + return x; + } + + public static void printWeights(double[] a) { + System.out.println(Arrays.toString(a)); + } + + public static void main(String[] args) { + + if (args.length < 3) { + System.err.println("Usage: JavaHdfsLR <master> <file> <iters>"); + System.exit(1); + } + + JavaSparkContext sc = new JavaSparkContext(args[0], "JavaHdfsLR", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + JavaRDD<String> lines = sc.textFile(args[1]); + JavaRDD<DataPoint> points = lines.map(new ParsePoint()).cache(); + int ITERATIONS = Integer.parseInt(args[2]); + + // Initialize w to a random value + double[] w = new double[D]; + for (int i = 0; i < D; i++) { + w[i] = 2 * rand.nextDouble() - 1; + } + + System.out.print("Initial w: "); + printWeights(w); + + for (int i = 1; i <= ITERATIONS; i++) { + System.out.println("On iteration " + i); + + double[] gradient = points.map( + new ComputeGradient(w) + ).reduce(new VectorSum()); + + for (int j = 0; j < D; j++) { + w[j] -= gradient[j]; + } + + } + + System.out.print("Final w: "); + printWeights(w); + System.exit(0); + } +} diff --git a/examples/src/main/java/org/apache/spark/examples/JavaKMeans.java b/examples/src/main/java/org/apache/spark/examples/JavaKMeans.java new file mode 100644 index 0000000000..5a6afe7eae --- /dev/null +++ b/examples/src/main/java/org/apache/spark/examples/JavaKMeans.java @@ -0,0 +1,131 @@ +/* + * 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.examples; + +import scala.Tuple2; +import org.apache.spark.api.java.JavaPairRDD; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.Function; +import org.apache.spark.api.java.function.PairFunction; +import org.apache.spark.util.Vector; + +import java.util.List; +import java.util.Map; + +/** + * K-means clustering using Java API. + */ +public class JavaKMeans { + + /** Parses numbers split by whitespace to a vector */ + static Vector parseVector(String line) { + String[] splits = line.split(" "); + double[] data = new double[splits.length]; + int i = 0; + for (String s : splits) + data[i] = Double.parseDouble(splits[i++]); + return new Vector(data); + } + + /** Computes the vector to which the input vector is closest using squared distance */ + static int closestPoint(Vector p, List<Vector> centers) { + int bestIndex = 0; + double closest = Double.POSITIVE_INFINITY; + for (int i = 0; i < centers.size(); i++) { + double tempDist = p.squaredDist(centers.get(i)); + if (tempDist < closest) { + closest = tempDist; + bestIndex = i; + } + } + return bestIndex; + } + + /** Computes the mean across all vectors in the input set of vectors */ + static Vector average(List<Vector> ps) { + int numVectors = ps.size(); + Vector out = new Vector(ps.get(0).elements()); + // start from i = 1 since we already copied index 0 above + for (int i = 1; i < numVectors; i++) { + out.addInPlace(ps.get(i)); + } + return out.divide(numVectors); + } + + public static void main(String[] args) throws Exception { + if (args.length < 4) { + System.err.println("Usage: JavaKMeans <master> <file> <k> <convergeDist>"); + System.exit(1); + } + JavaSparkContext sc = new JavaSparkContext(args[0], "JavaKMeans", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + String path = args[1]; + int K = Integer.parseInt(args[2]); + double convergeDist = Double.parseDouble(args[3]); + + JavaRDD<Vector> data = sc.textFile(path).map( + new Function<String, Vector>() { + @Override + public Vector call(String line) throws Exception { + return parseVector(line); + } + } + ).cache(); + + final List<Vector> centroids = data.takeSample(false, K, 42); + + double tempDist; + do { + // allocate each vector to closest centroid + JavaPairRDD<Integer, Vector> closest = data.map( + new PairFunction<Vector, Integer, Vector>() { + @Override + public Tuple2<Integer, Vector> call(Vector vector) throws Exception { + return new Tuple2<Integer, Vector>( + closestPoint(vector, centroids), vector); + } + } + ); + + // group by cluster id and average the vectors within each cluster to compute centroids + JavaPairRDD<Integer, List<Vector>> pointsGroup = closest.groupByKey(); + Map<Integer, Vector> newCentroids = pointsGroup.mapValues( + new Function<List<Vector>, Vector>() { + public Vector call(List<Vector> ps) throws Exception { + return average(ps); + } + }).collectAsMap(); + tempDist = 0.0; + for (int i = 0; i < K; i++) { + tempDist += centroids.get(i).squaredDist(newCentroids.get(i)); + } + for (Map.Entry<Integer, Vector> t: newCentroids.entrySet()) { + centroids.set(t.getKey(), t.getValue()); + } + System.out.println("Finished iteration (delta = " + tempDist + ")"); + } while (tempDist > convergeDist); + + System.out.println("Final centers:"); + for (Vector c : centroids) + System.out.println(c); + + System.exit(0); + + } +} diff --git a/examples/src/main/java/org/apache/spark/examples/JavaLogQuery.java b/examples/src/main/java/org/apache/spark/examples/JavaLogQuery.java new file mode 100644 index 0000000000..152f029213 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/examples/JavaLogQuery.java @@ -0,0 +1,131 @@ +/* + * 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.examples; + +import com.google.common.collect.Lists; +import scala.Tuple2; +import scala.Tuple3; +import org.apache.spark.api.java.JavaPairRDD; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.Function2; +import org.apache.spark.api.java.function.PairFunction; + +import java.io.Serializable; +import java.util.Collections; +import java.util.List; +import java.util.regex.Matcher; +import java.util.regex.Pattern; + +/** + * Executes a roll up-style query against Apache logs. + */ +public class JavaLogQuery { + + public static List<String> exampleApacheLogs = Lists.newArrayList( + "10.10.10.10 - \"FRED\" [18/Jan/2013:17:56:07 +1100] \"GET http://images.com/2013/Generic.jpg " + + "HTTP/1.1\" 304 315 \"http://referall.com/\" \"Mozilla/4.0 (compatible; MSIE 7.0; " + + "Windows NT 5.1; GTB7.4; .NET CLR 2.0.50727; .NET CLR 3.0.04506.30; .NET CLR 3.0.04506.648; " + + ".NET CLR 3.5.21022; .NET CLR 3.0.4506.2152; .NET CLR 1.0.3705; .NET CLR 1.1.4322; .NET CLR " + + "3.5.30729; Release=ARP)\" \"UD-1\" - \"image/jpeg\" \"whatever\" 0.350 \"-\" - \"\" 265 923 934 \"\" " + + "62.24.11.25 images.com 1358492167 - Whatup", + "10.10.10.10 - \"FRED\" [18/Jan/2013:18:02:37 +1100] \"GET http://images.com/2013/Generic.jpg " + + "HTTP/1.1\" 304 306 \"http:/referall.com\" \"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; " + + "GTB7.4; .NET CLR 2.0.50727; .NET CLR 3.0.04506.30; .NET CLR 3.0.04506.648; .NET CLR " + + "3.5.21022; .NET CLR 3.0.4506.2152; .NET CLR 1.0.3705; .NET CLR 1.1.4322; .NET CLR " + + "3.5.30729; Release=ARP)\" \"UD-1\" - \"image/jpeg\" \"whatever\" 0.352 \"-\" - \"\" 256 977 988 \"\" " + + "0 73.23.2.15 images.com 1358492557 - Whatup"); + + public static Pattern apacheLogRegex = Pattern.compile( + "^([\\d.]+) (\\S+) (\\S+) \\[([\\w\\d:/]+\\s[+\\-]\\d{4})\\] \"(.+?)\" (\\d{3}) ([\\d\\-]+) \"([^\"]+)\" \"([^\"]+)\".*"); + + /** Tracks the total query count and number of aggregate bytes for a particular group. */ + public static class Stats implements Serializable { + + private int count; + private int numBytes; + + public Stats(int count, int numBytes) { + this.count = count; + this.numBytes = numBytes; + } + public Stats merge(Stats other) { + return new Stats(count + other.count, numBytes + other.numBytes); + } + + public String toString() { + return String.format("bytes=%s\tn=%s", numBytes, count); + } + } + + public static Tuple3<String, String, String> extractKey(String line) { + Matcher m = apacheLogRegex.matcher(line); + List<String> key = Collections.emptyList(); + if (m.find()) { + String ip = m.group(1); + String user = m.group(3); + String query = m.group(5); + if (!user.equalsIgnoreCase("-")) { + return new Tuple3<String, String, String>(ip, user, query); + } + } + return new Tuple3<String, String, String>(null, null, null); + } + + public static Stats extractStats(String line) { + Matcher m = apacheLogRegex.matcher(line); + if (m.find()) { + int bytes = Integer.parseInt(m.group(7)); + return new Stats(1, bytes); + } + else + return