Package org.apache.hadoop.hive.ql.exec

Examples of org.apache.hadoop.hive.ql.exec.GroupByOperator$varLenFields

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      for (ExprNodeDesc key : partitionCols) {
        if (!(key instanceof ExprNodeColumnDesc)) {
          shouldDetect = false;
        }
      }
      GroupByOperator cGBY =
          CorrelationUtilities.getSingleChild(op, GroupByOperator.class);
      if (cGBY != null) {
        if (CorrelationUtilities.hasGroupingSet(op) ||
            cGBY.getConf().isGroupingSetsPresent()) {
          // Do not support grouping set right now
          shouldDetect = false;
        }
      }
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  public static class GroupByRule implements NodeProcessor {

    @Override
    public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx procCtx,
        Object... nodeOutputs) throws SemanticException {
      GroupByOperator gbyOp = (GroupByOperator)nd;
      List<String> gbyKeys = new ArrayList<String>();
      for (ExprNodeDesc exprDesc : gbyOp.getConf().getKeys()) {
        for (Entry<String, ExprNodeDesc> entry : gbyOp.getColumnExprMap().entrySet()) {
          if (exprDesc.isSame(entry.getValue())) {
            gbyKeys.add(entry.getKey());
          }
        }
      }

      List<List<String>> listBucketCols = new ArrayList<List<String>>();
      listBucketCols.add(gbyKeys);
      OpTraits opTraits = new OpTraits(listBucketCols, -1, listBucketCols);
      gbyOp.setOpTraits(opTraits);
      return null;
    }
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            false);

    // ////// 2. Generate GroupbyOperator
    Map<String, GenericUDAFEvaluator> genericUDAFEvaluators =
        new LinkedHashMap<String, GenericUDAFEvaluator>();
    GroupByOperator groupByOperatorInfo = (GroupByOperator) genGroupByPlanGroupByOperator(
        parseInfo, dest, reduceSinkOperatorInfo, reduceSinkOperatorInfo, GroupByDesc.Mode.PARTIAL1,
        genericUDAFEvaluators);

    int numReducers = -1;
    if (grpByExprs.isEmpty()) {
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    // does it need an additional MR job
    boolean groupingSetsNeedAdditionalMRJob =
        groupingSetsPresent && groupingSets.size() > newMRJobGroupingSetsThreshold ?
            true : false;

    GroupByOperator groupByOperatorInfo =
        (GroupByOperator) genGroupByPlanMapGroupByOperator(
            qb,
            dest,
            grpByExprs,
            inputOperatorInfo,
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    }

    // ////// Generate GroupbyOperator for a map-side partial aggregation
    Map<String, GenericUDAFEvaluator> genericUDAFEvaluators =
        new LinkedHashMap<String, GenericUDAFEvaluator>();
    GroupByOperator groupByOperatorInfo =
        (GroupByOperator) genGroupByPlanMapGroupByOperator(
            qb, dest, grpByExprs, inputOperatorInfo, GroupByDesc.Mode.HASH,
            genericUDAFEvaluators, groupingSets, groupingSetsPresent);

    groupOpToInputTables.put(groupByOperatorInfo, opParseCtx.get(
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        return nd;
      }

      for (Node op : stack) {
        if (op instanceof GroupByOperator) {
          GroupByOperator gby = (GroupByOperator) op;
          if (!gby.getConf().isDistinctLike()) {
            // GroupBy not distinct like, disabling
            walkerCtx.convertNotMetadataOnly();
            return nd;
          }
        }
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      LocalMapJoinProcCtx context = (LocalMapJoinProcCtx) ctx;
      if (!nd.getName().equals("GBY")) {
        return null;
      }
      context.setFollowedByGroupBy(true);
      GroupByOperator groupByOp = (GroupByOperator) nd;
      float groupByMemoryUsage = context.getParseCtx().getConf().getFloatVar(
          HiveConf.ConfVars.HIVEMAPJOINFOLLOWEDBYMAPAGGRHASHMEMORY);
      groupByOp.getConf().setGroupByMemoryUsage(groupByMemoryUsage);
      return null;
    }
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   * Node Processor for Column Pruning on Group By Operators.
   */
  public static class ColumnPrunerGroupByProc implements NodeProcessor {
    public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx ctx,
        Object... nodeOutputs) throws SemanticException {
      GroupByOperator op = (GroupByOperator) nd;
      ColumnPrunerProcCtx cppCtx = (ColumnPrunerProcCtx) ctx;
      List<String> colLists = new ArrayList<String>();
      GroupByDesc conf = op.getConf();
      ArrayList<ExprNodeDesc> keys = conf.getKeys();
      for (ExprNodeDesc key : keys) {
        colLists = Utilities.mergeUniqElems(colLists, key.getCols());
      }

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        // distinct columns will be added to the key columns.
        boolean isCorrelated = sameKeys(rsKeyCols, backtrackedKeyCols) &&
            sameOrder(rsop.getConf().getOrder(), childRSOrder) &&
            sameKeys(backtrackedPartitionCols, rsPartitionCols) &&
            correlation.adjustNumReducers(rsop.getConf().getNumReducers());
        GroupByOperator cGBY =
            CorrelationUtilities.getSingleChild(rsop, GroupByOperator.class);
        if (cGBY != null) {
          if (CorrelationUtilities.hasGroupingSet(rsop) ||
              cGBY.getConf().isGroupingSetsPresent()) {
            // Do not support grouping set right now
            isCorrelated = false;
          }
        }
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      for (ExprNodeDesc key : partitionCols) {
        if (!(key instanceof ExprNodeColumnDesc)) {
          shouldDetect = false;
        }
      }
      GroupByOperator cGBY =
          CorrelationUtilities.getSingleChild(op, GroupByOperator.class);
      if (cGBY != null) {
        if (CorrelationUtilities.hasGroupingSet(op) ||
            cGBY.getConf().isGroupingSetsPresent()) {
          // Do not support grouping set right now
          shouldDetect = false;
        }
      }
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