Package org.apache.hadoop.hive.ql.plan

Examples of org.apache.hadoop.hive.ql.plan.ReduceWork


    Context ctx = driverContext.getCtx();
    boolean ctxCreated = false;
    Path emptyScratchDir;

    MapWork mWork = work.getMapWork();
    ReduceWork rWork = work.getReduceWork();

    try {
      if (ctx == null) {
        ctx = new Context(job);
        ctxCreated = true;
      }

      emptyScratchDir = ctx.getMRTmpPath();
      FileSystem fs = emptyScratchDir.getFileSystem(job);
      fs.mkdirs(emptyScratchDir);
    } catch (IOException e) {
      e.printStackTrace();
      console.printError("Error launching map-reduce job", "\n"
          + org.apache.hadoop.util.StringUtils.stringifyException(e));
      return 5;
    }

    ShimLoader.getHadoopShims().prepareJobOutput(job);
    //See the javadoc on HiveOutputFormatImpl and HadoopShims.prepareJobOutput()
    job.setOutputFormat(HiveOutputFormatImpl.class);

    job.setMapperClass(ExecMapper.class);

    job.setMapOutputKeyClass(HiveKey.class);
    job.setMapOutputValueClass(BytesWritable.class);

    try {
      job.setPartitionerClass((Class<? extends Partitioner>) (Class.forName(HiveConf.getVar(job,
          HiveConf.ConfVars.HIVEPARTITIONER))));
    } catch (ClassNotFoundException e) {
      throw new RuntimeException(e.getMessage());
    }

    if (mWork.getNumMapTasks() != null) {
      job.setNumMapTasks(mWork.getNumMapTasks().intValue());
    }

    if (mWork.getMaxSplitSize() != null) {
      HiveConf.setLongVar(job, HiveConf.ConfVars.MAPREDMAXSPLITSIZE, mWork.getMaxSplitSize().longValue());
    }

    if (mWork.getMinSplitSize() != null) {
      HiveConf.setLongVar(job, HiveConf.ConfVars.MAPREDMINSPLITSIZE, mWork.getMinSplitSize().longValue());
    }

    if (mWork.getMinSplitSizePerNode() != null) {
      HiveConf.setLongVar(job, HiveConf.ConfVars.MAPREDMINSPLITSIZEPERNODE, mWork.getMinSplitSizePerNode().longValue());
    }

    if (mWork.getMinSplitSizePerRack() != null) {
      HiveConf.setLongVar(job, HiveConf.ConfVars.MAPREDMINSPLITSIZEPERRACK, mWork.getMinSplitSizePerRack().longValue());
    }

    job.setNumReduceTasks(rWork != null ? rWork.getNumReduceTasks().intValue() : 0);
    job.setReducerClass(ExecReducer.class);

    // set input format information if necessary
    setInputAttributes(job);

    // Turn on speculative execution for reducers
    boolean useSpeculativeExecReducers = HiveConf.getBoolVar(job,
        HiveConf.ConfVars.HIVESPECULATIVEEXECREDUCERS);
    HiveConf.setBoolVar(job, HiveConf.ConfVars.HADOOPSPECULATIVEEXECREDUCERS,
        useSpeculativeExecReducers);

    String inpFormat = HiveConf.getVar(job, HiveConf.ConfVars.HIVEINPUTFORMAT);
    if ((inpFormat == null) || (!StringUtils.isNotBlank(inpFormat))) {
      inpFormat = ShimLoader.getHadoopShims().getInputFormatClassName();
    }

    if (mWork.isUseBucketizedHiveInputFormat()) {
      inpFormat = BucketizedHiveInputFormat.class.getName();
    }

    LOG.info("Using " + inpFormat);

    try {
      job.setInputFormat((Class<? extends InputFormat>) (Class.forName(inpFormat)));
    } catch (ClassNotFoundException e) {
      throw new RuntimeException(e.getMessage());
    }


    // No-Op - we don't really write anything here ..
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(Text.class);

    // Transfer HIVEAUXJARS and HIVEADDEDJARS to "tmpjars" so hadoop understands
    // it
    String auxJars = HiveConf.getVar(job, HiveConf.ConfVars.HIVEAUXJARS);
    String addedJars = HiveConf.getVar(job, HiveConf.ConfVars.HIVEADDEDJARS);
    if (StringUtils.isNotBlank(auxJars) || StringUtils.isNotBlank(addedJars)) {
      String allJars = StringUtils.isNotBlank(auxJars) ? (StringUtils.isNotBlank(addedJars) ? addedJars
          + "," + auxJars
          : auxJars)
          : addedJars;
      LOG.info("adding libjars: " + allJars);
      initializeFiles("tmpjars", allJars);
    }