new Stats(1, 0); + } + + public static void main(String[] args) throws Exception { + if (args.length == 0) { + System.err.println("Usage: JavaLogQuery <master> [logFile]"); + System.exit(1); + } + + JavaSparkContext jsc = new JavaSparkContext(args[0], "JavaLogQuery", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + + JavaRDD<String> dataSet = (args.length == 2) ? jsc.textFile(args[1]) : jsc.parallelize(exampleApacheLogs); + + JavaPairRDD<Tuple3<String, String, String>, Stats> extracted = dataSet.map(new PairFunction<String, Tuple3<String, String, String>, Stats>() { + @Override + public Tuple2<Tuple3<String, String, String>, Stats> call(String s) throws Exception { + return new Tuple2<Tuple3<String, String, String>, Stats>(extractKey(s), extractStats(s)); + } + }); + + JavaPairRDD<Tuple3<String, String, String>, Stats> counts = extracted.reduceByKey(new Function2<Stats, Stats, Stats>() { + @Override + public Stats call(Stats stats, Stats stats2) throws Exception { + return stats.merge(stats2); + } + }); + + List<Tuple2<Tuple3<String, String, String>, Stats>> output = counts.collect(); + for (Tuple2 t : output) { + System.out.println(t._1 + "\t" + t._2); + } + System.exit(0); + } +} diff --git a/examples/src/main/java/org/apache/spark/examples/JavaPageRank.java b/examples/src/main/java/org/apache/spark/examples/JavaPageRank.java new file mode 100644 index 0000000000..c5603a639b --- /dev/null +++ b/examples/src/main/java/org/apache/spark/examples/JavaPageRank.java @@ -0,0 +1,115 @@ +/* + * 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.examples; + +import scala.Tuple2; +import org.apache.spark.api.java.JavaPairRDD; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +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.PairFlatMapFunction; +import org.apache.spark.api.java.function.PairFunction; + +import java.util.List; +import java.util.ArrayList; + +/** + * Computes the PageRank of URLs from an input file. Input file should + * be in format of: + * URL neighbor URL + * URL neighbor URL + * URL neighbor URL + * ... + * where URL and their neighbors are separated by space(s). + */ +public class JavaPageRank { + private static class Sum extends Function2<Double, Double, Double> { + @Override + public Double call(Double a, Double b) { + return a + b; + } + } + + public static void main(String[] args) throws Exception { + if (args.length < 3) { + System.err.println("Usage: JavaPageRank <master> <file> <number_of_iterations>"); + System.exit(1); + } + + JavaSparkContext ctx = new JavaSparkContext(args[0], "JavaPageRank", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + + // Loads in input file. It should be in format of: + // URL neighbor URL + // URL neighbor URL + // URL neighbor URL + // ... + JavaRDD<String> lines = ctx.textFile(args[1], 1); + + // Loads all URLs from input file and initialize their neighbors. + JavaPairRDD<String, List<String>> links = lines.map(new PairFunction<String, String, String>() { + @Override + public Tuple2<String, String> call(String s) { + String[] parts = s.split("\\s+"); + return new Tuple2<String, String>(parts[0], parts[1]); + } + }).distinct().groupByKey().cache(); + + // Loads all URLs with other URL(s) link to from input file and initialize ranks of them to one. + JavaPairRDD<String, Double> ranks = links.mapValues(new Function<List<String>, Double>() { + @Override + public Double call(List<String> rs) throws Exception { + return 1.0; + } + }); + + // Calculates and updates URL ranks continuously using PageRank algorithm. + for (int current = 0; current < Integer.parseInt(args[2]); current++) { + // Calculates URL contributions to the rank of other URLs. + JavaPairRDD<String, Double> contribs = links.join(ranks).values() + .flatMap(new PairFlatMapFunction<Tuple2<List<String>, Double>, String, Double>() { + @Override + public Iterable<Tuple2<String, Double>> call(Tuple2<List<String>, Double> s) { + List<Tuple2<String, Double>> results = new ArrayList<Tuple2<String, Double>>(); + for (String n : s._1) { + results.add(new