Example usage for org.apache.commons.lang3 StringEscapeUtils unescapeJava

List of usage examples for org.apache.commons.lang3 StringEscapeUtils unescapeJava

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Introduction

In this page you can find the example usage for org.apache.commons.lang3 StringEscapeUtils unescapeJava.

Prototype

public static final String unescapeJava(final String input)

Source Link

Document

Unescapes any Java literals found in the String .

Usage

From source file:org.apache.flink.graph.drivers.Graph500.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);
    env.getConfig().setGlobalJobParameters(parameters);

    if (!parameters.has("directed")) {
        throw new ProgramParametrizationException(
                getUsage("must declare execution mode as '--directed true' or '--directed false'"));
    }// ww w . j ava2  s  .com
    boolean directed = parameters.getBoolean("directed");

    if (!parameters.has("simplify")) {
        throw new ProgramParametrizationException(
                getUsage("must declare '--simplify true' or '--simplify false'"));
    }
    boolean simplify = parameters.getBoolean("simplify");

    // Generate RMat graph
    int scale = parameters.getInt("scale", DEFAULT_SCALE);
    int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

    RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

    long vertexCount = 1L << scale;
    long edgeCount = vertexCount * edgeFactor;

    boolean clipAndFlip = parameters.getBoolean("clip_and_flip", DEFAULT_CLIP_AND_FLIP);

    Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount).generate();

    if (directed) {
        if (simplify) {
            graph = graph.run(
                    new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>());
        }
    } else {
        if (simplify) {
            graph = graph.run(
                    new org.apache.flink.graph.asm.simple.undirected.Simplify<LongValue, NullValue, NullValue>(
                            clipAndFlip));
        } else {
            graph = graph.getUndirected();
        }
    }

    DataSet<Tuple2<LongValue, LongValue>> edges = graph.getEdges().project(0, 1);

    // Print, hash, or write RMat graph to disk
    switch (parameters.get("output", "")) {
    case "print":
        System.out.println();
        edges.print();
        break;

    case "hash":
        System.out.println();
        System.out.println(DataSetUtils.checksumHashCode(edges));
        break;

    case "csv":
        String filename = parameters.getRequired("output_filename");

        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("output_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils.unescapeJava(
                parameters.get("output_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        edges.writeAsCsv(filename, lineDelimiter, fieldDelimiter);

        env.execute("Graph500");
        break;
    default:
        throw new ProgramParametrizationException(getUsage("invalid output type"));
    }

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.flink.graph.drivers.GraphMetrics.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);
    env.getConfig().setGlobalJobParameters(parameters);

    if (!parameters.has("directed")) {
        throw new ProgramParametrizationException(
                getUsage("must declare execution mode as '--directed true' or '--directed false'"));
    }/*from  w  ww. j av  a  2s. c  o  m*/
    boolean directedAlgorithm = parameters.getBoolean("directed");

    GraphAnalytic vm;
    GraphAnalytic em;

    switch (parameters.get("input", "")) {
    case "csv": {
        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        GraphCsvReader reader = Graph.fromCsvReader(parameters.getRequired("input_filename"), env)
                .ignoreCommentsEdges("#").lineDelimiterEdges(lineDelimiter).fieldDelimiterEdges(fieldDelimiter);

        switch (parameters.get("type", "")) {
        case "integer": {
            Graph<LongValue, NullValue, NullValue> graph = reader.keyType(LongValue.class);

            if (directedAlgorithm) {
                if (parameters.getBoolean("simplify", false)) {
                    graph = graph.run(
                            new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>());
                }

                vm = graph.run(
                        new org.apache.flink.graph.library.metric.directed.VertexMetrics<LongValue, NullValue, NullValue>());
                em = graph.run(
                        new org.apache.flink.graph.library.metric.directed.EdgeMetrics<LongValue, NullValue, NullValue>());
            } else {
                if (parameters.getBoolean("simplify", false)) {
                    graph = graph.run(
                            new org.apache.flink.graph.asm.simple.undirected.Simplify<LongValue, NullValue, NullValue>(
                                    false));
                }

                vm = graph.run(
                        new org.apache.flink.graph.library.metric.undirected.VertexMetrics<LongValue, NullValue, NullValue>());
                em = graph.run(
                        new org.apache.flink.graph.library.metric.undirected.EdgeMetrics<LongValue, NullValue, NullValue>());
            }
        }
            break;

        case "string": {
            Graph<StringValue, NullValue, NullValue> graph = reader.keyType(StringValue.class);

            if (directedAlgorithm) {
                if (parameters.getBoolean("simplify", false)) {
                    graph = graph.run(
                            new org.apache.flink.graph.asm.simple.directed.Simplify<StringValue, NullValue, NullValue>());
                }

                vm = graph.run(
                        new org.apache.flink.graph.library.metric.directed.VertexMetrics<StringValue, NullValue, NullValue>());
                em = graph.run(
                        new org.apache.flink.graph.library.metric.directed.EdgeMetrics<StringValue, NullValue, NullValue>());
            } else {
                if (parameters.getBoolean("simplify", false)) {
                    graph = graph.run(
                            new org.apache.flink.graph.asm.simple.undirected.Simplify<StringValue, NullValue, NullValue>(
                                    false));
                }

                vm = graph.run(
                        new org.apache.flink.graph.library.metric.undirected.VertexMetrics<StringValue, NullValue, NullValue>());
                em = graph.run(
                        new org.apache.flink.graph.library.metric.undirected.EdgeMetrics<StringValue, NullValue, NullValue>());
            }
        }
            break;

        default:
            throw new ProgramParametrizationException(getUsage("invalid CSV type"));
        }
    }
        break;

    case "rmat": {
        int scale = parameters.getInt("scale", DEFAULT_SCALE);
        int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

        RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

        long vertexCount = 1L << scale;
        long edgeCount = vertexCount * edgeFactor;

        Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount)
                .generate();

        if (directedAlgorithm) {
            if (scale > 32) {
                Graph<LongValue, NullValue, NullValue> newGraph = graph.run(
                        new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>());

                vm = newGraph.run(
                        new org.apache.flink.graph.library.metric.directed.VertexMetrics<LongValue, NullValue, NullValue>());
                em = newGraph.run(
                        new org.apache.flink.graph.library.metric.directed.EdgeMetrics<LongValue, NullValue, NullValue>());
            } else {
                Graph<IntValue, NullValue, NullValue> newGraph = graph
                        .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                                new LongValueToUnsignedIntValue()))
                        .run(new org.apache.flink.graph.asm.simple.directed.Simplify<IntValue, NullValue, NullValue>());

                vm = newGraph.run(
                        new org.apache.flink.graph.library.metric.directed.VertexMetrics<IntValue, NullValue, NullValue>());
                em = newGraph.run(
                        new org.apache.flink.graph.library.metric.directed.EdgeMetrics<IntValue, NullValue, NullValue>());
            }
        } else {
            boolean clipAndFlip = parameters.getBoolean("clip_and_flip", DEFAULT_CLIP_AND_FLIP);

            if (scale > 32) {
                Graph<LongValue, NullValue, NullValue> newGraph = graph.run(
                        new org.apache.flink.graph.asm.simple.undirected.Simplify<LongValue, NullValue, NullValue>(
                                clipAndFlip));

                vm = newGraph.run(
                        new org.apache.flink.graph.library.metric.undirected.VertexMetrics<LongValue, NullValue, NullValue>());
                em = newGraph.run(
                        new org.apache.flink.graph.library.metric.undirected.EdgeMetrics<LongValue, NullValue, NullValue>());
            } else {
                Graph<IntValue, NullValue, NullValue> newGraph = graph
                        .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                                new LongValueToUnsignedIntValue()))
                        .run(new org.apache.flink.graph.asm.simple.undirected.Simplify<IntValue, NullValue, NullValue>(
                                clipAndFlip));

                vm = newGraph.run(
                        new org.apache.flink.graph.library.metric.undirected.VertexMetrics<IntValue, NullValue, NullValue>());
                em = newGraph.run(
                        new org.apache.flink.graph.library.metric.undirected.EdgeMetrics<IntValue, NullValue, NullValue>());
            }
        }
    }
        break;

    default:
        throw new ProgramParametrizationException(getUsage("invalid input type"));
    }

    env.execute("Graph Metrics");

    System.out.println();
    System.out.print("Vertex metrics:\n  ");
    System.out.println(vm.getResult().toString().replace(";", "\n "));
    System.out.println();
    System.out.print("Edge metrics:\n  ");
    System.out.println(em.getResult().toString().replace(";", "\n "));

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.flink.graph.drivers.HITS.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);
    env.getConfig().setGlobalJobParameters(parameters);

    int iterations = parameters.getInt("iterations", DEFAULT_ITERATIONS);

    DataSet hits;//from  ww w  .j a v  a 2  s  . c o m

    switch (parameters.get("input", "")) {
    case "csv": {
        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        GraphCsvReader reader = Graph.fromCsvReader(parameters.getRequired("input_filename"), env)
                .ignoreCommentsEdges("#").lineDelimiterEdges(lineDelimiter).fieldDelimiterEdges(fieldDelimiter);

        switch (parameters.get("type", "")) {
        case "integer": {
            hits = reader.keyType(LongValue.class)
                    .run(new org.apache.flink.graph.library.link_analysis.HITS<LongValue, NullValue, NullValue>(
                            iterations));
        }
            break;

        case "string": {
            hits = reader.keyType(StringValue.class).run(
                    new org.apache.flink.graph.library.link_analysis.HITS<StringValue, NullValue, NullValue>(
                            iterations));
        }
            break;

        default:
            throw new ProgramParametrizationException(getUsage("invalid CSV type"));
        }
    }
        break;

    case "rmat": {
        int scale = parameters.getInt("scale", DEFAULT_SCALE);
        int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

        RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

        long vertexCount = 1L << scale;
        long edgeCount = vertexCount * edgeFactor;

        Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount)
                .generate();

        if (scale > 32) {
            hits = graph.run(new Simplify<LongValue, NullValue, NullValue>())
                    .run(new org.apache.flink.graph.library.link_analysis.HITS<LongValue, NullValue, NullValue>(
                            iterations));
        } else {
            hits = graph
                    .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                            new LongValueToUnsignedIntValue()))
                    .run(new Simplify<IntValue, NullValue, NullValue>())
                    .run(new org.apache.flink.graph.library.link_analysis.HITS<IntValue, NullValue, NullValue>(
                            iterations));
        }
    }
        break;

    default:
        throw new ProgramParametrizationException(getUsage("invalid input type"));
    }

    switch (parameters.get("output", "")) {
    case "print":
        System.out.println();
        for (Object e : hits.collect()) {
            System.out.println(((Result) e).toPrintableString());
        }
        break;

    case "hash":
        System.out.println();
        System.out.println(DataSetUtils.checksumHashCode(hits));
        break;

    case "csv":
        String filename = parameters.getRequired("output_filename");

        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("output_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils.unescapeJava(
                parameters.get("output_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        hits.writeAsCsv(filename, lineDelimiter, fieldDelimiter);

        env.execute("HITS");
        break;
    default:
        throw new ProgramParametrizationException(getUsage("invalid output type"));
    }

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.flink.graph.drivers.JaccardIndex.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);
    env.getConfig().setGlobalJobParameters(parameters);

    int little_parallelism = parameters.getInt("little_parallelism", PARALLELISM_DEFAULT);

    DataSet ji;//  ww w.  j av  a 2 s .co  m

    switch (parameters.get("input", "")) {
    case "csv": {
        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        GraphCsvReader reader = Graph.fromCsvReader(parameters.getRequired("input_filename"), env)
                .ignoreCommentsEdges("#").lineDelimiterEdges(lineDelimiter).fieldDelimiterEdges(fieldDelimiter);

        switch (parameters.get("type", "")) {
        case "integer": {
            Graph<LongValue, NullValue, NullValue> graph = reader.keyType(LongValue.class);

            if (parameters.getBoolean("simplify", false)) {
                graph = graph.run(
                        new org.apache.flink.graph.asm.simple.undirected.Simplify<LongValue, NullValue, NullValue>(
                                false).setParallelism(little_parallelism));
            }

            ji = graph.run(
                    new org.apache.flink.graph.library.similarity.JaccardIndex<LongValue, NullValue, NullValue>()
                            .setLittleParallelism(little_parallelism));
        }
            break;

        case "string": {
            Graph<StringValue, NullValue, NullValue> graph = reader.keyType(StringValue.class);

            if (parameters.getBoolean("simplify", false)) {
                graph = graph.run(
                        new org.apache.flink.graph.asm.simple.undirected.Simplify<StringValue, NullValue, NullValue>(
                                false).setParallelism(little_parallelism));
            }

            ji = graph.run(
                    new org.apache.flink.graph.library.similarity.JaccardIndex<StringValue, NullValue, NullValue>()
                            .setLittleParallelism(little_parallelism));
        }
            break;

        default:
            throw new ProgramParametrizationException(getUsage("invalid CSV type"));
        }
    }
        break;

    case "rmat": {
        int scale = parameters.getInt("scale", DEFAULT_SCALE);
        int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

        RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

        long vertexCount = 1L << scale;
        long edgeCount = vertexCount * edgeFactor;

        Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount)
                .setParallelism(little_parallelism).generate();

        boolean clipAndFlip = parameters.getBoolean("clip_and_flip", DEFAULT_CLIP_AND_FLIP);

        if (scale > 32) {
            ji = graph
                    .run(new Simplify<LongValue, NullValue, NullValue>(clipAndFlip)
                            .setParallelism(little_parallelism))
                    .run(new org.apache.flink.graph.library.similarity.JaccardIndex<LongValue, NullValue, NullValue>()
                            .setLittleParallelism(little_parallelism));
        } else {
            ji = graph
                    .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                            new LongValueToUnsignedIntValue()).setParallelism(little_parallelism))
                    .run(new Simplify<IntValue, NullValue, NullValue>(clipAndFlip)
                            .setParallelism(little_parallelism))
                    .run(new org.apache.flink.graph.library.similarity.JaccardIndex<IntValue, NullValue, NullValue>()
                            .setLittleParallelism(little_parallelism));
        }
    }
        break;

    default:
        throw new ProgramParametrizationException(getUsage("invalid input type"));
    }

    switch (parameters.get("output", "")) {
    case "print":
        System.out.println();
        for (Object e : ji.collect()) {
            Result result = (Result) e;
            System.out.println(result.toPrintableString());
        }
        break;

    case "hash":
        System.out.println();
        System.out.println(DataSetUtils.checksumHashCode(ji));
        break;

    case "csv":
        String filename = parameters.getRequired("output_filename");

        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("output_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils.unescapeJava(
                parameters.get("output_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        ji.writeAsCsv(filename, lineDelimiter, fieldDelimiter);

        env.execute("Jaccard Index");
        break;

    default:
        throw new ProgramParametrizationException(getUsage("invalid output type"));
    }

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.flink.graph.drivers.TriangleListing.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);
    env.getConfig().setGlobalJobParameters(parameters);

    if (!parameters.has("directed")) {
        throw new ProgramParametrizationException(
                getUsage("must declare execution mode as '--directed true' or '--directed false'"));
    }/*w  ww  .j  av a2s . c  o  m*/
    boolean directedAlgorithm = parameters.getBoolean("directed");

    int little_parallelism = parameters.getInt("little_parallelism", PARALLELISM_DEFAULT);
    boolean triadic_census = parameters.getBoolean("triadic_census", DEFAULT_TRIADIC_CENSUS);

