Examples with NumberFormat java.text.NumberFormat used on opensource projects

Example 1 with NumberFormat

use of java.text.NumberFormat in project camel by apache.

the class BindyAbstractFactory method getNumberFormat.

private static NumberFormat getNumberFormat() {
    // Get instance of NumberFormat
    NumberFormat nf = NumberFormat.getInstance();
    // set max number of digits to 3 (thousands)
    nf.setMaximumIntegerDigits(3);
    nf.setMinimumIntegerDigits(3);
    return nf;
}

Example 2 with NumberFormat

use of java.text.NumberFormat in project camel by apache.

the class TimeUtils method printDuration.

/**
     * Prints the duration in a human readable format as X days Y hours Z minutes etc.
     *
     * @param uptime the uptime in millis
     * @return the time used for displaying on screen or in logs
     */
public static String printDuration(double uptime) {
    // Code taken from Karaf
    // https://svn.apache.org/repos/asf/karaf/trunk/shell/commands/src/main/java/org/apache/karaf/shell/commands/impl/InfoAction.java
    NumberFormat fmtI = new DecimalFormat("###,###", new DecimalFormatSymbols(Locale.ENGLISH));
    NumberFormat fmtD = new DecimalFormat("###,##0.000", new DecimalFormatSymbols(Locale.ENGLISH));
    uptime /= 1000;
    if (uptime < 60) {
        return fmtD.format(uptime) + " seconds";
    }
    uptime /= 60;
    if (uptime < 60) {
        long minutes = (long) uptime;
        String s = fmtI.format(minutes) + (minutes > 1 ? " minutes" : " minute");
        return s;
    }
    uptime /= 60;
    if (uptime < 24) {
        long hours = (long) uptime;
        long minutes = (long) ((uptime - hours) * 60);
        String s = fmtI.format(hours) + (hours > 1 ? " hours" : " hour");
        if (minutes != 0) {
            s += " " + fmtI.format(minutes) + (minutes > 1 ? " minutes" : " minute");
        }
        return s;
    }
    uptime /= 24;
    long days = (long) uptime;
    long hours = (long) ((uptime - days) * 24);
    String s = fmtI.format(days) + (days > 1 ? " days" : " day");
    if (hours != 0) {
        s += " " + fmtI.format(hours) + (hours > 1 ? " hours" : " hour");
    }
    return s;
}

Example 3 with NumberFormat

use of java.text.NumberFormat in project flink by apache.

