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Java JobConf.setPartitionerClass方法代碼示例

本文整理匯總了Java中org.apache.hadoop.mapred.JobConf.setPartitionerClass方法的典型用法代碼示例。如果您正苦於以下問題:Java JobConf.setPartitionerClass方法的具體用法?Java JobConf.setPartitionerClass怎麽用?Java JobConf.setPartitionerClass使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在org.apache.hadoop.mapred.JobConf的用法示例。


在下文中一共展示了JobConf.setPartitionerClass方法的3個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Java代碼示例。

示例1: getJob

import org.apache.hadoop.mapred.JobConf; //導入方法依賴的package包/類
/**
 * Sets up a job conf for the given job using the given config object. Ensures
 * that the correct input format is set, the mapper and and reducer class and
 * the input and output keys and value classes along with any other job
 * configuration.
 * 
 * @param config
 * @return JobConf representing the job to be ran
 * @throws IOException
 */
private JobConf getJob(ConfigExtractor config) throws IOException {
  JobConf job = new JobConf(config.getConfig(), SliveTest.class);
  job.setInputFormat(DummyInputFormat.class);
  FileOutputFormat.setOutputPath(job, config.getOutputPath());
  job.setMapperClass(SliveMapper.class);
  job.setPartitionerClass(SlivePartitioner.class);
  job.setReducerClass(SliveReducer.class);
  job.setOutputKeyClass(Text.class);
  job.setOutputValueClass(Text.class);
  job.setOutputFormat(TextOutputFormat.class);
  TextOutputFormat.setCompressOutput(job, false);
  job.setNumReduceTasks(config.getReducerAmount());
  job.setNumMapTasks(config.getMapAmount());
  return job;
}
 
開發者ID:naver,項目名稱:hadoop,代碼行數:26,代碼來源:SliveTest.java

示例2: initTableReduceJob

import org.apache.hadoop.mapred.JobConf; //導入方法依賴的package包/類
/**
 * Use this before submitting a TableReduce job. It will
 * appropriately set up the JobConf.
 *
 * @param table  The output table.
 * @param reducer  The reducer class to use.
 * @param job  The current job configuration to adjust.
 * @param partitioner  Partitioner to use. Pass <code>null</code> to use
 * default partitioner.
 * @param addDependencyJars upload HBase jars and jars for any of the configured
 *           job classes via the distributed cache (tmpjars).
 * @throws IOException When determining the region count fails.
 */
public static void initTableReduceJob(String table,
  Class<? extends TableReduce> reducer, JobConf job, Class partitioner,
  boolean addDependencyJars) throws IOException {
  job.setOutputFormat(TableOutputFormat.class);
  job.setReducerClass(reducer);
  job.set(TableOutputFormat.OUTPUT_TABLE, table);
  job.setOutputKeyClass(ImmutableBytesWritable.class);
  job.setOutputValueClass(Put.class);
  job.setStrings("io.serializations", job.get("io.serializations"),
      MutationSerialization.class.getName(), ResultSerialization.class.getName());
  if (partitioner == HRegionPartitioner.class) {
    job.setPartitionerClass(HRegionPartitioner.class);
    int regions =
      MetaTableAccessor.getRegionCount(HBaseConfiguration.create(job), TableName.valueOf(table));
    if (job.getNumReduceTasks() > regions) {
      job.setNumReduceTasks(regions);
    }
  } else if (partitioner != null) {
    job.setPartitionerClass(partitioner);
  }
  if (addDependencyJars) {
    addDependencyJars(job);
  }
  initCredentials(job);
}
 
開發者ID:fengchen8086,項目名稱:ditb,代碼行數:39,代碼來源:TableMapReduceUtil.java

示例3: setupPipesJob

import org.apache.hadoop.mapred.JobConf; //導入方法依賴的package包/類
private static void setupPipesJob(JobConf conf) throws IOException {
  // default map output types to Text
  if (!getIsJavaMapper(conf)) {
    conf.setMapRunnerClass(PipesMapRunner.class);
    // Save the user's partitioner and hook in our's.
    setJavaPartitioner(conf, conf.getPartitionerClass());
    conf.setPartitionerClass(PipesPartitioner.class);
  }
  if (!getIsJavaReducer(conf)) {
    conf.setReducerClass(PipesReducer.class);
    if (!getIsJavaRecordWriter(conf)) {
      conf.setOutputFormat(NullOutputFormat.class);
    }
  }
  String textClassname = Text.class.getName();
  setIfUnset(conf, MRJobConfig.MAP_OUTPUT_KEY_CLASS, textClassname);
  setIfUnset(conf, MRJobConfig.MAP_OUTPUT_VALUE_CLASS, textClassname);
  setIfUnset(conf, MRJobConfig.OUTPUT_KEY_CLASS, textClassname);
  setIfUnset(conf, MRJobConfig.OUTPUT_VALUE_CLASS, textClassname);
  
  // Use PipesNonJavaInputFormat if necessary to handle progress reporting
  // from C++ RecordReaders ...
  if (!getIsJavaRecordReader(conf) && !getIsJavaMapper(conf)) {
    conf.setClass(Submitter.INPUT_FORMAT, 
                  conf.getInputFormat().getClass(), InputFormat.class);
    conf.setInputFormat(PipesNonJavaInputFormat.class);
  }
  
  String exec = getExecutable(conf);
  if (exec == null) {
    throw new IllegalArgumentException("No application program defined.");
  }
  // add default debug script only when executable is expressed as
  // <path>#<executable>
  if (exec.contains("#")) {
    // set default gdb commands for map and reduce task 
    String defScript = "$HADOOP_PREFIX/src/c++/pipes/debug/pipes-default-script";
    setIfUnset(conf, MRJobConfig.MAP_DEBUG_SCRIPT,defScript);
    setIfUnset(conf, MRJobConfig.REDUCE_DEBUG_SCRIPT,defScript);
  }
  URI[] fileCache = DistributedCache.getCacheFiles(conf);
  if (fileCache == null) {
    fileCache = new URI[1];
  } else {
    URI[] tmp = new URI[fileCache.length+1];
    System.arraycopy(fileCache, 0, tmp, 1, fileCache.length);
    fileCache = tmp;
  }
  try {
    fileCache[0] = new URI(exec);
  } catch (URISyntaxException e) {
    IOException ie = new IOException("Problem parsing execable URI " + exec);
    ie.initCause(e);
    throw ie;
  }
  DistributedCache.setCacheFiles(fileCache, conf);
}
 
開發者ID:naver,項目名稱:hadoop,代碼行數:58,代碼來源:Submitter.java


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