    GraphAnalytic tc = null;
    DataSet tl;

    switch (parameters.get("input", "")) {
    case "csv": {
        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        GraphCsvReader reader = Graph.fromCsvReader(parameters.getRequired("input_filename"), env)
                .ignoreCommentsEdges("#").lineDelimiterEdges(lineDelimiter).fieldDelimiterEdges(fieldDelimiter);

        switch (parameters.get("type", "")) {
        case "integer": {
            Graph<LongValue, NullValue, NullValue> graph = reader.keyType(LongValue.class);

            if (directedAlgorithm) {
                if (parameters.getBoolean("simplify", false)) {
                    graph = graph.run(
                            new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>()
                                    .setParallelism(little_parallelism));
                }

                if (triadic_census) {
                    tc = graph.run(
                            new org.apache.flink.graph.library.clustering.directed.TriadicCensus<LongValue, NullValue, NullValue>()
                                    .setLittleParallelism(little_parallelism));
                }
                tl = graph.run(
                        new org.apache.flink.graph.library.clustering.directed.TriangleListing<LongValue, NullValue, NullValue>()
                                .setLittleParallelism(little_parallelism));
            } else {
                if (parameters.getBoolean("simplify", false)) {
                    graph = graph.run(
                            new org.apache.flink.graph.asm.simple.undirected.Simplify<LongValue, NullValue, NullValue>(
                                    false).setParallelism(little_parallelism));
                }

                if (triadic_census) {
                    tc = graph.run(
                            new org.apache.flink.graph.library.clustering.undirected.TriadicCensus<LongValue, NullValue, NullValue>()
                                    .setLittleParallelism(little_parallelism));
                }
                tl = graph.run(
                        new org.apache.flink.graph.library.clustering.undirected.TriangleListing<LongValue, NullValue, NullValue>()
                                .setLittleParallelism(little_parallelism));
            }
        }
            break;

        case "string": {
            Graph<StringValue, NullValue, NullValue> graph = reader.keyType(StringValue.class);

            if (directedAlgorithm) {
                if (parameters.getBoolean("simplify", false)) {
                    graph = graph.run(
                            new org.apache.flink.graph.asm.simple.directed.Simplify<StringValue, NullValue, NullValue>()
                                    .setParallelism(little_parallelism));
                }

                if (triadic_census) {
                    tc = graph.run(
                            new org.apache.flink.graph.library.clustering.directed.TriadicCensus<StringValue, NullValue, NullValue>()
                                    .setLittleParallelism(little_parallelism));
                }
                tl = graph.run(
                        new org.apache.flink.graph.library.clustering.directed.TriangleListing<StringValue, NullValue, NullValue>()
                                .setLittleParallelism(little_parallelism));
            } else {
                if (parameters.getBoolean("simplify", false)) {
                    graph = graph.run(
                            new org.apache.flink.graph.asm.simple.undirected.Simplify<StringValue, NullValue, NullValue>(
                                    false).setParallelism(little_parallelism));
                }

                if (triadic_census) {
                    tc = graph.run(
                            new org.apache.flink.graph.library.clustering.undirected.TriadicCensus<StringValue, NullValue, NullValue>()
                                    .setLittleParallelism(little_parallelism));
                }
                tl = graph.run(
                        new org.apache.flink.graph.library.clustering.undirected.TriangleListing<StringValue, NullValue, NullValue>()
                                .setLittleParallelism(little_parallelism));
            }
        }
            break;

        default:
            throw new ProgramParametrizationException(getUsage("invalid CSV type"));
        }

    }
        break;

    case "rmat": {
        int scale = parameters.getInt("scale", DEFAULT_SCALE);
        int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

        RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

        long vertexCount = 1L << scale;
        long edgeCount = vertexCount * edgeFactor;

        Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount)
                .generate();

        if (directedAlgorithm) {
            if (scale > 32) {
                Graph<LongValue, NullValue, NullValue> simpleGraph = graph.run(
                        new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>()
                                .setParallelism(little_parallelism));

                if (triadic_census) {
                    tc = simpleGraph.run(
                            new org.apache.flink.graph.library.clustering.directed.TriadicCensus<LongValue, NullValue, NullValue>()
                                    .setLittleParallelism(little_parallelism));
                }
                tl = simpleGraph.run(
                        new org.apache.flink.graph.library.clustering.directed.TriangleListing<LongValue, NullValue, NullValue>()
                                .setLittleParallelism(little_parallelism));
            } else {
                Graph<LongValue, NullValue, NullValue> simpleGraph = graph.run(
                        new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>()
                                .setParallelism(little_parallelism));

                if (triadic_census) {
                    tc = simpleGraph.run(
                            new org.apache.flink.graph.library.clustering.directed.TriadicCensus<LongValue, NullValue, NullValue>()
                                    .setLittleParallelism(little_parallelism));
                }
                tl = simpleGraph.run(
                        new org.apache.flink.graph.library.clustering.directed.TriangleListing<LongValue, NullValue, NullValue>()
                                .setLittleParallelism(little_parallelism));
            }
        } else {
            boolean clipAndFlip = parameters.getBoolean("clip_and_flip", DEFAULT_CLIP_AND_FLIP);

