/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.hadoop.hive.ql.exec.vector.expressions.aggregates.gen;

import java.util.ArrayList;
import java.util.List;

import org.apache.hadoop.hive.common.type.HiveDecimal;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.vector.expressions.DecimalUtil;
import org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression;
import org.apache.hadoop.hive.ql.exec.vector.expressions.aggregates.VectorAggregateExpression;
import org.apache.hadoop.hive.ql.exec.vector.VectorAggregationBufferRow;
import org.apache.hadoop.hive.ql.exec.vector.VectorAggregationDesc;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.exec.vector.ColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.DecimalColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.LongColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.StructColumnVector;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.plan.AggregationDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeDesc;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.Mode;
import org.apache.hadoop.hive.ql.util.JavaDataModel;
import org.apache.hadoop.hive.serde2.typeinfo.StructTypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.DecimalTypeInfo;
import org.apache.hadoop.hive.serde2.io.HiveDecimalWritable;

import com.google.common.base.Preconditions;

/**
 * Generated from template VectorUDAFAvg.txt.
 */
@Description(name = "avg",
    value = "_FUNC_(AVG) - Returns the average value of expr (vectorized, type: decimal)")
public class <ClassName> extends VectorAggregateExpression {

    private static final long serialVersionUID = 1L;

    /** class for storing the current aggregate value. */
    static class Aggregation implements AggregationBuffer {

      private static final long serialVersionUID = 1L;

      transient private final HiveDecimalWritable sum = new HiveDecimalWritable();
      transient private long count;

      public void avgValue(HiveDecimalWritable writable) {

        // Note that if sum is out of range, mutateAdd will ignore the call.
        // At the end, sum.isSet() can be checked for null.
        sum.mutateAdd(writable);
        count++;
      }

      @Override
      public int getVariableSize() {
        throw new UnsupportedOperationException();
      }

      @Override
      public void reset() {
        sum.setFromLong(0L);
        count = 0;
      }
    }

#IF COMPLETE
    transient private HiveDecimalWritable tempDecWritable;
#ENDIF COMPLETE

    DecimalTypeInfo outputDecimalTypeInfo;

    /**
     * The scale of the SUM in the partial output
     */
    private int sumScale;

    /**
     * The precision of the SUM in the partial output
     */
    private int sumPrecision;

  // This constructor is used to momentarily create the object so match can be called.
  public <ClassName>() {
    super();
  }

  public <ClassName>(VectorAggregationDesc vecAggrDesc) {
    super(vecAggrDesc);
#IF PARTIAL1
      Preconditions.checkState(this.mode == GenericUDAFEvaluator.Mode.PARTIAL1);
#ENDIF PARTIAL1
#IF COMPLETE
      Preconditions.checkState(this.mode == GenericUDAFEvaluator.Mode.COMPLETE);
#ENDIF COMPLETE
    init();
  }

    private void init() {
#IF PARTIAL1
      StructTypeInfo structTypeInfo = (StructTypeInfo) outputTypeInfo;
      outputDecimalTypeInfo = (DecimalTypeInfo) structTypeInfo.getAllStructFieldTypeInfos().get(AVERAGE_SUM_FIELD_INDEX);
#ENDIF PARTIAL1
#IF COMPLETE
      outputDecimalTypeInfo = (DecimalTypeInfo) outputTypeInfo;
#ENDIF COMPLETE
      sumScale = outputDecimalTypeInfo.scale();
      sumPrecision = outputDecimalTypeInfo.precision();
#IF COMPLETE
      tempDecWritable = new HiveDecimalWritable();
#ENDIF COMPLETE
    }

    private Aggregation getCurrentAggregationBuffer(
        VectorAggregationBufferRow[] aggregationBufferSets,
        int bufferIndex,
        int row) {
      VectorAggregationBufferRow mySet = aggregationBufferSets[row];
      Aggregation myagg = (Aggregation) mySet.getAggregationBuffer(bufferIndex);
      return myagg;
    }

    @Override
    public void aggregateInputSelection(
      VectorAggregationBufferRow[] aggregationBufferSets,
      int bufferIndex,
      VectorizedRowBatch batch) throws HiveException {

      int batchSize = batch.size;

      if (batchSize == 0) {
        return;
      }

      inputExpression.evaluate(batch);

       DecimalColumnVector inputVector =
           (DecimalColumnVector) batch.cols[
               this.inputExpression.getOutputColumnNum()];