    // Transfer HIVEADDEDFILES to "tmpfiles" so hadoop understands it
    String addedFiles = HiveConf.getVar(job, HiveConf.ConfVars.HIVEADDEDFILES);
    if (StringUtils.isNotBlank(addedFiles)) {
      initializeFiles("tmpfiles", addedFiles);
    }
    int returnVal = 0;
    boolean noName = StringUtils.isEmpty(HiveConf.getVar(job, HiveConf.ConfVars.HADOOPJOBNAME));

    if (noName) {
      // This is for a special case to ensure unit tests pass
      HiveConf.setVar(job, HiveConf.ConfVars.HADOOPJOBNAME, "JOB" + Utilities.randGen.nextInt());
    }
    String addedArchives = HiveConf.getVar(job, HiveConf.ConfVars.HIVEADDEDARCHIVES);
    // Transfer HIVEADDEDARCHIVES to "tmparchives" so hadoop understands it
    if (StringUtils.isNotBlank(addedArchives)) {
      initializeFiles("tmparchives", addedArchives);
    }

    try{
      MapredLocalWork localwork = mWork.getMapRedLocalWork();
      if (localwork != null && localwork.hasStagedAlias()) {
        if (!ShimLoader.getHadoopShims().isLocalMode(job)) {
          Path localPath = localwork.getTmpPath();
          Path hdfsPath = mWork.getTmpHDFSPath();

          FileSystem hdfs = hdfsPath.getFileSystem(job);
          FileSystem localFS = localPath.getFileSystem(job);
          FileStatus[] hashtableFiles = localFS.listStatus(localPath);
          int fileNumber = hashtableFiles.length;
          String[] fileNames = new String[fileNumber];

          for ( int i = 0; i < fileNumber; i++){
            fileNames[i] = hashtableFiles[i].getPath().getName();
          }

          //package and compress all the hashtable files to an archive file
          String stageId = this.getId();
          String archiveFileName = Utilities.generateTarFileName(stageId);
          localwork.setStageID(stageId);

          CompressionUtils.tar(localPath.toUri().getPath(), fileNames,archiveFileName);
          Path archivePath = Utilities.generateTarPath(localPath, stageId);
          LOG.info("Archive "+ hashtableFiles.length+" hash table files to " + archivePath);

          //upload archive file to hdfs
          Path hdfsFilePath =Utilities.generateTarPath(hdfsPath, stageId);
          short replication = (short) job.getInt("mapred.submit.replication", 10);
          hdfs.copyFromLocalFile(archivePath, hdfsFilePath);
          hdfs.setReplication(hdfsFilePath, replication);
          LOG.info("Upload 1 archive file  from" + archivePath + " to: " + hdfsFilePath);

          //add the archive file to distributed cache
          DistributedCache.createSymlink(job);
          DistributedCache.addCacheArchive(hdfsFilePath.toUri(), job);
          LOG.info("Add 1 archive file to distributed cache. Archive file: " + hdfsFilePath.toUri());
        }
      }
      work.configureJobConf(job);
      List<Path> inputPaths = Utilities.getInputPaths(job, mWork, emptyScratchDir, ctx, false);
      Utilities.setInputPaths(job, inputPaths);

      Utilities.setMapRedWork(job, work, ctx.getMRTmpPath());

      if (mWork.getSamplingType() > 0 && rWork != null && job.getNumReduceTasks() > 1) {
        try {
          handleSampling(driverContext, mWork, job, conf);
          job.setPartitionerClass(HiveTotalOrderPartitioner.class);
        } catch (IllegalStateException e) {
          console.printInfo("Not enough sampling data.. Rolling back to single reducer task");
          rWork.setNumReduceTasks(1);
          job.setNumReduceTasks(1);
        } catch (Exception e) {
          LOG.error("Sampling error", e);
          console.printError(e.toString(),
              "\n" + org.apache.hadoop.util.StringUtils.stringifyException(e));
          rWork.setNumReduceTasks(1);
          job.setNumReduceTasks(1);
        }
      }

      // remove the pwd from conf file so that job tracker doesn't show this
      // logs
      String pwd = HiveConf.getVar(job, HiveConf.ConfVars.METASTOREPWD);
      if (pwd != null) {
        HiveConf.setVar(job, HiveConf.ConfVars.METASTOREPWD, "HIVE");
      }
      JobClient jc = new JobClient(job);
      // make this client wait if job tracker is not behaving well.
      Throttle.checkJobTracker(job, LOG);

      if (mWork.isGatheringStats() || (rWork != null && rWork.isGatheringStats())) {
        // initialize stats publishing table
        StatsPublisher statsPublisher;
        StatsFactory factory = StatsFactory.newFactory(job);
        if (factory != null) {
          statsPublisher = factory.getStatsPublisher();
          if (!statsPublisher.init(job)) { // creating stats table if not exists
            if (HiveConf.getBoolVar(job, HiveConf.ConfVars.HIVE_STATS_RELIABLE)) {
              throw
                new HiveException(ErrorMsg.STATSPUBLISHER_INITIALIZATION_ERROR.getErrorCodedMsg());
            }
          }
        }
      }