Tuple2<String, Double>(n, s._2 / s._1.size())); + } + return results; + } + }); + + // Re-calculates URL ranks based on neighbor contributions. + ranks = contribs.reduceByKey(new Sum()).mapValues(new Function<Double, Double>() { + @Override + public Double call(Double sum) throws Exception { + return 0.15 + sum * 0.85; + } + }); + } + + // Collects all URL ranks and dump them to console. + List<Tuple2<String, Double>> output = ranks.collect(); + for (Tuple2 tuple : output) { + System.out.println(tuple._1 + " has rank: " + tuple._2 + "."); + } + + System.exit(0); + } +} diff --git a/examples/src/main/java/org/apache/spark/examples/JavaSparkPi.java b/examples/src/main/java/org/apache/spark/examples/JavaSparkPi.java new file mode 100644 index 0000000000..4a2380caf5 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/examples/JavaSparkPi.java @@ -0,0 +1,65 @@ +/* + * 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.examples; + +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.Function; +import org.apache.spark.api.java.function.Function2; + +import java.util.ArrayList; +import java.util.List; + +/** Computes an approximation to pi */ +public class JavaSparkPi { + + + public static void main(String[] args) throws Exception { + if (args.length == 0) { + System.err.println("Usage: JavaLogQuery <master> [slices]"); + System.exit(1); + } + + JavaSparkContext jsc = new JavaSparkContext(args[0], "JavaLogQuery", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + + int slices = (args.length == 2) ? Integer.parseInt(args[1]) : 2; + int n = 100000 * slices; + List<Integer> l = new ArrayList<Integer>(n); + for (int i = 0; i < n; i++) + l.add(i); + + JavaRDD<Integer> dataSet = jsc.parallelize(l, slices); + + int count = dataSet.map(new Function<Integer, Integer>() { + @Override + public Integer call(Integer integer) throws Exception { + double x = Math.random() * 2 - 1; + double y = Math.random() * 2 - 1; + return (x * x + y * y < 1) ? 1 : 0; + } + }).reduce(new Function2<Integer, Integer, Integer>() { + @Override + public Integer call(Integer integer, Integer integer2) throws Exception { + return integer + integer2; + } + }); + + System.out.println("Pi is roughly " + 4.0 * count / n); + } +} diff --git a/examples/src/main/java/org/apache/spark/examples/JavaTC.java b/examples/src/main/java/org/apache/spark/examples/JavaTC.java new file mode 100644 index 0000000000..17f21f6b77 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/examples/JavaTC.java @@ -0,0 +1,97 @@ +/* + * 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.examples; + +import scala.Tuple2; +import org.apache.spark.api.java.JavaPairRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.PairFunction; + +import java.util.ArrayList; +import java.util.HashSet; +import java.util.List; +import java.util.Random; +import java.util.Set; + +/** + * Transitive closure on a graph, implemented in Java. + */ +public class JavaTC { + + static int numEdges = 200; + static int numVertices = 100; + static Random rand = new Random(42); + + static List<Tuple2<Integer, Integer>> generateGraph() { + Set<Tuple2<Integer, Integer>> edges = new HashSet<Tuple2<Integer, Integer>>(numEdges); + while (edges.size() < numEdges) { + int from = rand.nextInt(numVertices); + int to = rand.nextInt(numVertices); + Tuple2<Integer, Integer> e = new Tuple2<Integer, Integer>(from, to); + if (from != to) edges.add(e); + } + return new ArrayList<Tuple2<Integer, Integer>>(edges); + } + + static class ProjectFn extends PairFunction<Tuple2<Integer, Tuple2<Integer, Integer>>, + Integer, Integer> { + static ProjectFn INSTANCE = new ProjectFn(); + + public Tuple2<Integer, Integer> call(Tuple2<Integer, Tuple2<Integer, Integer>> triple) { + return new Tuple2<Integer, Integer>(triple._2()._2(), triple._2()._1()); + } + } + + public static void main(String[] args) { + if (args.length == 0) { + System.err.println("Usage: JavaTC <host> [<slices>]"); + System.exit(1); + } + + JavaSparkContext sc = new JavaSparkContext(args[0], "JavaTC", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + Integer slices = (args.length > 1) ? Integer.parseInt(args[1]): 2; + JavaPairRDD<Integer, Integer> tc = sc.parallelizePairs(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. + JavaPairRDD<Integer, Integer> edges = tc.map( + new PairFunction<Tuple2<Integer, Integer>, Integer, Integer>() { + public Tuple2<Integer, Integer> call(Tuple2<Integer, Integer> e) { + return new Tuple2<Integer, Integer>(e._2(), e._1()); + } + }); + + long oldCount = 0; + long nextCount = tc.count(); + do { + oldCount = nextCount; + // Perform the join, obtaining an RDD of (y, (z, x)) pairs, + // then project the result to obtain the new (x, z) paths. + tc = tc.union(tc.join(edges).map(ProjectFn.INSTANCE)).distinct().cache(); + nextCount = tc.count(); + } while (nextCount != oldCount); + + System.out.println("TC has " + tc.count() + " edges."); + System.exit(0); + } +} diff --git a/examples/src/main/java/org/apache/spark/examples/JavaWordCount.java b/examples/src/main/java/org/apache/spark/examples/JavaWordCount.java new file mode 100644 index 0000000000..07d32ad659 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/examples/JavaWordCount.java @@ -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. + */ + +package org.apache.spark.examples; + +import scala.Tuple2; +import org.apache.spark.api.java.JavaPairRDD; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +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 java.util.Arrays; +import java.util.List; + +public class JavaWordCount { + public static void main(String[] args) throws Exception { + if (args.length < 2) { + System.err.println("Usage: JavaWordCount <master> <file>"); + System.exit(1); + } + + JavaSparkContext ctx = new JavaSparkContext(args[0], "JavaWordCount", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + JavaRDD<String> lines = ctx.textFile(args[1], 1); + + JavaRDD<String> words = lines.flatMap(new FlatMapFunction<String, String>() { + public Iterable<String> call(String s) { + return Arrays.asList(s.split(" ")); + } + }); + + JavaPairRDD<String, Integer> ones = words.map(new PairFunction<String, String, Integer>() { + public Tuple2<String, Integer> call(String s) { + return new Tuple2<String, Integer>(s, 1); + } + }); + + JavaPairRDD<String, Integer> counts = ones.reduceByKey(new Function2<Integer, Integer, Integer>() { + public Integer call(Integer i1, Integer i2) { + return i1 + i2; + } + }); + + List<Tuple2<String, Integer>> output = counts.collect(); + for (Tuple2 tuple : output) { + System.out.println(tuple._1 + ": " + tuple._2); + } + System.exit(0); + } +} diff --git a/examples/src/main/java/org/apache/spark/mllib/examples/JavaALS.java b/examples/src/main/java/org/apache/spark/mllib/examples/JavaALS.java new file mode 100644 index 0000000000..628cb892b6 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/mllib/examples/JavaALS.java @@ -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. + */ + +package org.apache.spark.mllib.examples; + +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.Function; + +import org.apache.spark.mllib.recommendation.ALS; +import org.apache.spark.mllib.recommendation.MatrixFactorizationModel; +import org.apache.spark.mllib.recommendation.Rating; + +import java.io.Serializable; +import java.util.Arrays; +import java.util.StringTokenizer; + +import scala.Tuple2; + +/** + * Example using MLLib ALS from Java. + */ +public class JavaALS { + + static class ParseRating extends Function<String, Rating> { + public Rating call(String line) { + StringTokenizer tok = new StringTokenizer(line, ","); + int x = Integer.parseInt(tok.nextToken()); + int y = Integer.parseInt(tok.nextToken()); + double rating = Double.parseDouble(tok.nextToken()); + return new Rating(x, y, rating); + } + } + + static class FeaturesToString extends Function<Tuple2<Object, double[]>, String> { + public String call(Tuple2<Object, double[]> element) { + return element._1().toString() + "," + Arrays.toString(element._2()); + } + } + + public static void main(String[] args) { + + if (args.length != 5 && args.length != 