本文整理了Java中org.apache.crunch.types.writable.Writables.longs()方法的一些代码示例，展示了Writables.longs()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Writables.longs()方法的具体详情如下：
包路径：org.apache.crunch.types.writable.Writables
类名称：Writables
方法名：longs

Writables.longs介绍

暂无

代码示例

代码示例来源：origin: org.apache.crunch/crunch

public PType<Long> longs() {
 return Writables.longs();
}

代码示例来源：origin: cloudera/crunch

public PType<Long> longs() {
 return Writables.longs();
}

代码示例来源：origin: org.apache.crunch/crunch-core

public PType<Long> longs() {
 return Writables.longs();
}

代码示例来源：origin: cloudera/search

/** Randomizes the order of the items in the collection via a MapReduce job */
private static <T> PCollection<T> randomize(PCollection<T> items) {
 PTable<Long, T> table = items.by("randomize", new RandomizeFn<T>(), Writables.longs());
 table = Sort.sort(table, Sort.Order.ASCENDING);
 return table.values();
}

代码示例来源：origin: apache/crunch

public int run(String[] args) throws Exception {
 if (args.length != 2) {
  System.err.println();
  System.err.println("Two and only two arguments are accepted.");
  System.err.println("Usage: " + this.getClass().getName() + " [generic options] input output");
  System.err.println();
  GenericOptionsParser.printGenericCommandUsage(System.err);
  return 1;
 }
 // Create an object to coordinate pipeline creation and execution.
 Pipeline pipeline = new MRPipeline(TotalBytesByIP.class, getConf());
 // Reference a given text file as a collection of Strings.
 PCollection<String> lines = pipeline.readTextFile(args[0]);
 // Aggregator used for summing up response size
 Aggregator<Long> agg = Aggregators.SUM_LONGS();
 // Table of (ip, sum(response size))
 PTable<String, Long> ipAddrResponseSize = lines
   .parallelDo(extractIPResponseSize, Writables.tableOf(Writables.strings(), Writables.longs())).groupByKey()
   .combineValues(agg);
 pipeline.writeTextFile(ipAddrResponseSize, args[1]);
 // Execute the pipeline as a MapReduce.
 PipelineResult result = pipeline.done();
 return result.succeeded() ? 0 : 1;
}

代码示例来源：origin: apache/crunch

public int run(String[] args) throws Exception {
 if (args.length != 1) {
  System.err.println();
  System.err.println("Usage: " + this.getClass().getName() + " [generic options] input");
  System.err.println();
  GenericOptionsParser.printGenericCommandUsage(System.err);
  return 1;
 }
 // Create an object to coordinate pipeline creation and execution.
 Pipeline pipeline = new MRPipeline(TotalWordCount.class, getConf());
 // Reference a given text file as a collection of Strings.
 PCollection<String> lines = pipeline.readTextFile(args[0]);
 // Define a function that splits each line in a PCollection of Strings into
 // a
 // PCollection made up of the individual words in the file.
 PCollection<Long> numberOfWords = lines.parallelDo(new DoFn<String, Long>() {
  public void process(String line, Emitter<Long> emitter) {
   emitter.emit((long)line.split("\\s+").length);
  }
 }, Writables.longs()); // Indicates the serialization format
 // The aggregate method groups a collection into a single PObject.
 PObject<Long> totalCount = numberOfWords.aggregate(Aggregators.SUM_LONGS()).first();
 // Execute the pipeline as a MapReduce.
 PipelineResult result = pipeline.run();
 System.out.println("Total number of words: " + totalCount.getValue());
 
 pipeline.done();
 return result.succeeded() ? 0 : 1;
}

代码示例来源：origin: apache/crunch

public int run(String[] args) throws Exception {
 if (args.length != 2) {
  System.err.println();
  System.err.println("Two and only two arguments are accepted.");
  System.err.println("Usage: " + this.getClass().getName() + " [generic options] input output");
  System.err.println();
  GenericOptionsParser.printGenericCommandUsage(System.err);
  return 1;
 }
 // Create an object to coordinate pipeline creation and execution.
 Pipeline pipeline = new MRPipeline(AverageBytesByIP.class, getConf());
 // Reference a given text file as a collection of Strings.
 PCollection<String> lines = pipeline.readTextFile(args[0]);
 // Aggregator used for summing up response size and count
 Aggregator<Pair<Long, Long>> agg = pairAggregator(SUM_LONGS(), SUM_LONGS());
 // Table of (ip, sum(response size), count)
 PTable<String, Pair<Long, Long>> remoteAddrResponseSize = lines
   .parallelDo(extractResponseSize,
     Writables.tableOf(Writables.strings(), Writables.pairs(Writables.longs(), Writables.longs()))).groupByKey()
   .combineValues(agg);
 // Calculate average response size by ip address
 PTable<String, Double> avgs = remoteAddrResponseSize.parallelDo(calulateAverage,
   Writables.tableOf(Writables.strings(), Writables.doubles()));
 // write the result to a text file
 pipeline.writeTextFile(avgs, args[1]);
 // Execute the pipeline as a MapReduce.
 PipelineResult result = pipeline.done();
 return result.succeeded() ? 0 : 1;
}

代码示例来源：origin: cloudera/search

WritableTypeFamily.getInstance().tableOf(Writables.longs(), Writables.strings()),