      HiveDecimalWritable[] vector = inputVector.vector;

      if (inputVector.noNulls) {
        if (inputVector.isRepeating) {
          iterateNoNullsRepeatingWithAggregationSelection(
            aggregationBufferSets, bufferIndex,
            vector[0], batchSize);
        } else {
          if (batch.selectedInUse) {
            iterateNoNullsSelectionWithAggregationSelection(
              aggregationBufferSets, bufferIndex,
              vector, batch.selected, batchSize);
          } else {
            iterateNoNullsWithAggregationSelection(
              aggregationBufferSets, bufferIndex,
              vector, batchSize);
          }
        }
      } else {
        if (inputVector.isRepeating) {
          iterateHasNullsRepeatingWithAggregationSelection(
            aggregationBufferSets, bufferIndex,
            vector[0], batchSize, inputVector.isNull);
        } else {
          if (batch.selectedInUse) {
            iterateHasNullsSelectionWithAggregationSelection(
              aggregationBufferSets, bufferIndex,
              vector, batchSize, batch.selected, inputVector.isNull);
          } else {
            iterateHasNullsWithAggregationSelection(
              aggregationBufferSets, bufferIndex,
              vector, batchSize, inputVector.isNull);
          }
        }
      }
    }

    private void iterateNoNullsRepeatingWithAggregationSelection(
      VectorAggregationBufferRow[] aggregationBufferSets,
      int bufferIndex,
      HiveDecimalWritable value,
      int batchSize) {

      for (int i=0; i < batchSize; ++i) {
        Aggregation myagg = getCurrentAggregationBuffer(
          aggregationBufferSets,
          bufferIndex,
          i);
        myagg.avgValue(value);
      }
    }

    private void iterateNoNullsSelectionWithAggregationSelection(
      VectorAggregationBufferRow[] aggregationBufferSets,
      int bufferIndex,
      HiveDecimalWritable[] values,
      int[] selection,
      int batchSize) {

      for (int i=0; i < batchSize; ++i) {
        Aggregation myagg = getCurrentAggregationBuffer(
          aggregationBufferSets,
          bufferIndex,
          i);
        myagg.avgValue(values[selection[i]]);
      }
    }

    private void iterateNoNullsWithAggregationSelection(
      VectorAggregationBufferRow[] aggregationBufferSets,
      int bufferIndex,
      HiveDecimalWritable[] values,
      int batchSize) {
      for (int i=0; i < batchSize; ++i) {
        Aggregation myagg = getCurrentAggregationBuffer(
          aggregationBufferSets,
          bufferIndex,
          i);
        myagg.avgValue(values[i]);
      }
    }

    private void iterateHasNullsRepeatingWithAggregationSelection(
      VectorAggregationBufferRow[] aggregationBufferSets,
      int bufferIndex,
      HiveDecimalWritable value,
      int batchSize,
      boolean[] isNull) {

      if (isNull[0]) {
        return;
      }

      for (int i=0; i < batchSize; ++i) {
        Aggregation myagg = getCurrentAggregationBuffer(
          aggregationBufferSets,
          bufferIndex,
          i);
        myagg.avgValue(value);
      }
    }

    private void iterateHasNullsSelectionWithAggregationSelection(
      VectorAggregationBufferRow[] aggregationBufferSets,
      int bufferIndex,
      HiveDecimalWritable[] values,
      int batchSize,
      int[] selection,
      boolean[] isNull) {

      for (int j=0; j < batchSize; ++j) {
        int i = selection[j];
        if (!isNull[i]) {
          Aggregation myagg = getCurrentAggregationBuffer(
            aggregationBufferSets,
            bufferIndex,
            j);
          myagg.avgValue(values[i]);
        }
      }
   }

    private void iterateHasNullsWithAggregationSelection(
      VectorAggregationBufferRow[] aggregationBufferSets,
      int bufferIndex,
      HiveDecimalWritable[] values,
      int batchSize,
      boolean[] isNull) {

      for (int i=0; i < batchSize; ++i) {
        if (!isNull[i]) {
          Aggregation myagg = getCurrentAggregationBuffer(
            aggregationBufferSets,
            bufferIndex,
            i);
          myagg.avgValue(values[i]);
        }
      }
   }


    @Override
    public void aggregateInput(AggregationBuffer agg, VectorizedRowBatch batch)
        throws HiveException {

        inputExpression.evaluate(batch);

        DecimalColumnVector inputVector =
            (DecimalColumnVector) batch.cols[
                this.inputExpression.getOutputColumnNum()];

        int batchSize = batch.size;

        if (batchSize == 0) {
          return;
        }

        Aggregation myagg = (Aggregation)agg;

        HiveDecimalWritable[] vector = inputVector.vector;

        if (inputVector.isRepeating) {
          if (inputVector.noNulls || !inputVector.isNull[0]) {
            HiveDecimal value = vector[0].getHiveDecimal();
            HiveDecimal multiple = value.multiply(HiveDecimal.create(batchSize));
            myagg.sum.mutateAdd(multiple);
            myagg.count += batchSize;
          }
          return;
        }

        if (!batch.selectedInUse && inputVector.noNulls) {
          iterateNoSelectionNoNulls(myagg, vector, batchSize);
        }
        else if (!batch.selectedInUse) {
          iterateNoSelectionHasNulls(myagg, vector, batchSize, inputVector.isNull);
        }
        else if (inputVector.noNulls){
          iterateSelectionNoNulls(myagg, vector, batchSize, batch.selected);
        }
        else {
          iterateSelectionHasNulls(myagg, vector, batchSize, inputVector.isNull, batch.selected);
        }
    }