6) { + System.err.println( + "Usage: JavaALS <master> <ratings_file> <rank> <iterations> <output_dir> [<blocks>]"); + System.exit(1); + } + + int rank = Integer.parseInt(args[2]); + int iterations = Integer.parseInt(args[3]); + String outputDir = args[4]; + int blocks = -1; + if (args.length == 6) { + blocks = Integer.parseInt(args[5]); + } + + JavaSparkContext sc = new JavaSparkContext(args[0], "JavaALS", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + JavaRDD<String> lines = sc.textFile(args[1]); + + JavaRDD<Rating> ratings = lines.map(new ParseRating()); + + MatrixFactorizationModel model = ALS.train(ratings.rdd(), rank, iterations, 0.01, blocks); + + model.userFeatures().toJavaRDD().map(new FeaturesToString()).saveAsTextFile( + outputDir + "/userFeatures"); + model.productFeatures().toJavaRDD().map(new FeaturesToString()).saveAsTextFile( + outputDir + "/productFeatures"); + System.out.println("Final user/product features written to " + outputDir); + + System.exit(0); + } +} diff --git a/examples/src/main/java/org/apache/spark/mllib/examples/JavaKMeans.java b/examples/src/main/java/org/apache/spark/mllib/examples/JavaKMeans.java new file mode 100644 index 0000000000..cd59a139b9 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/mllib/examples/JavaKMeans.java @@ -0,0 +1,81 @@ +/* + * 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.mllib.examples; + +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.Function; + +import org.apache.spark.mllib.clustering.KMeans; +import org.apache.spark.mllib.clustering.KMeansModel; + +import java.util.Arrays; +import java.util.StringTokenizer; + +/** + * Example using MLLib KMeans from Java. + */ +public class JavaKMeans { + + static class ParsePoint extends Function<String, double[]> { + public double[] call(String line) { + StringTokenizer tok = new StringTokenizer(line, " "); + int numTokens = tok.countTokens(); + double[] point = new double[numTokens]; + for (int i = 0; i < numTokens; ++i) { + point[i] = Double.parseDouble(tok.nextToken()); + } + return point; + } + } + + public static void main(String[] args) { + + if (args.length < 4) { + System.err.println( + "Usage: JavaKMeans <master> <input_file> <k> <max_iterations> [<runs>]"); + System.exit(1); + } + + String inputFile = args[1]; + int k = Integer.parseInt(args[2]); + int iterations = Integer.parseInt(args[3]); + int runs = 1; + + if (args.length >= 5) { + runs = Integer.parseInt(args[4]); + } + + JavaSparkContext sc = new JavaSparkContext(args[0], "JavaKMeans", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + JavaRDD<String> lines = sc.textFile(args[1]); + + JavaRDD<double[]> points = lines.map(new ParsePoint()); + + KMeansModel model = KMeans.train(points.rdd(), k, iterations, runs); + + System.out.println("Cluster centers:"); + for (double[] center : model.clusterCenters()) { + System.out.println(" " + Arrays.toString(center)); + } + double cost = model.computeCost(points.rdd()); + System.out.println("Cost: " + cost); + + System.exit(0); + } +} diff --git a/examples/src/main/java/org/apache/spark/mllib/examples/JavaLR.java b/examples/src/main/java/org/apache/spark/mllib/examples/JavaLR.java new file mode 100644 index 0000000000..258061c8e6 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/mllib/examples/JavaLR.java @@ -0,0 +1,85 @@ +/* + * 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.mllib.examples; + + +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.Function; + +import org.apache.spark.mllib.classification.LogisticRegressionWithSGD; +import org.apache.spark.mllib.classification.LogisticRegressionModel; +import org.apache.spark.mllib.regression.LabeledPoint; + +import java.util.Arrays; +import java.util.StringTokenizer; + +/** + * Logistic regression based classification using ML Lib. + */ +public class JavaLR { + + static class ParsePoint extends Function<String, LabeledPoint> { + public LabeledPoint call(String line) { + String[] parts = line.split(","); + double y = Double.parseDouble(parts[0]); + StringTokenizer tok = new