      Utilities.createTmpDirs(job, mWork);
      Utilities.createTmpDirs(job, rWork);

      SessionState ss = SessionState.get();
      if (HiveConf.getVar(job, HiveConf.ConfVars.HIVE_EXECUTION_ENGINE).equals("tez")
          && ss != null) {
        TezSessionState session = ss.getTezSession();
        TezSessionPoolManager.getInstance().close(session, true);
      }

      // Finally SUBMIT the JOB!
      rj = jc.submitJob(job);
      // replace it back
      if (pwd != null) {
        HiveConf.setVar(job, HiveConf.ConfVars.METASTOREPWD, pwd);
      }

      returnVal = jobExecHelper.progress(rj, jc, ctx.getHiveTxnManager());
      success = (returnVal == 0);
    } catch (Exception e) {
      e.printStackTrace();
      String mesg = " with exception '" + Utilities.getNameMessage(e) + "'";
      if (rj != null) {
        mesg = "Ended Job = " + rj.getJobID() + mesg;
      } else {
        mesg = "Job Submission failed" + mesg;
      }

      // Has to use full name to make sure it does not conflict with
      // org.apache.commons.lang.StringUtils
      console.printError(mesg, "\n" + org.apache.hadoop.util.StringUtils.stringifyException(e));

      success = false;
      returnVal = 1;
    } finally {
      Utilities.clearWork(job);
      try {
        if (ctxCreated) {
          ctx.clear();
        }

        if (rj != null) {
          if (returnVal != 0) {
            rj.killJob();
          }
          HadoopJobExecHelper.runningJobs.remove(rj);
          jobID = rj.getID().toString();
        }
      } catch (Exception e) {
      }
    }

    // get the list of Dynamic partition paths
    try {
      if (rj != null) {
        if (mWork.getAliasToWork() != null) {
          for (Operator<? extends OperatorDesc> op : mWork.getAliasToWork().values()) {
            op.jobClose(job, success);
          }
        }
        if (rWork != null) {
          rWork.getReducer().jobClose(job, success);
        }
      }
    } catch (Exception e) {
      // jobClose needs to execute successfully otherwise fail task
      if (success) {
View Full Code Here


        getMapJoinOperator(newTask, newWork, smbJoinOp, joinTree, bigTablePosition);

    // The reducer needs to be restored - Consider a query like:
    // select count(*) FROM bucket_big a JOIN bucket_small b ON a.key = b.key;
    // The reducer contains a groupby, which needs to be restored.
    ReduceWork rWork = newWork.getReduceWork();

    // create the local work for this plan
    MapJoinProcessor.genLocalWorkForMapJoin(newWork, newMapJoinOp, bigTablePosition);

    // restore the reducer
View Full Code Here

    return true;
  }

  private JoinOperator getJoinOp(MapRedTask task) throws SemanticException {
    MapWork mWork = task.getWork().getMapWork();
    ReduceWork rWork = task.getWork().getReduceWork();
    if (rWork == null) {
      return null;
    }
    Operator<? extends OperatorDesc> reducerOp = rWork.getReducer();
    if (reducerOp instanceof JoinOperator) {
      /* Is any operator present, which prevents the conversion */
      Map<String, Operator<? extends OperatorDesc>> aliasToWork = mWork.getAliasToWork();
      for (Operator<? extends OperatorDesc> op : aliasToWork.values()) {
        if (!checkOperatorOKMapJoinConversion(op)) {
View Full Code Here

    HashMap<Operator<? extends OperatorDesc>, Task<? extends Serializable>> opTaskMap =
        opProcCtx.getOpTaskMap();
    Operator<? extends OperatorDesc> currTopOp = opProcCtx.getCurrTopOp();

    opTaskMap.put(reducer, currTask);
    plan.setReduceWork(new ReduceWork());
    plan.getReduceWork().setReducer(reducer);
    ReduceSinkDesc desc = op.getConf();

    plan.getReduceWork().setNumReduceTasks(desc.getNumReducers());
View Full Code Here

    HashMap<Operator<? extends OperatorDesc>, Task<? extends Serializable>> opTaskMap =
        opProcCtx.getOpTaskMap();

    opTaskMap.put(reducer, unionTask);

    plan.setReduceWork(new ReduceWork());
    plan.getReduceWork().setReducer(reducer);
    plan.getReduceWork().setReducer(reducer);
    ReduceSinkDesc desc = op.getConf();

    plan.getReduceWork().setNumReduceTasks(desc.getNumReducers());
View Full Code Here

    Task<? extends Serializable> childTask = TaskFactory.get(childPlan, parseCtx
        .getConf());
    Operator<? extends OperatorDesc> reducer = cRS.getChildOperators().get(0);

