Package org.apache.hadoop.mapred.MRCaching

Examples of org.apache.hadoop.mapred.MRCaching.TestResult

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                                           mr.createJobConf());
      double error = Math.abs(Math.PI - estimate);
      assertTrue("Error in PI estimation "+error+" exceeds 0.01", (error < 0.01));
      // run the wordcount example with caching
      JobConf job = mr.createJobConf();
      TestResult ret = MRCaching.launchMRCache(TEST_ROOT_DIR + "/wc/input",
                                            TEST_ROOT_DIR + "/wc/output",
                                            TEST_ROOT_DIR + "/cachedir",
                                            job,
                                            "The quick brown fox\n"
                                            + "has many silly\n"
View Full Code Here
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                                           mr.createJobConf());
      double error = Math.abs(Math.PI - estimate);
      assertTrue("Error in PI estimation "+error+" exceeds 0.01", (error < 0.01));
      // run the wordcount example with caching
      JobConf job = mr.createJobConf();
      TestResult ret = MRCaching.launchMRCache(TEST_ROOT_DIR + "/wc/input",
                                            TEST_ROOT_DIR + "/wc/output",
                                            TEST_ROOT_DIR + "/cachedir",
                                            job,
                                            "The quick brown fox\n"
                                            + "has many silly\n"
View Full Code Here
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      mr = new MiniMRCluster(2, "file:///", 3);
      TestMiniMRWithDFS.runPI(mr, mr.createJobConf());

      // run the wordcount example with caching
      JobConf job = mr.createJobConf();
      TestResult ret = MRCaching.launchMRCache(TEST_ROOT_DIR + "/wc/input",
                                            TEST_ROOT_DIR + "/wc/output",
                                            TEST_ROOT_DIR + "/cachedir",
                                            job,
                                            "The quick brown fox\n"
                                            + "has many silly\n"
View Full Code Here
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                                           mr.createJobConf());
      double error = Math.abs(Math.PI - estimate);
      assertTrue("Error in PI estimation "+error+" exceeds 0.01", (error < 0.01));
      // run the wordcount example with caching
      JobConf job = mr.createJobConf();
      TestResult ret = MRCaching.launchMRCache(TEST_ROOT_DIR + "/wc/input",
                                            TEST_ROOT_DIR + "/wc/output",
                                            TEST_ROOT_DIR + "/cachedir",
                                            job,
                                            "The quick brown fox\n"
                                            + "has many silly\n"
View Full Code Here
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               "org.apache.hadoop.hdfs.ChecksumDistributedFileSystem");     
      dfs = new MiniDFSCluster(conf, 1, true, null);
      fileSys = dfs.getFileSystem();
      mr = new MiniMRCluster(2, fileSys.getName(), 4);
      // run the wordcount example with caching
      TestResult ret = MRCaching.launchMRCache("/testing/wc/input",
                                            "/testing/wc/output",
                                            "/cachedir",
                                            mr.createJobConf(),
                                            "The quick brown fox\nhas many silly\n"
                                            + "red fox sox\n");
View Full Code Here
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      mr = new MiniMRCluster(2, "file:///", 3);
      TestMiniMRWithDFS.runPI(mr, mr.createJobConf());

      // run the wordcount example with caching
      JobConf job = mr.createJobConf();
      TestResult ret = MRCaching.launchMRCache(TEST_ROOT_DIR + "/wc/input",
                                            TEST_ROOT_DIR + "/wc/output",
                                            TEST_ROOT_DIR + "/cachedir",
                                            job,
                                            "The quick brown fox\n"
                                            + "has many silly\n"
View Full Code Here
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                                           mr.createJobConf());
      double error = Math.abs(Math.PI - estimate);
      assertTrue("Error in PI estimation "+error+" exceeds 0.01", (error < 0.01));
      // run the wordcount example with caching
      JobConf job = mr.createJobConf();
      TestResult ret = MRCaching.launchMRCache(TEST_ROOT_DIR + "/wc/input",
                                            TEST_ROOT_DIR + "/wc/output",
                                            TEST_ROOT_DIR + "/cachedir",
                                            job,
                                            "The quick brown fox\n"
                                            + "has many silly\n"
View Full Code Here
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      dfs = new MiniDFSCluster(conf, 1, true, null);
      fileSys = dfs.getFileSystem();
      mr = new MiniMRCluster(2, fileSys.getUri().toString(), 4);
      MRCaching.setupCache("/cachedir", fileSys);
      // run the wordcount example with caching
      TestResult ret = MRCaching.launchMRCache("/testing/wc/input",
                                            "/testing/wc/output",
                                            "/cachedir",
                                            mr.createJobConf(),
                                            "The quick brown fox\nhas many silly\n"
                                            + "red fox sox\n", false);
View Full Code Here
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      TestMiniMRWithDFS.runPI(mr, mr.createJobConf());

      // run the wordcount example with caching
      JobConf job = mr.createJobConf();
      TestResult ret = MRCaching.launchMRCache(TEST_ROOT_DIR + "/wc/input",
                                            TEST_ROOT_DIR + "/wc/output",
                                            TEST_ROOT_DIR + "/cachedir",
                                            job,
                                            "The quick brown fox\n"
                                            + "has many silly\n"
View Full Code Here
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      dfs = new MiniDFSCluster(conf, 1, true, null);
      fileSys = dfs.getFileSystem();
      mr = new MiniMRCluster(2, fileSys.getUri().toString(), 4);
      MRCaching.setupCache("/cachedir", fileSys);
      // run the wordcount example with caching
      TestResult ret = MRCaching.launchMRCache("/testing/wc/input",
                                            "/testing/wc/output",
                                            "/cachedir",
                                            mr.createJobConf(),
                                            "The quick brown fox\nhas many silly\n"
                                            + "red fox sox\n");
View Full Code Here
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Related Classes of org.apache.hadoop.mapred.MRCaching.TestResult

  • org.apache.hadoop.mapred.TestMiniMRDFSCaching
  • org.apache.hadoop.mapred.TestMiniMRLocalFS
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