Examples with JDKRandomGeneratorFactory org.apache.flink.graph.generator.random.JDKRandomGeneratorFactory used on opensource projects

Example 6 with JDKRandomGeneratorFactory

use of org.apache.flink.graph.generator.random.JDKRandomGeneratorFactory in project flink by apache.

the class AsmTestBase method directedRMatGraph.

/**
 * Generate a directed RMat graph. Tests are usually run on a graph with scale=10 and
 * edgeFactor=16 but algorithms generating very large DataSets require smaller input graphs.
 *
 * <p>The examples program can write this graph as a CSV file for verifying algorithm results
 * with external libraries:
 *
 * <pre>
 * ./bin/flink run examples/flink-gelly-examples_*.jar --algorithm EdgeList \
 *     --input RMatGraph --type long --simplify directed --scale $SCALE --edge_factor $EDGE_FACTOR \
 *     --output csv --filename directedRMatGraph.csv
 * </pre>
 *
 * @param scale vertices are generated in the range [0, 2<sup>scale</sup>)
 * @param edgeFactor the edge count is {@code edgeFactor} * 2<sup>scale</sup>
 * @return directed RMat graph
 * @throws Exception on error
 */
protected Graph<LongValue, NullValue, NullValue> directedRMatGraph(int scale, int edgeFactor) throws Exception {
    long vertexCount = 1L << scale;
    long edgeCount = edgeFactor * vertexCount;
    return new RMatGraph<>(env, new JDKRandomGeneratorFactory(), vertexCount, edgeCount).generate().run(new org.apache.flink.graph.asm.simple.directed.Simplify<>());
}

Example 7 with JDKRandomGeneratorFactory

use of org.apache.flink.graph.generator.random.JDKRandomGeneratorFactory in project flink by apache.

the class GraphMetrics method main.

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'"));
    }
    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");
}

Example 8 with JDKRandomGeneratorFactory

use of org.apache.flink.graph.generator.random.JDKRandomGeneratorFactory in project flink by apache.

the class TriangleListing method main.

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'"));
    }
    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");
}

Example 9 with JDKRandomGeneratorFactory

use of org.apache.flink.graph.generator.random.JDKRandomGeneratorFactory in project flink by apache.

the class AsmTestBase method undirectedRMatGraph.

/**
 * Generate an undirected RMat graph. Tests are usually run on a graph with scale=10 and
 * edgeFactor=16 but algorithms generating very large DataSets require smaller input graphs.
 *
 * <p>The examples program can write this graph as a CSV file for verifying algorithm results
 * with external libraries:
 *
 * <pre>
 * ./bin/flink run examples/flink-gelly-examples_*.jar --algorithm EdgeList \
 *     --input RMatGraph --type long --simplify undirected --scale $SCALE --edge_factor $EDGE_FACTOR \
 *     --output csv --filename undirectedRMatGraph.csv
 * </pre>
 *
 * @param scale vertices are generated in the range [0, 2<sup>scale</sup>)
 * @param edgeFactor the edge count is {@code edgeFactor} * 2<sup>scale</sup>
 * @return undirected RMat graph
 * @throws Exception on error
 */
protected Graph<LongValue, NullValue, NullValue> undirectedRMatGraph(int scale, int edgeFactor) throws Exception {
    long vertexCount = 1L << scale;
    long edgeCount = edgeFactor * vertexCount;
    return new RMatGraph<>(env, new JDKRandomGeneratorFactory(), vertexCount, edgeCount).generate().run(new org.apache.flink.graph.asm.simple.undirected.Simplify<>(false));
}