@Test
public void testCrossWithLarge() {
// construct the plan
FileDataSource source1 = new FileDataSource(new DummyInputFormat(), IN_FILE, "Source 1");
FileDataSource source2 = new FileDataSource(new DummyInputFormat(), IN_FILE, "Source 2");
CrossOperator cross =
CrossWithLargeOperator.builder(new DummyCrossStub())
.input1(source1)
.input2(source2)
.name("Cross")
.build();
FileDataSink sink = new FileDataSink(new DummyOutputFormat(), OUT_FILE, cross, "Sink");
Plan plan = new Plan(sink);
plan.setDefaultParallelism(DEFAULT_PARALLELISM);
try {
OptimizedPlan oPlan = compileNoStats(plan);
OptimizerPlanNodeResolver resolver = new OptimizerPlanNodeResolver(oPlan);
DualInputPlanNode crossPlanNode = resolver.getNode("Cross");
Channel in1 = crossPlanNode.getInput1();
Channel in2 = crossPlanNode.getInput2();
assertEquals(ShipStrategyType.BROADCAST, in1.getShipStrategy());
assertEquals(ShipStrategyType.FORWARD, in2.getShipStrategy());
} catch (CompilerException ce) {
ce.printStackTrace();
fail("The pact compiler is unable to compile this plan correctly.");
}
}
@Override
public Plan getPlan(String... args) {
// parse job parameters
int numSubTasks = (args.length > 0 ? Integer.parseInt(args[0]) : 1);
String dataPointInput = (args.length > 1 ? args[1] : "");
String clusterInput = (args.length > 2 ? args[2] : "");
String output = (args.length > 3 ? args[3] : "");
// create DataSourceContract for data point input
@SuppressWarnings("unchecked")
FileDataSource pointsSource =
new FileDataSource(
new CsvInputFormat(
'|', IntValue.class, DoubleValue.class, DoubleValue.class, DoubleValue.class),
dataPointInput,
"Data Points");
// create DataSourceContract for cluster center input
@SuppressWarnings("unchecked")
FileDataSource clustersSource =
new FileDataSource(
new CsvInputFormat(
'|', IntValue.class, DoubleValue.class, DoubleValue.class, DoubleValue.class),
clusterInput,
"Centers");
MapOperator dataPoints =
MapOperator.builder(new PointBuilder())
.name("Build data points")
.input(pointsSource)
.build();
MapOperator clusterPoints =
MapOperator.builder(new PointBuilder())
.name("Build cluster points")
.input(clustersSource)
.build();
// the mapper computes the distance to all points, which it draws from a broadcast variable
MapOperator findNearestClusterCenters =
MapOperator.builder(new SelectNearestCenter())
.setBroadcastVariable("centers", clusterPoints)
.input(dataPoints)
.name("Find Nearest Centers")
.build();
// create reducer recomputes the cluster centers as the average of all associated data points
ReduceOperator recomputeClusterCenter =
ReduceOperator.builder(new RecomputeClusterCenter(), IntValue.class, 0)
.input(findNearestClusterCenters)
.name("Recompute Center Positions")
.build();
// create DataSinkContract for writing the new cluster positions
FileDataSink newClusterPoints =
new FileDataSink(
new PointOutFormat(), output, recomputeClusterCenter, "New Center Positions");
// return the plan
Plan plan = new Plan(newClusterPoints, "KMeans Iteration");
plan.setDefaultParallelism(numSubTasks);
return plan;
}
@SuppressWarnings("unchecked")
@Override
public Plan getPlan(String... args) {
// parse job parameters
final int numSubTasks = (args.length > 0 ? Integer.parseInt(args[0]) : 1);
final String verticesInput = (args.length > 1 ? args[1] : "");
final String edgeInput = (args.length > 2 ? args[2] : "");
final String output = (args.length > 3 ? args[3] : "");
final int maxIterations = (args.length > 4 ? Integer.parseInt(args[4]) : 1);
// data source for initial vertices
FileDataSource initialVertices =
new FileDataSource(new CsvInputFormat(' ', LongValue.class), verticesInput, "Vertices");
MapOperator verticesWithId =
MapOperator.builder(DuplicateLongMap.class)
.input(initialVertices)
.name("Assign Vertex Ids")
.build();
DeltaIteration iteration = new DeltaIteration(0, "Connected Components Iteration");
iteration.setInitialSolutionSet(verticesWithId);
iteration.setInitialWorkset(verticesWithId);
iteration.setMaximumNumberOfIterations(maxIterations);
// create DataSourceContract for the edges
FileDataSource edges =
new FileDataSource(
new CsvInputFormat(' ', LongValue.class, LongValue.class), edgeInput, "Edges");
// create CrossOperator for distance computation
JoinOperator joinWithNeighbors =
JoinOperator.builder(new NeighborWithComponentIDJoin(), LongValue.class, 0, 0)
.input1(iteration.getWorkset())
.input2(edges)
.name("Join Candidate Id With Neighbor")
.build();
CoGroupOperator minAndUpdate =
CoGroupOperator.builder(new MinIdAndUpdate(), LongValue.class, 0, 0)
.input1(joinWithNeighbors)
.input2(iteration.getSolutionSet())
.name("Min Id and Update")
.build();
iteration.setNextWorkset(minAndUpdate);
iteration.setSolutionSetDelta(minAndUpdate);
// create DataSinkContract for writing the new cluster positions
FileDataSink result = new FileDataSink(new CsvOutputFormat(), output, iteration, "Result");
CsvOutputFormat.configureRecordFormat(result)
.recordDelimiter('\n')
.fieldDelimiter(' ')
.field(LongValue.class, 0)
.field(LongValue.class, 1);
// return the PACT plan
Plan plan = new Plan(result, "Workset Connected Components");
plan.setDefaultParallelism(numSubTasks);
return plan;
}
