private static DataSet<Tuple3<Integer, String, Integer>> getRanksDataSet(
ExecutionEnvironment env, ParameterTool params) {
// Create DataSet for ranks relation (Rank, URL, Avg-Visit-Duration)
if (params.has("ranks")) {
return env.readCsvFile(params.get("ranks"))
.fieldDelimiter("|")
.types(Integer.class, String.class, Integer.class);
} else {
System.out.println("Executing WebLogAnalysis example with default ranks data set.");
System.out.println("Use --ranks to specify file input.");
return WebLogData.getRankDataSet(env);
}
}
private static DataSet<Tuple2<String, String>> getDocumentsDataSet(
ExecutionEnvironment env, ParameterTool params) {
// Create DataSet for documents relation (URL, Doc-Text)
if (params.has("documents")) {
return env.readCsvFile(params.get("documents"))
.fieldDelimiter("|")
.types(String.class, String.class);
} else {
System.out.println("Executing WebLogAnalysis example with default documents data set.");
System.out.println("Use --documents to specify file input.");
return WebLogData.getDocumentDataSet(env);
}
}
private static DataSet<Point> getPointDataSet(ParameterTool params, ExecutionEnvironment env) {
DataSet<Point> points;
if (params.has("points")) {
// read points from CSV file
points =
env.readCsvFile(params.get("points")).fieldDelimiter(" ").pojoType(Point.class, "x", "y");
} else {
System.out.println("Executing K-Means example with default point data set.");
System.out.println("Use --points to specify file input.");
points = KMeansData.getDefaultPointDataSet(env);
}
return points;
}
private Plan getTestPlanRightStatic(String strategy) {
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(DEFAULT_PARALLELISM);
DataSet<Tuple3<Long, Long, Long>> bigInput =
env.readCsvFile("file://bigFile").types(Long.class, Long.class, Long.class).name("bigFile");
DataSet<Tuple3<Long, Long, Long>> smallInput =
env.readCsvFile("file://smallFile")
.types(Long.class, Long.class, Long.class)
.name("smallFile");
IterativeDataSet<Tuple3<Long, Long, Long>> iteration = bigInput.iterate(10);
Configuration joinStrategy = new Configuration();
joinStrategy.setString(
Optimizer.HINT_SHIP_STRATEGY, Optimizer.HINT_SHIP_STRATEGY_REPARTITION_HASH);
if (!strategy.equals("")) {
joinStrategy.setString(Optimizer.HINT_LOCAL_STRATEGY, strategy);
}
DataSet<Tuple3<Long, Long, Long>> inner =
iteration
.join(smallInput)
.where(0)
.equalTo(0)
.with(new DummyJoiner())
.name("DummyJoiner")
.withParameters(joinStrategy);
DataSet<Tuple3<Long, Long, Long>> output = iteration.closeWith(inner);
output.output(new DiscardingOutputFormat<Tuple3<Long, Long, Long>>());
return env.createProgramPlan();
}
private static DataSet<Centroid> getCentroidDataSet(
ParameterTool params, ExecutionEnvironment env) {
DataSet<Centroid> centroids;
if (params.has("centroids")) {
centroids =
env.readCsvFile(params.get("centroids"))
.fieldDelimiter(" ")
.pojoType(Centroid.class, "id", "x", "y");
} else {
System.out.println("Executing K-Means example with default centroid data set.");
System.out.println("Use --centroids to specify file input.");
centroids = KMeansData.getDefaultCentroidDataSet(env);
}
return centroids;
}
@SuppressWarnings("serial")
private static DataSet<Edge<Long, NullValue>> getEdgesDataSet(ExecutionEnvironment env) {
if (fileOutput) {
return env.readCsvFile(edgeInputPath)
.ignoreComments("#")
.fieldDelimiter("\t")
.lineDelimiter("\n")
.types(Long.class, Long.class)
.map(
new MapFunction<Tuple2<Long, Long>, Edge<Long, NullValue>>() {
@Override
public Edge<Long, NullValue> map(Tuple2<Long, Long> value) throws Exception {
return new Edge<>(value.f0, value.f1, NullValue.getInstance());
}
});
} else {
return ConnectedComponentsDefaultData.getDefaultEdgeDataSet(env);
}
}