the class ClusteringCoefficient 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);
    // global and local clustering coefficient results
    GraphAnalytic gcc;
    GraphAnalytic acc;
    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) {
                                if (parameters.getBoolean("simplify", false)) {
                                    graph = graph.run(new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>().setParallelism(little_parallelism));
                                }
                                gcc = graph.run(new org.apache.flink.graph.library.clustering.directed.GlobalClusteringCoefficient<LongValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                                acc = graph.run(new org.apache.flink.graph.library.clustering.directed.AverageClusteringCoefficient<LongValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                                lcc = graph.run(new org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient<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));
                                }
                                gcc = graph.run(new org.apache.flink.graph.library.clustering.undirected.GlobalClusteringCoefficient<LongValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                                acc = graph.run(new org.apache.flink.graph.library.clustering.undirected.AverageClusteringCoefficient<LongValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                                lcc = graph.run(new org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient<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));
                                }
                                gcc = graph.run(new org.apache.flink.graph.library.clustering.directed.GlobalClusteringCoefficient<StringValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                                acc = graph.run(new org.apache.flink.graph.library.clustering.directed.AverageClusteringCoefficient<StringValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                                lcc = graph.run(new org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient<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));
                                }
                                gcc = graph.run(new org.apache.flink.graph.library.clustering.undirected.GlobalClusteringCoefficient<StringValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                                acc = graph.run(new org.apache.flink.graph.library.clustering.undirected.AverageClusteringCoefficient<StringValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                                lcc = graph.run(new org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient<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();
                if (directedAlgorithm) {
                    if (scale > 32) {
                        Graph<LongValue, NullValue, NullValue> newGraph = graph.run(new org.apache.flink.graph.asm.simple.directed.Simplify<LongValue, NullValue, NullValue>().setParallelism(little_parallelism));
                        gcc = newGraph.run(new org.apache.flink.graph.library.clustering.directed.GlobalClusteringCoefficient<LongValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                        acc = newGraph.run(new org.apache.flink.graph.library.clustering.directed.AverageClusteringCoefficient<LongValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                        lcc = newGraph.run(new org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient<LongValue, NullValue, NullValue>().setIncludeZeroDegreeVertices(false).setLittleParallelism(little_parallelism));
                    } else {
                        Graph<IntValue, NullValue, NullValue> newGraph = graph.run(new TranslateGraphIds<LongValue, IntValue, NullValue, NullValue>(new LongValueToUnsignedIntValue()).setParallelism(little_parallelism)).run(new org.apache.flink.graph.asm.simple.directed.Simplify<IntValue, NullValue, NullValue>().setParallelism(little_parallelism));
                        gcc = newGraph.run(new org.apache.flink.graph.library.clustering.directed.GlobalClusteringCoefficient<IntValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                        acc = newGraph.run(new org.apache.flink.graph.library.clustering.directed.AverageClusteringCoefficient<IntValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                        lcc = newGraph.run(new org.apache.flink.graph.library.clustering.directed.LocalClusteringCoefficient<IntValue, NullValue, NullValue>().setIncludeZeroDegreeVertices(false).setLittleParallelism(little_parallelism));
                    }
                } 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).setParallelism(little_parallelism));
                        gcc = newGraph.run(new org.apache.flink.graph.library.clustering.undirected.GlobalClusteringCoefficient<LongValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                        acc = newGraph.run(new org.apache.flink.graph.library.clustering.undirected.AverageClusteringCoefficient<LongValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                        lcc = newGraph.run(new org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient<LongValue, NullValue, NullValue>().setIncludeZeroDegreeVertices(false).setLittleParallelism(little_parallelism));
                    } else {
                        Graph<IntValue, NullValue, NullValue> newGraph = 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));
                        gcc = newGraph.run(new org.apache.flink.graph.library.clustering.undirected.GlobalClusteringCoefficient<IntValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                        acc = newGraph.run(new org.apache.flink.graph.library.clustering.undirected.AverageClusteringCoefficient<IntValue, NullValue, NullValue>().setLittleParallelism(little_parallelism));
                        lcc = newGraph.run(new org.apache.flink.graph.library.clustering.undirected.LocalClusteringCoefficient<IntValue, NullValue, NullValue>().setIncludeZeroDegreeVertices(false).setLittleParallelism(little_parallelism));
                    }
                }
            }
            break;
        default:
            throw new ProgramParametrizationException(getUsage("invalid input type"));
    }
    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.toPrintableString());
                }
            } 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.toPrintableString());
                }
            }
            break;
        case "hash":
            System.out.println(DataSetUtils.checksumHashCode(lcc));
            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);
            env.execute("Clustering Coefficient");
            break;
        default:
            throw new ProgramParametrizationException(getUsage("invalid output type"));
    }
    System.out.println(gcc.getResult());
    System.out.println(acc.getResult());
    JobExecutionResult result = env.getLastJobExecutionResult();
    NumberFormat nf = NumberFormat.getInstance();
    System.out.println("Execution runtime: " + nf.format(result.getNetRuntime()) + " ms");
}

Example 4 with NumberFormat

use of java.text.NumberFormat in project flink by apache.

the class Graph500 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 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");
}

Example 5 with NumberFormat

use of java.text.NumberFormat in project flink by apache.

the class HITS 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);
    int iterations = parameters.getInt("iterations", DEFAULT_ITERATIONS);
    DataSet hits;
    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");
}