StringTokenizer(parts[1], " "); + int numTokens = tok.countTokens(); + double[] x = new double[numTokens]; + for (int i = 0; i < numTokens; ++i) { + x[i] = Double.parseDouble(tok.nextToken()); + } + return new LabeledPoint(y, x); + } + } + + public static void printWeights(double[] a) { + System.out.println(Arrays.toString(a)); + } + + public static void main(String[] args) { + if (args.length != 4) { + System.err.println("Usage: JavaLR <master> <input_dir> <step_size> <niters>"); + System.exit(1); + } + + JavaSparkContext sc = new JavaSparkContext(args[0], "JavaLR", + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + JavaRDD<String> lines = sc.textFile(args[1]); + JavaRDD<LabeledPoint> points = lines.map(new ParsePoint()).cache(); + double stepSize = Double.parseDouble(args[2]); + int iterations = Integer.parseInt(args[3]); + + // Another way to configure LogisticRegression + // + // LogisticRegressionWithSGD lr = new LogisticRegressionWithSGD(); + // lr.optimizer().setNumIterations(iterations) + // .setStepSize(stepSize) + // .setMiniBatchFraction(1.0); + // lr.setIntercept(true); + // LogisticRegressionModel model = lr.train(points.rdd()); + + LogisticRegressionModel model = LogisticRegressionWithSGD.train(points.rdd(), + iterations, stepSize); + + System.out.print("Final w: "); + printWeights(model.weights()); + + System.exit(0); + } +} diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaFlumeEventCount.java b/examples/src/main/java/org/apache/spark/streaming/examples/JavaFlumeEventCount.java new file mode 100644 index 0000000000..261813bf2f --- /dev/null +++ b/examples/src/main/java/org/apache/spark/streaming/examples/JavaFlumeEventCount.java @@ -0,0 +1,68 @@ +/* + * 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.streaming.examples; + +import org.apache.spark.api.java.function.Function; +import org.apache.spark.streaming.*; +import org.apache.spark.streaming.api.java.*; +import org.apache.spark.streaming.dstream.SparkFlumeEvent; + +/** + * Produces a count of events received from Flume. + * + * This should be used in conjunction with an AvroSink in Flume. It will start + * an Avro server on at the request host:port address and listen for requests. + * Your Flume AvroSink should be pointed to this address. + * + * Usage: JavaFlumeEventCount <master> <host> <port> + * + * <master> is a Spark master URL + * <host> is the host the Flume receiver will be started on - a receiver + * creates a server and listens for flume events. + * <port> is the port the Flume receiver will listen on. + */ +public class JavaFlumeEventCount { + public static void main(String[] args) { + if (args.length != 3) { + System.err.println("Usage: JavaFlumeEventCount <master> <host> <port>"); + System.exit(1); + } + + String master = args[0]; + String host = args[1]; + int port = Integer.parseInt(args[2]); + + Duration batchInterval = new Duration(2000); + + JavaStreamingContext sc = new JavaStreamingContext(master, "FlumeEventCount", batchInterval, + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + + JavaDStream<SparkFlumeEvent> flumeStream = sc.flumeStream("localhost", port); + + flumeStream.count(); + + flumeStream.count().map(new Function<Long, String>() { + @Override + public String call(Long in) { + return "Received " + in + " flume events."; + } + }).print(); + + sc.start(); + } +} diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaNetworkWordCount.java b/examples/src/main/java/org/apache/spark/streaming/examples/JavaNetworkWordCount.java new file mode 100644 index 0000000000..def87c199b --- /dev/null +++ b/examples/src/main/java/org/apache/spark/streaming/examples/JavaNetworkWordCount.java @@ -0,0 +1,79 @@ +/* + * 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.streaming.examples; + +import com.google.common.collect.Lists; +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.streaming.Duration; +import org.apache.spark.streaming.api.java.JavaDStream; +import org.apache.spark.streaming.api.java.JavaPairDStream; +import org.apache.spark.streaming.api.java.JavaStreamingContext; + +/** + * Counts