            if (scale > 32) {
                Graph<LongValue, NullValue, NullValue> simpleGraph = graph.run(
                        new org.apache.flink.graph.asm.simple.undirected.Simplify<LongValue, NullValue, NullValue>(
                                clipAndFlip).setParallelism(little_parallelism));

                if (triadic_census) {
                    tc = simpleGraph.run(
                            new org.apache.flink.graph.library.clustering.undirected.TriadicCensus<LongValue, NullValue, NullValue>()
                                    .setLittleParallelism(little_parallelism));
                }
                tl = simpleGraph.run(
                        new org.apache.flink.graph.library.clustering.undirected.TriangleListing<LongValue, NullValue, NullValue>()
                                .setLittleParallelism(little_parallelism));
            } else {
                Graph<IntValue, NullValue, NullValue> simpleGraph = graph
                        .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                                new LongValueToUnsignedIntValue()).setParallelism(little_parallelism))
                        .run(new org.apache.flink.graph.asm.simple.undirected.Simplify<IntValue, NullValue, NullValue>(
                                clipAndFlip).setParallelism(little_parallelism));

                if (triadic_census) {
                    tc = simpleGraph.run(
                            new org.apache.flink.graph.library.clustering.undirected.TriadicCensus<IntValue, NullValue, NullValue>()
                                    .setLittleParallelism(little_parallelism));
                }
                tl = simpleGraph.run(
                        new org.apache.flink.graph.library.clustering.undirected.TriangleListing<IntValue, NullValue, NullValue>()
                                .setLittleParallelism(little_parallelism));
            }
        }
    }
        break;

    default:
        throw new ProgramParametrizationException(getUsage("invalid input type"));
    }

    switch (parameters.get("output", "")) {
    case "print":
        System.out.println();
        if (directedAlgorithm) {
            for (Object e : tl.collect()) {
                org.apache.flink.graph.library.clustering.directed.TriangleListing.Result result = (org.apache.flink.graph.library.clustering.directed.TriangleListing.Result) e;
                System.out.println(result.toPrintableString());
            }
        } else {
            tl.print();
        }
        break;

    case "hash":
        System.out.println();
        System.out.println(DataSetUtils.checksumHashCode(tl));
        break;

    case "csv":
        String filename = parameters.getRequired("output_filename");

        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("output_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils.unescapeJava(
                parameters.get("output_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        tl.writeAsCsv(filename, lineDelimiter, fieldDelimiter);

        env.execute();
        break;
    default:
        throw new ProgramParametrizationException(getUsage("invalid output type"));
    }

    if (tc != null) {
        System.out.print("Triadic census:\n  ");
        System.out.println(tc.getResult().toString().replace(";", "\n "));
    }

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.flink.graph.examples.ClusteringCoefficient.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);
    if (!parameters.has("directed")) {
        printUsage();/*from  w ww  .j  a  v  a2s  . c o m*/
        return;
    }
    boolean directedAlgorithm = parameters.getBoolean("directed");

    // global and local clustering coefficient results
    GraphAnalytic gcc;
    DataSet lcc;

    switch (parameters.get("input", "")) {
    case "csv": {
        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        GraphCsvReader reader = Graph.fromCsvReader(parameters.get("input_filename"), env)
                .ignoreCommentsEdges("#").lineDelimiterEdges(lineDelimiter).fieldDelimiterEdges(fieldDelimiter);

        switch (parameters.get("type", "")) {
        case "integer": {
            Graph<LongValue, NullValue, NullValue> graph = reader.keyType(LongValue.class);

            if (directedAlgorithm) {
                gcc = graph.run(
                        new org.apache.flink.graph.library.clustering.directed.GlobalClusteringCoefficient<LongValue, NullValue, NullValue>());
                lcc = graph.run(
                        new org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient<LongValue, NullValue, NullValue>());
            } else {
                gcc = graph.run(
                        new org.apache.flink.graph.library.clustering.undirected.GlobalClusteringCoefficient<LongValue, NullValue, NullValue>());
                lcc = graph.run(
                        new org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient<LongValue, NullValue, NullValue>());
            }
        }
            break;

        case "string": {
            Graph<StringValue, NullValue, NullValue> graph = reader.keyType(StringValue.class);

            if (directedAlgorithm) {
                gcc = graph.run(
                        new org.apache.flink.graph.library.clustering.directed.GlobalClusteringCoefficient<StringValue, NullValue, NullValue>());
                lcc = graph.run(
                        new org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient<StringValue, NullValue, NullValue>());
            } else {
                gcc = graph.run(
                        new org.apache.flink.graph.library.clustering.undirected.GlobalClusteringCoefficient<StringValue, NullValue, NullValue>());
                lcc = graph.run(
                        new org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient<StringValue, NullValue, NullValue>());
            }
        }
            break;

        default:
            printUsage();
            return;
        }
    }
        break;

    case "rmat": {
        int scale = parameters.getInt("scale", DEFAULT_SCALE);
        int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

        RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

        long vertexCount = 1L << scale;
        long edgeCount = vertexCount * edgeFactor;

        Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount)
                .generate();

        if (directedAlgorithm) {
            if (scale > 32) {
                Graph<LongValue, NullValue, NullValue> newGraph = graph.run(
                        new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>());

                gcc = newGraph.run(
                        new org.apache.flink.graph.library.clustering.directed.GlobalClusteringCoefficient<LongValue, NullValue, NullValue>());
                lcc = newGraph.run(
                        new org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient<LongValue, NullValue, NullValue>()
                                .setIncludeZeroDegreeVertices(false));
            } else {
                Graph<IntValue, NullValue, NullValue> newGraph = graph
                        .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                                new LongValueToIntValue()))
                        .run(new org.apache.flink.graph.asm.simple.directed.Simplify<IntValue, NullValue, NullValue>());

                gcc = newGraph.run(
                        new org.apache.flink.graph.library.clustering.directed.GlobalClusteringCoefficient<IntValue, NullValue, NullValue>());
                lcc = newGraph.run(
                        new org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient<IntValue, NullValue, NullValue>()
                                .setIncludeZeroDegreeVertices(false));
            }
        } else {
            boolean clipAndFlip = parameters.getBoolean("clip_and_flip", DEFAULT_CLIP_AND_FLIP);

            if (scale > 32) {
                Graph<LongValue, NullValue, NullValue> newGraph = graph.run(
                        new org.apache.flink.graph.asm.simple.undirected.Simplify<LongValue, NullValue, NullValue>(
                                clipAndFlip));

                gcc = newGraph.run(
                        new org.apache.flink.graph.library.clustering.undirected.GlobalClusteringCoefficient<LongValue, NullValue, NullValue>());
                lcc = newGraph.run(
                        new org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient<LongValue, NullValue, NullValue>()
                                .setIncludeZeroDegreeVertices(false));
            } else {
                Graph<IntValue, NullValue, NullValue> newGraph = graph
                        .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                                new LongValueToIntValue()))
                        .run(new org.apache.flink.graph.asm.simple.undirected.Simplify<IntValue, NullValue, NullValue>(
                                clipAndFlip));

                gcc = newGraph.run(
                        new org.apache.flink.graph.library.clustering.undirected.GlobalClusteringCoefficient<IntValue, NullValue, NullValue>());
                lcc = newGraph.run(
                        new org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient<IntValue, NullValue, NullValue>()
                                .setIncludeZeroDegreeVertices(false));
            }
        }
    }
        break;

    default:
        printUsage();
        return;
    }

    switch (parameters.get("output", "")) {
    case "print":
        if (directedAlgorithm) {
            for (Object e : lcc.collect()) {
                org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient.Result result = (org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient.Result) e;
                System.out.println(result.toVerboseString());
            }
        } else {
            for (Object e : lcc.collect()) {
                org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient.Result result = (org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient.Result) e;
                System.out.println(result.toVerboseString());
            }
        }
        System.out.println(gcc.getResult());
        break;

    case "hash":
        System.out.println(DataSetUtils.checksumHashCode(lcc));
        System.out.println(gcc.getResult());
        break;

    case "csv":
        String filename = parameters.get("output_filename");

        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("output_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils.unescapeJava(
                parameters.get("output_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        lcc.writeAsCsv(filename, lineDelimiter, fieldDelimiter);

        System.out.println(gcc.execute());
        break;

    default:
        printUsage();
        return;
    }

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.flink.graph.examples.HITS.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);
    int iterations = parameters.getInt("iterations", DEFAULT_ITERATIONS);

    DataSet hits;//from  w ww  .j a v a 2s . co m

    switch (parameters.get("input", "")) {
    case "csv": {
        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        GraphCsvReader reader = Graph.fromCsvReader(parameters.get("input_filename"), env)
                .ignoreCommentsEdges("#").lineDelimiterEdges(lineDelimiter).fieldDelimiterEdges(fieldDelimiter);

        switch (parameters.get("type", "")) {
        case "integer": {
            hits = reader.keyType(LongValue.class)
                    .run(new org.apache.flink.graph.library.link_analysis.HITS<LongValue, NullValue, NullValue>(
                            iterations));
        }
            break;

        case "string": {
            hits = reader.keyType(StringValue.class).run(
                    new org.apache.flink.graph.library.link_analysis.HITS<StringValue, NullValue, NullValue>(
                            iterations));
        }
            break;

        default:
            printUsage();
            return;
        }
    }
        break;

    case "rmat": {
        int scale = parameters.getInt("scale", DEFAULT_SCALE);
        int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

        RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

        long vertexCount = 1L << scale;
        long edgeCount = vertexCount * edgeFactor;

        Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount)
                .generate();

        if (scale > 32) {
            hits = graph.run(new Simplify<LongValue, NullValue, NullValue>())
                    .run(new org.apache.flink.graph.library.link_analysis.HITS<LongValue, NullValue, NullValue>(
                            iterations));
        } else {
            hits = graph
                    .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                            new LongValueToIntValue()))
                    .run(new Simplify<IntValue, NullValue, NullValue>())
                    .run(new org.apache.flink.graph.library.link_analysis.HITS<IntValue, NullValue, NullValue>(
                            iterations));
        }
    }
        break;

    default:
        printUsage();
        return;
    }

    switch (parameters.get("output", "")) {
    case "print":
        for (Object e : hits.collect()) {
            System.out.println(((Result) e).toVerboseString());
        }
        break;

    case "hash":
        System.out.println(DataSetUtils.checksumHashCode(hits));
        break;

    case "csv":
        String filename = parameters.get("output_filename");

        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("output_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils.unescapeJava(
                parameters.get("output_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        hits.writeAsCsv(filename, lineDelimiter, fieldDelimiter);

        env.execute();
        break;
    default:
        printUsage();
        return;
    }

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.flink.graph.examples.JaccardIndex.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);

    DataSet ji;//from w w  w. j  a  va2  s .com

    switch (parameters.get("input", "")) {
    case "csv": {
        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        GraphCsvReader reader = Graph.fromCsvReader(parameters.get("input_filename"), env)
                .ignoreCommentsEdges("#").lineDelimiterEdges(lineDelimiter).fieldDelimiterEdges(fieldDelimiter);

        switch (parameters.get("type", "")) {
        case "integer": {
            ji = reader.keyType(LongValue.class).run(
                    new org.apache.flink.graph.library.similarity.JaccardIndex<LongValue, NullValue, NullValue>());
        }
            break;

        case "string": {
            ji = reader.keyType(StringValue.class).run(
                    new org.apache.flink.graph.library.similarity.JaccardIndex<StringValue, NullValue, NullValue>());
        }
            break;

        default:
            printUsage();
            return;
        }
    }
        break;

    case "rmat": {
        int scale = parameters.getInt("scale", DEFAULT_SCALE);
        int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

        RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

        long vertexCount = 1L << scale;
        long edgeCount = vertexCount * edgeFactor;

        boolean clipAndFlip = parameters.getBoolean("clip_and_flip", DEFAULT_CLIP_AND_FLIP);

        Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount)
                .generate();

        if (scale > 32) {
            ji = graph.run(new Simplify<LongValue, NullValue, NullValue>(clipAndFlip)).run(
                    new org.apache.flink.graph.library.similarity.JaccardIndex<LongValue, NullValue, NullValue>());
        } else {
            ji = graph
                    .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                            new LongValueToIntValue()))
                    .run(new Simplify<IntValue, NullValue, NullValue>(clipAndFlip))
                    .run(new org.apache.flink.graph.library.similarity.JaccardIndex<IntValue, NullValue, NullValue>());
        }
    }
        break;

    default:
        printUsage();
        return;
    }

    switch (parameters.get("output", "")) {
    case "print":
        for (Object e : ji.collect()) {
            Result result = (Result) e;
            System.out.println(result.toVerboseString());
        }
        break;

    case "hash":
        System.out.println(DataSetUtils.checksumHashCode(ji));
        break;

    case "csv":
        String filename = parameters.get("output_filename");

        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("output_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils.unescapeJava(
                parameters.get("output_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        ji.writeAsCsv(filename, lineDelimiter, fieldDelimiter);

        env.execute();
        break;

    default:
        printUsage();
        return;
    }

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.flink.graph.examples.TriangleListing.java

public static void main(String[] args) throws Exception {
    // Set up the execution environment
    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.getConfig().enableObjectReuse();

    ParameterTool parameters = ParameterTool.fromArgs(args);
    if (!parameters.has("directed")) {
        printUsage();/*from   w  w w  .  j av  a 2s  .  c  o  m*/
        return;
    }
    boolean directedAlgorithm = parameters.getBoolean("directed");

    DataSet tl;

    switch (parameters.get("input", "")) {
    case "csv": {
        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("input_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        GraphCsvReader reader = Graph.fromCsvReader(parameters.get("input_filename"), env)
                .ignoreCommentsEdges("#").lineDelimiterEdges(lineDelimiter).fieldDelimiterEdges(fieldDelimiter);

        switch (parameters.get("type", "")) {
        case "integer": {
            Graph<LongValue, NullValue, NullValue> graph = reader.keyType(LongValue.class);

            if (directedAlgorithm) {
                tl = graph.run(
                        new org.apache.flink.graph.library.clustering.directed.TriangleListing<LongValue, NullValue, NullValue>());
            } else {
                tl = graph.run(
                        new org.apache.flink.graph.library.clustering.undirected.TriangleListing<LongValue, NullValue, NullValue>());
            }
        }
            break;

        case "string": {
            Graph<StringValue, NullValue, NullValue> graph = reader.keyType(StringValue.class);

            if (directedAlgorithm) {
                tl = graph.run(
                        new org.apache.flink.graph.library.clustering.directed.TriangleListing<StringValue, NullValue, NullValue>());
            } else {
                tl = graph.run(
                        new org.apache.flink.graph.library.clustering.undirected.TriangleListing<StringValue, NullValue, NullValue>());
            }
        }
            break;

        default:
            printUsage();
            return;
        }

    }
        break;

    case "rmat": {
        int scale = parameters.getInt("scale", DEFAULT_SCALE);
        int edgeFactor = parameters.getInt("edge_factor", DEFAULT_EDGE_FACTOR);