    private void iterateSelectionHasNulls(
        Aggregation myagg,
        HiveDecimalWritable[] vector,
        int batchSize,
        boolean[] isNull,
        int[] selected) {

      for (int j=0; j< batchSize; ++j) {
        int i = selected[j];
        if (!isNull[i]) {
          myagg.avgValue(vector[i]);
        }
      }
    }

    private void iterateSelectionNoNulls(
        Aggregation myagg,
        HiveDecimalWritable[] vector,
        int batchSize,
        int[] selected) {

      for (int i=0; i< batchSize; ++i) {
        myagg.avgValue(vector[selected[i]]);
      }
    }

    private void iterateNoSelectionHasNulls(
        Aggregation myagg,
        HiveDecimalWritable[] vector,
        int batchSize,
        boolean[] isNull) {

      for(int i=0;i<batchSize;++i) {
        if (!isNull[i]) {
          myagg.avgValue(vector[i]);
        }
      }
    }

    private void iterateNoSelectionNoNulls(
        Aggregation myagg,
        HiveDecimalWritable[] vector,
        int batchSize) {

      for (int i=0;i<batchSize;++i) {
        myagg.avgValue(vector[i]);
      }
    }

    @Override
    public AggregationBuffer getNewAggregationBuffer() throws HiveException {
      return new Aggregation();
    }

    @Override
    public void reset(AggregationBuffer agg) throws HiveException {
      Aggregation myAgg = (Aggregation) agg;
      myAgg.reset();
    }

  @Override
  public long getAggregationBufferFixedSize() {
    JavaDataModel model = JavaDataModel.get();
    return JavaDataModel.alignUp(
      model.object() +
      model.primitive2() * 2,
      model.memoryAlign());
  }

  @Override
  public boolean matches(String name, ColumnVector.Type inputColVectorType,
      ColumnVector.Type outputColVectorType, Mode mode) {

    /*
     * Average input is DECIMAL.
#IF PARTIAL1
     * Output is STRUCT.
     *
     * Mode PARTIAL1.
#ENDIF PARTIAL1
#IF COMPLETE
     * Output is DECIMAL.
     *
     * Mode COMPLETE.
#ENDIF COMPLETE
     */
    return
        name.equals("avg") &&
        inputColVectorType == ColumnVector.Type.DECIMAL &&
#IF PARTIAL1
        outputColVectorType == ColumnVector.Type.STRUCT &&
        mode == Mode.PARTIAL1;
#ENDIF PARTIAL1
#IF COMPLETE
        outputColVectorType == ColumnVector.Type.DECIMAL &&
        mode == Mode.COMPLETE;
#ENDIF COMPLETE
  }

  @Override
  public void assignRowColumn(VectorizedRowBatch batch, int batchIndex, int columnNum,
      AggregationBuffer agg) throws HiveException {

#IF PARTIAL1
    StructColumnVector outputColVector = (StructColumnVector) batch.cols[columnNum];
#ENDIF PARTIAL1
#IF COMPLETE
    DecimalColumnVector outputColVector = (DecimalColumnVector) batch.cols[columnNum];
#ENDIF COMPLETE

    Aggregation myagg = (Aggregation) agg;

    // For AVG, we only mark NULL on actual overflow.
    if (!myagg.sum.isSet()) {
      outputColVector.noNulls = false;
      outputColVector.isNull[batchIndex] = true;
      return;
    }

    outputColVector.isNull[batchIndex] = false;

#IF PARTIAL1
    ColumnVector[] fields = outputColVector.fields;
    fields[AVERAGE_COUNT_FIELD_INDEX].isNull[batchIndex] = false;
    ((LongColumnVector) fields[AVERAGE_COUNT_FIELD_INDEX]).vector[batchIndex] = myagg.count;
    fields[AVERAGE_SUM_FIELD_INDEX].isNull[batchIndex] = false;
    ((DecimalColumnVector) fields[AVERAGE_SUM_FIELD_INDEX]).set(batchIndex, myagg.sum);

    // NULL out useless source field.
    ColumnVector sourceColVector = (ColumnVector) fields[AVERAGE_SOURCE_FIELD_INDEX];
    sourceColVector.isRepeating = true;
    sourceColVector.noNulls = false;
    sourceColVector.isNull[0] = true;

#ENDIF PARTIAL1
#IF COMPLETE
    // For AVG, we mark NULL on count 0 or on overflow.
    if (myagg.count == 0 || !myagg.sum.isSet()) {
      outputColVector.noNulls = false;
      outputColVector.isNull[batchIndex] = true;
      return;
    }
    tempDecWritable.setFromLong (myagg.count);
    HiveDecimalWritable result = outputColVector.vector[batchIndex];
    result.set(myagg.sum);
    result.mutateDivide(tempDecWritable);
    result.mutateEnforcePrecisionScale(sumPrecision, sumScale);
    if (!result.isSet()) {
      outputColVector.noNulls = false;
      outputColVector.isNull[batchIndex] = true;
    }
#ENDIF COMPLETE
  }
}