words in UTF8 encoded, '\n' delimited text received from the network every second. + * Usage: NetworkWordCount <master> <hostname> <port> + * <master> is the Spark master URL. In local mode, <master> should be 'local[n]' with n > 1. + * <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive data. + * + * To run this on your local machine, you need to first run a Netcat server + * `$ nc -lk 9999` + * and then run the example + * `$ ./run spark.streaming.examples.JavaNetworkWordCount local[2] localhost 9999` + */ +public class JavaNetworkWordCount { + public static void main(String[] args) { + if (args.length < 3) { + System.err.println("Usage: NetworkWordCount <master> <hostname> <port>\n" + + "In local mode, <master> should be 'local[n]' with n > 1"); + System.exit(1); + } + + // Create the context with a 1 second batch size + JavaStreamingContext ssc = new JavaStreamingContext(args[0], "NetworkWordCount", + new Duration(1000), System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + + // Create a NetworkInputDStream on target ip:port and count the + // words in input stream of \n delimited test (eg. generated by 'nc') + JavaDStream<String> lines = ssc.socketTextStream(args[1], Integer.parseInt(args[2])); + JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() { + @Override + public Iterable<String> call(String x) { + return Lists.newArrayList(x.split(" ")); + } + }); + JavaPairDStream<String, Integer> wordCounts = words.map( + new PairFunction<String, String, Integer>() { + @Override + public Tuple2<String, Integer> call(String s) throws Exception { + return new Tuple2<String, Integer>(s, 1); + } + }).reduceByKey(new Function2<Integer, Integer, Integer>() { + @Override + public Integer call(Integer i1, Integer i2) throws Exception { + return i1 + i2; + } + }); + + wordCounts.print(); + ssc.start(); + + } +} diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaQueueStream.java b/examples/src/main/java/org/apache/spark/streaming/examples/JavaQueueStream.java new file mode 100644 index 0000000000..c8c7389dd1 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/streaming/examples/JavaQueueStream.java @@ -0,0 +1,80 @@ +/* + * 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.streaming.examples; + +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.streaming.Duration; +import org.apache.spark.streaming.api.java.JavaDStream; +import org.apache.spark.streaming.api.java.JavaPairDStream; +import org.apache.spark.streaming.api.java.JavaStreamingContext; + +import java.util.LinkedList; +import java.util.List; +import java.util.Queue; + +public class JavaQueueStream { + public static void main(String[] args) throws InterruptedException { + if (args.length < 1) { + System.err.println("Usage: JavaQueueStream <master>"); + System.exit(1); + } + + // Create the context + JavaStreamingContext ssc = new JavaStreamingContext(args[0], "QueueStream", new Duration(1000), + System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR")); + + // Create the queue through which RDDs can be pushed to + // a QueueInputDStream + Queue<JavaRDD<Integer>> rddQueue = new LinkedList<JavaRDD<Integer>>(); + + // Create and push some RDDs into the queue + List<Integer> list = Lists.newArrayList(); + for (int i = 0; i < 1000; i++) { + list.add(i); + } + + for (int i = 0; i < 30; i++) { + rddQueue.add(ssc.sc().parallelize(list)); + } + + + // Create the QueueInputDStream and use it do some processing + JavaDStream<Integer> inputStream = ssc.queueStream(rddQueue); + JavaPairDStream<Integer, Integer> mappedStream = inputStream.map( + new PairFunction<Integer, Integer, Integer>() { + @Override + public Tuple2<Integer, Integer> call(Integer i) throws Exception { + return new Tuple2<Integer, Integer>(i % 10, 1); + } + }); + JavaPairDStream<Integer, Integer> reducedStream = mappedStream.reduceByKey( + new Function2<Integer, Integer, Integer>() { + @Override + public Integer call(Integer i1, Integer i2) throws Exception { + return i1 + i2; + } + }); + + reducedStream.print(); + ssc.start(); + } +} |