        RandomGenerableFactory<JDKRandomGenerator> rnd = new JDKRandomGeneratorFactory();

        long vertexCount = 1L << scale;
        long edgeCount = vertexCount * edgeFactor;

        Graph<LongValue, NullValue, NullValue> graph = new RMatGraph<>(env, rnd, vertexCount, edgeCount)
                .generate();

        if (directedAlgorithm) {
            if (scale > 32) {
                tl = graph.run(
                        new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>())
                        .run(new org.apache.flink.graph.library.clustering.directed.TriangleListing<LongValue, NullValue, NullValue>());
            } else {
                tl = graph
                        .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                                new LongValueToIntValue()))
                        .run(new org.apache.flink.graph.asm.simple.directed.Simplify<IntValue, NullValue, NullValue>())
                        .run(new org.apache.flink.graph.library.clustering.directed.TriangleListing<IntValue, NullValue, NullValue>());
            }
        } else {
            boolean clipAndFlip = parameters.getBoolean("clip_and_flip", DEFAULT_CLIP_AND_FLIP);

            graph = graph.run(new Simplify<LongValue, NullValue, NullValue>(clipAndFlip));

            if (scale > 32) {
                tl = graph.run(
                        new org.apache.flink.graph.asm.simple.undirected.Simplify<LongValue, NullValue, NullValue>(
                                clipAndFlip))
                        .run(new org.apache.flink.graph.library.clustering.undirected.TriangleListing<LongValue, NullValue, NullValue>());
            } else {
                tl = graph
                        .run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(
                                new LongValueToIntValue()))
                        .run(new org.apache.flink.graph.asm.simple.undirected.Simplify<IntValue, NullValue, NullValue>(
                                clipAndFlip))
                        .run(new org.apache.flink.graph.library.clustering.undirected.TriangleListing<IntValue, NullValue, NullValue>());
            }
        }
    }
        break;

    default:
        printUsage();
        return;
    }

    switch (parameters.get("output", "")) {
    case "print":
        if (directedAlgorithm) {
            for (Object e : tl.collect()) {
                org.apache.flink.graph.library.clustering.directed.TriangleListing.Result result = (org.apache.flink.graph.library.clustering.directed.TriangleListing.Result) e;
                System.out.println(result.toVerboseString());
            }
        } else {
            tl.print();
        }
        break;

    case "hash":
        System.out.println(DataSetUtils.checksumHashCode(tl));
        break;

    case "csv":
        String filename = parameters.get("output_filename");

        String lineDelimiter = StringEscapeUtils
                .unescapeJava(parameters.get("output_line_delimiter", CsvOutputFormat.DEFAULT_LINE_DELIMITER));

        String fieldDelimiter = StringEscapeUtils.unescapeJava(
                parameters.get("output_field_delimiter", CsvOutputFormat.DEFAULT_FIELD_DELIMITER));

        tl.writeAsCsv(filename, lineDelimiter, fieldDelimiter);

        env.execute();
        break;
    default:
        printUsage();
        return;
    }

    JobExecutionResult result = env.getLastJobExecutionResult();

    NumberFormat nf = NumberFormat.getInstance();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

From source file:org.apache.hadoop.hive.druid.HiveDruidQueryBasedInputFormat.java

@SuppressWarnings("deprecation")
private HiveDruidSplit[] getInputSplits(Configuration conf) throws IOException {
    String address = HiveConf.getVar(conf, HiveConf.ConfVars.HIVE_DRUID_BROKER_DEFAULT_ADDRESS);
    if (StringUtils.isEmpty(address)) {
        throw new IOException("Druid broker address not specified in configuration");
    }/*from ww  w .  j  av a 2 s .c  o  m*/
    String druidQuery = StringEscapeUtils.unescapeJava(conf.get(Constants.DRUID_QUERY_JSON));
    String druidQueryType;
    if (StringUtils.isEmpty(druidQuery)) {
        // Empty, maybe because CBO did not run; we fall back to
        // full Select query
        if (LOG.isWarnEnabled()) {
            LOG.warn("Druid query is empty; creating Select query");
        }
        String dataSource = conf.get(Constants.DRUID_DATA_SOURCE);
        if (dataSource == null) {
            throw new IOException("Druid data source cannot be empty");
        }
        druidQuery = createSelectStarQuery(address, dataSource);
        druidQueryType = Query.SELECT;
    } else {
        druidQueryType = conf.get(Constants.DRUID_QUERY_TYPE);
        if (druidQueryType == null) {
            throw new IOException("Druid query type not recognized");
        }
    }

    // hive depends on FileSplits
    Job job = new Job(conf);
    JobContext jobContext = ShimLoader.getHadoopShims().newJobContext(job);
    Path[] paths = FileInputFormat.getInputPaths(jobContext);

    switch (druidQueryType) {
    case Query.TIMESERIES:
    case Query.TOPN:
    case Query.GROUP_BY:
        return new HiveDruidSplit[] { new HiveDruidSplit(address, druidQuery, paths[0]) };
    case Query.SELECT:
        return splitSelectQuery(conf, address, druidQuery, paths[0]);
    default:
        throw new IOException("Druid query type not recognized");
    }
}