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

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


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

      boolean isDistinct = value.getType() == HiveParser.TOK_FUNCTIONDI;
      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
View Full Code Here


    GenericUDAFResolver udafResolver = getGenericUDAFResolver(name);
    if (udafResolver == null) {
      return null;
    }

    GenericUDAFEvaluator udafEvaluator = null;
    ObjectInspector args[] = new ObjectInspector[argumentOIs.size()];
    // Can't use toArray here because Java is dumb when it comes to
    // generics + arrays.
    for (int ii = 0; ii < argumentOIs.size(); ++ii) {
      args[ii] = argumentOIs.get(ii);
View Full Code Here

   */
  public boolean isDistinctLike() {
    ArrayList<AggregationDesc> aggregators = getAggregators();
    for(AggregationDesc ad: aggregators){
      if(!ad.getDistinct()) {
        GenericUDAFEvaluator udafEval = ad.getGenericUDAFEvaluator();
        UDFType annot = udafEval.getClass().getAnnotation(UDFType.class);
        if(annot == null || !annot.distinctLike()) {
          return false;
        }
      }
    }
View Full Code Here

    try
    {
      WindowFunctionSpec wSpec = wFnDef.getSpec();
      ArrayList<ArgDef> args = wFnDef.getArgs();
      ArrayList<ObjectInspector> argOIs = getWritableObjectInspector(args);
      GenericUDAFEvaluator wFnEval = org.apache.hadoop.hive.ql.exec.FunctionRegistry.getGenericUDAFEvaluator(wSpec.getName(), argOIs, wSpec.isDistinct(), wSpec.isStar());
      ObjectInspector[] funcArgOIs = null;
     
      if ( args != null)
      {
        funcArgOIs = new ObjectInspector[args.size()];
        int i = 0;
        for(ArgDef arg : args)
        {
          funcArgOIs[i++] =arg.getOI();
        }
      }
     
      ObjectInspector OI = wFnEval.init(GenericUDAFEvaluator.Mode.COMPLETE, funcArgOIs);
     
      wFnDef.setEvaluator(wFnEval);
      wFnDef.setOI(OI);
    }
    catch(HiveException he)
View Full Code Here

      {
        boolean processWindow = wFn.getWindow() != null;
        pItr.reset();
        if ( !processWindow )
        {
          GenericUDAFEvaluator fEval = wFn.getEvaluator();
          Object[] args = new Object[wFn.getArgs().size()];
          AggregationBuffer aggBuffer = fEval.getNewAggregationBuffer();
          while(pItr.hasNext())
          {
            Object row = pItr.next();
            int i =0;
            for(ArgDef arg : wFn.getArgs())
            {
              args[i++] = arg.getExprEvaluator().evaluate(row);
            }
            fEval.aggregate(aggBuffer, args);
          }
          Object out = fEval.evaluate(aggBuffer);
          WindowFunctionInfo wFnInfo = FunctionRegistry.getWindowFunctionInfo(wFn.getSpec().getName());
          if ( !wFnInfo.isPivotResult())
          {
            out = new SameList(iPart.size(), out);
          }
View Full Code Here

  static ArrayList<Object> executeFnwithWindow(QueryDef qDef, WindowFunctionDef wFnDef, Partition iPart)
    throws HiveException, WindowingException
  {
    ArrayList<Object> vals = new ArrayList<Object>();
   
    GenericUDAFEvaluator fEval = wFnDef.getEvaluator();
    Object[] args = new Object[wFnDef.getArgs().size()];
    for(int i=0; i < iPart.size(); i++)
    {
      AggregationBuffer aggBuffer = fEval.getNewAggregationBuffer();
      Range rng = getRange(wFnDef, i, iPart);
      PartitionIterator<Object> rItr = rng.iterator();
      RuntimeUtils.connectLeadLagFunctionsToPartition(qDef, rItr);
      while(rItr.hasNext())
      {
        Object row = rItr.next();
        int j = 0;
        for(ArgDef arg : wFnDef.getArgs())
        {
          args[j++] = arg.getExprEvaluator().evaluate(row);
        }
        fEval.aggregate(aggBuffer, args);
      }
      Object out = fEval.evaluate(aggBuffer);
      out = ObjectInspectorUtils.copyToStandardObject(out, wFnDef.getOI(), ObjectInspectorCopyOption.WRITABLE);
      vals.add(out);
    }
    return vals;
  }
View Full Code Here

      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(),
View Full Code Here

      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

      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(),
View Full Code Here

      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
View Full Code Here

TOP

Related Classes of org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator$AbstractAggregationBuffer

Copyright © 2018 www.massapicom. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.