    // Add the reducer
    ReduceWork rWork = new ReduceWork();
    childPlan.setReduceWork(rWork);
    rWork.setReducer(reducer);
    ReduceSinkDesc desc = cRS.getConf();
    childPlan.getReduceWork().setNumReduceTasks(new Integer(desc.getNumReducers()));

    opProcCtx.getOpTaskMap().put(reducer, childTask);
View Full Code Here

        } else {
          // There are separate configuration parameters to control whether to
          // merge for a map-only job
          // or for a map-reduce job
          if (currTask.getWork() instanceof MapredWork) {
            ReduceWork reduceWork = ((MapredWork) currTask.getWork()).getReduceWork();
            boolean mergeMapOnly =
              hconf.getBoolVar(ConfVars.HIVEMERGEMAPFILES) && reduceWork == null;
            boolean mergeMapRed =
              hconf.getBoolVar(ConfVars.HIVEMERGEMAPREDFILES) &&
              reduceWork != null;
View Full Code Here

        .getReduceSinkDesc(Utilities.makeList(getStringColumn("key")),
        Utilities.makeList(getStringColumn("value")), outputColumns, true,
        -1, 1, -1, AcidUtils.Operation.NOT_ACID));

    addMapWork(mr, src, "a", op1);
    ReduceWork rWork = new ReduceWork();
    rWork.setNumReduceTasks(Integer.valueOf(1));
    rWork.setKeyDesc(op1.getConf().getKeySerializeInfo());
    rWork.getTagToValueDesc().add(op1.getConf().getValueSerializeInfo());
    mr.setReduceWork(rWork);

    // reduce side work
    Operator<FileSinkDesc> op3 = OperatorFactory.get(new FileSinkDesc(new Path(tmpdir + File.separator
        + "mapredplan1.out"), Utilities.defaultTd, false));

    Operator<ExtractDesc> op2 = OperatorFactory.get(new ExtractDesc(
        getStringColumn(Utilities.ReduceField.VALUE.toString())), op3);

    rWork.setReducer(op2);
  }
View Full Code Here

        Utilities
        .makeList(getStringColumn("key"), getStringColumn("value")),
        outputColumns, false, -1, 1, -1, AcidUtils.Operation.NOT_ACID));

    addMapWork(mr, src, "a", op1);
    ReduceWork rWork = new ReduceWork();
    rWork.setNumReduceTasks(Integer.valueOf(1));
    rWork.setKeyDesc(op1.getConf().getKeySerializeInfo());
    rWork.getTagToValueDesc().add(op1.getConf().getValueSerializeInfo());
    mr.setReduceWork(rWork);

    // reduce side work
    Operator<FileSinkDesc> op4 = OperatorFactory.get(new FileSinkDesc(new Path(tmpdir + File.separator
        + "mapredplan2.out"), Utilities.defaultTd, false));

    Operator<FilterDesc> op3 = OperatorFactory.get(getTestFilterDesc("0"), op4);

    Operator<ExtractDesc> op2 = OperatorFactory.get(new ExtractDesc(
        getStringColumn(Utilities.ReduceField.VALUE.toString())), op3);

    rWork.setReducer(op2);
  }
View Full Code Here

        .getReduceSinkDesc(Utilities.makeList(getStringColumn("key")),
        Utilities.makeList(getStringColumn("key")), outputColumns, true,
        Byte.valueOf((byte) 1), Integer.MAX_VALUE, -1, AcidUtils.Operation.NOT_ACID));

    addMapWork(mr, src2, "b", op2);
    ReduceWork rWork = new ReduceWork();
    rWork.setNumReduceTasks(Integer.valueOf(1));
    rWork.setNeedsTagging(true);
    rWork.setKeyDesc(op1.getConf().getKeySerializeInfo());
    rWork.getTagToValueDesc().add(op1.getConf().getValueSerializeInfo());

    mr.setReduceWork(rWork);
    rWork.getTagToValueDesc().add(op2.getConf().getValueSerializeInfo());

    // reduce side work
    Operator<FileSinkDesc> op4 = OperatorFactory.get(new FileSinkDesc(new Path(tmpdir + File.separator
        + "mapredplan3.out"), Utilities.defaultTd, false));

    Operator<SelectDesc> op5 = OperatorFactory.get(new SelectDesc(Utilities
        .makeList(new ExprNodeFieldDesc(TypeInfoFactory.stringTypeInfo,
        new ExprNodeColumnDesc(TypeInfoFactory.getListTypeInfo(TypeInfoFactory.stringTypeInfo),
        Utilities.ReduceField.VALUE.toString(), "", false), "0", false)),
        Utilities.makeList(outputColumns.get(0))), op4);

    rWork.setReducer(op5);
  }
View Full Code Here

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