public static void main(String[] args) throws Exception {
// Checking input parameters
final ParameterTool params = ParameterTool.fromArgs(args);
System.out.println(
"Usage: KMeans --points <path> --centroids <path> --output <path> --iterations <n>");
// set up execution environment
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
env.getConfig()
.setGlobalJobParameters(params); // make parameters available in the web interface
// get input data:
// read the points and centroids from the provided paths or fall back to default data
DataSet<Point> points = getPointDataSet(params, env);
DataSet<Centroid> centroids = getCentroidDataSet(params, env);
// set number of bulk iterations for KMeans algorithm
IterativeDataSet<Centroid> loop = centroids.iterate(params.getInt("iterations", 10));
DataSet<Centroid> newCentroids =
points
// compute closest centroid for each point
.map(new SelectNearestCenter())
.withBroadcastSet(loop, "centroids")
// count and sum point coordinates for each centroid
.map(new CountAppender())
.groupBy(0)
.reduce(new CentroidAccumulator())
// compute new centroids from point counts and coordinate sums
.map(new CentroidAverager());
// feed new centroids back into next iteration
DataSet<Centroid> finalCentroids = loop.closeWith(newCentroids);
DataSet<Tuple2<Integer, Point>> clusteredPoints =
points
// assign points to final clusters
.map(new SelectNearestCenter())
.withBroadcastSet(finalCentroids, "centroids");
// emit result
if (params.has("output")) {
clusteredPoints.writeAsCsv(params.get("output"), "\n", " ");
// since file sinks are lazy, we trigger the execution explicitly
env.execute("KMeans Example");
} else {
System.out.println("Printing result to stdout. Use --output to specify output path.");
clusteredPoints.print();
}
}
@Override
protected void testProgram() throws Exception {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
DataSet<Record> initialInput =
env.readFile(new PointInFormat(), this.dataPath).setParallelism(1);
IterativeDataSet<Record> iteration = initialInput.iterate(2);
DataSet<Record> result = iteration.union(iteration).map(new IdentityMapper());
iteration.closeWith(result).write(new PointOutFormat(), this.resultPath);
env.execute();
}
@Override
protected void testProgram() throws Exception {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
env.setDegreeOfParallelism(4);
DataSet<Integer> data = env.fromElements(1, 2, 3, 4, 5, 6, 7, 8);
IterativeDataSet<Integer> iteration = data.iterate(10);
DataSet<Integer> result =
data.reduceGroup(new PickOneAllReduce()).withBroadcastSet(iteration, "bc");
final List<Integer> resultList = new ArrayList<Integer>();
iteration.closeWith(result).output(new LocalCollectionOutputFormat<Integer>(resultList));
env.execute();
Assert.assertEquals(8, resultList.get(0).intValue());
}
