Package org.apache.hadoop.hive.ql.udf.generic

Examples of org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator


      String aggName = value.getChild(0).getText();

      boolean isDistinct = value.getType() == HiveParser.TOK_FUNCTIONDI;
      Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);
      GenericUDAFEvaluator genericUDAFEvaluator = genericUDAFEvaluators.get(entry.getKey());
      assert(genericUDAFEvaluator != null);
      GenericUDAFInfo udaf = getGenericUDAFInfo(genericUDAFEvaluator, amode, aggParameters);
      aggregations.add(new aggregationDesc(aggName.toLowerCase(), udaf.genericUDAFEvaluator, udaf.convertedParameters,
                                           (mode != groupByDesc.Mode.FINAL && value.getToken().getType() == HiveParser.TOK_FUNCTIONDI),
                                           amode));
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      ArrayList<ExprNodeDesc> aggParameters, ASTNode aggTree,
      boolean isDistinct, boolean isAllColumns)
      throws SemanticException {
    ArrayList<ObjectInspector> originalParameterTypeInfos =
        getWritableObjectInspector(aggParameters);
    GenericUDAFEvaluator result = FunctionRegistry.getGenericUDAFEvaluator(
        aggName, originalParameterTypeInfos, isDistinct, isAllColumns);
    if (null == result) {
      String reason = "Looking for UDAF Evaluator\"" + aggName
          + "\" with parameters " + originalParameterTypeInfos;
      throw new SemanticException(ErrorMsg.INVALID_FUNCTION_SIGNATURE.getMsg(
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      if (isDistinct) {
        numDistinctUDFs++;
      }
      Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);
      GenericUDAFEvaluator genericUDAFEvaluator = getGenericUDAFEvaluator(
          aggName, aggParameters, value, isDistinct, isAllColumns);
      assert (genericUDAFEvaluator != null);
      GenericUDAFInfo udaf = getGenericUDAFInfo(genericUDAFEvaluator, amode,
          aggParameters);
      aggregations.add(new AggregationDesc(aggName.toLowerCase(),
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      if (isDistinct) {
        numDistinctUDFs++;
      }
      boolean isAllColumns = value.getType() == HiveParser.TOK_FUNCTIONSTAR;
      Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);
      GenericUDAFEvaluator genericUDAFEvaluator = null;
      // For distincts, partial aggregations have not been done
      if (distPartAgg) {
        genericUDAFEvaluator = getGenericUDAFEvaluator(aggName, aggParameters,
            value, isDistinct, isAllColumns);
        assert (genericUDAFEvaluator != null);
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      boolean isDistinct = value.getType() == HiveParser.TOK_FUNCTIONDI;
      containsDistinctAggr = containsDistinctAggr || isDistinct;
      boolean isAllColumns = value.getType() == HiveParser.TOK_FUNCTIONSTAR;
      Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);

      GenericUDAFEvaluator genericUDAFEvaluator = getGenericUDAFEvaluator(
          aggName, aggParameters, value, isDistinct, isAllColumns);
      assert (genericUDAFEvaluator != null);
      GenericUDAFInfo udaf = getGenericUDAFInfo(genericUDAFEvaluator, amode,
          aggParameters);
      aggregations.add(new AggregationDesc(aggName.toLowerCase(),
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      boolean isDistinct = value.getType() == HiveParser.TOK_FUNCTIONDI;
      containsDistinctAggr = containsDistinctAggr || isDistinct;
      boolean isStar = value.getType() == HiveParser.TOK_FUNCTIONSTAR;
      Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);
      GenericUDAFEvaluator genericUDAFEvaluator = genericUDAFEvaluators
          .get(entry.getKey());
      assert (genericUDAFEvaluator != null);
      GenericUDAFInfo udaf = getGenericUDAFInfo(genericUDAFEvaluator, amode,
          aggParameters);
      aggregations
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      }
      funcArgOIs = new ObjectInspector[args.size()];
      funcArgOIs = argOIs.toArray(funcArgOIs);
    }

    GenericUDAFEvaluator wFnEval = FunctionRegistry.getGenericWindowingEvaluator(def.getName(),
        argOIs,
        def.isDistinct(), def.isStar());
    ObjectInspector OI = wFnEval.init(GenericUDAFEvaluator.Mode.COMPLETE, funcArgOIs);
    def.setWFnEval(wFnEval);
    def.setOI(OI);
  }
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      ArrayList<ExprNodeDesc> aggParameters, ASTNode aggTree,
      boolean isDistinct, boolean isAllColumns)
      throws SemanticException {
    ArrayList<ObjectInspector> originalParameterTypeInfos =
        getWritableObjectInspector(aggParameters);
    GenericUDAFEvaluator result = FunctionRegistry.getGenericUDAFEvaluator(
        aggName, originalParameterTypeInfos, isDistinct, isAllColumns);
    if (null == result) {
      String reason = "Looking for UDAF Evaluator\"" + aggName
          + "\" with parameters " + originalParameterTypeInfos;
      throw new SemanticException(ErrorMsg.INVALID_FUNCTION_SIGNATURE.getMsg(
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      if (isDistinct) {
        numDistinctUDFs++;
      }
      Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);
      GenericUDAFEvaluator genericUDAFEvaluator = getGenericUDAFEvaluator(
          aggName, aggParameters, value, isDistinct, isAllColumns);
      assert (genericUDAFEvaluator != null);
      GenericUDAFInfo udaf = getGenericUDAFInfo(genericUDAFEvaluator, amode,
          aggParameters);
      aggregations.add(new AggregationDesc(aggName.toLowerCase(),
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      if (isDistinct) {
        numDistinctUDFs++;
      }
      boolean isAllColumns = value.getType() == HiveParser.TOK_FUNCTIONSTAR;
      Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);
      GenericUDAFEvaluator genericUDAFEvaluator = null;
      // For distincts, partial aggregations have not been done
      if (distPartAgg) {
        genericUDAFEvaluator = getGenericUDAFEvaluator(aggName, aggParameters,
            value, isDistinct, isAllColumns);
        assert (genericUDAFEvaluator != null);
View Full Code Here

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