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

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

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        -1 : Integer.MAX_VALUE), -1, false);

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

    int numReducers = -1;
    List<ASTNode> grpByExprs = getGroupByForClause(parseInfo, dest);
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    QBParseInfo parseInfo = qb.getParseInfo();

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

    groupOpToInputTables.put(groupByOperatorInfo, opParseCtx.get(
        inputOperatorInfo).getRowResolver().getTableNames());
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    QBParseInfo parseInfo = qb.getParseInfo();

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

    groupOpToInputTables.put(groupByOperatorInfo, opParseCtx.get(
        inputOperatorInfo).getRowResolver().getTableNames());
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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());

      ArrayList<aggregationDesc> aggrs = conf.getAggregators();
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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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    @Override
    public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx procCtx,
        Object... nodeOutputs) throws SemanticException {
      // GBY,RS,GBY... (top to bottom)
      GroupByOperator groupByOp = (GroupByOperator) stack.get(stack.size() - 3);

      GroupByOptimizerContext ctx = (GroupByOptimizerContext) procCtx;

      if (!checkGroupByOperatorProcessed(ctx, groupByOp)) {
        processGroupBy(ctx, stack, groupByOp, 2);
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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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  • org.apache.hadoop.hive.ql.optimizer.correlation.CorrelationOptimizer$CorrelationNodeProc
  • org.apache.hadoop.hive.ql.optimizer.correlation.CorrelationUtilities
  • org.apache.hadoop.hive.ql.optimizer.correlation.QueryPlanTreeTransformation
  • org.apache.hadoop.hive.ql.optimizer.correlation.ReduceSinkDeDuplication$AbsctractReducerReducerProc
  • org.apache.hadoop.hive.ql.optimizer.correlation.ReduceSinkDeDuplication$GroupbyReducerProc
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