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/*
* 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.gen;
import org.apache.hadoop.hive.ql.exec.vector.Decimal64ColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.VectorExpressionDescriptor;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.exec.vector.expressions.NullUtil;
import org.apache.hadoop.hive.ql.exec.vector.expressions.Decimal64Util;
import org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression;
import org.apache.hadoop.hive.serde2.io.HiveDecimalWritable;
import org.apache.hadoop.hive.ql.metadata.HiveException;
/**
* Generated from template Decimal64ColumnArithmeticDecimal64Column.txt, which covers
* decimal64 arithmetic expressions between columns.
*/
public class <ClassName> extends VectorExpression {
private static final long serialVersionUID = 1L;
public <ClassName>(int colNum1, int colNum2, int outputColumnNum) {
super(colNum1, colNum2, outputColumnNum);
}
public <ClassName>() {
super();
}
@Override
public void evaluate(VectorizedRowBatch batch) throws HiveException {
// return immediately if batch is empty
final int n = batch.size;
if (n == 0) {
return;
}
if (childExpressions != null) {
super.evaluateChildren(batch);
}
Decimal64ColumnVector inputColVector1 = (Decimal64ColumnVector) batch.cols[inputColumnNum[0]];
Decimal64ColumnVector inputColVector2 = (Decimal64ColumnVector) batch.cols[inputColumnNum[1]];
Decimal64ColumnVector outputColVector = (Decimal64ColumnVector) batch.cols[outputColumnNum];
int[] sel = batch.selected;
long[] vector1 = inputColVector1.vector;
long[] vector2 = inputColVector2.vector;
long[] outputVector = outputColVector.vector;
boolean[] outputIsNull = outputColVector.isNull;
final long outputDecimal64AbsMax =
HiveDecimalWritable.getDecimal64AbsMax(outputColVector.precision);
/*
* Propagate null values for a two-input operator and set isRepeating and noNulls appropriately.
*/
NullUtil.propagateNullsColCol(
inputColVector1, inputColVector2, outputColVector, sel, n, batch.selectedInUse);
/*
* Disregard nulls for processing. In other words,
* the arithmetic operation is performed even if one or
* more inputs are null. This is to improve speed by avoiding
* conditional checks in the inner loop.
*/
if (inputColVector1.isRepeating && inputColVector2.isRepeating) {
final long result = vector1[0] <OperatorSymbol> vector2[0];
outputVector[0] = result;
if (Math.abs(result) > outputDecimal64AbsMax) {
outputColVector.noNulls = false;
outputIsNull[0] = true;
}
} else if (inputColVector1.isRepeating) {
final long repeatedValue1 = vector1[0];
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
final long result = repeatedValue1 <OperatorSymbol> vector2[i];
outputVector[i] = result;
if (Math.abs(result) > outputDecimal64AbsMax) {
outputColVector.noNulls = false;
outputIsNull[i] = true;
}
}
} else {
for(int i = 0; i != n; i++) {
final long result = repeatedValue1 <OperatorSymbol> vector2[i];
outputVector[i] = result;
if (Math.abs(result) > outputDecimal64AbsMax) {
outputColVector.noNulls = false;
outputIsNull[i] = true;
}
}
}
} else if (inputColVector2.isRepeating) {
final long repeatedValue2 = vector2[0];
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
final long result = vector1[i] <OperatorSymbol> repeatedValue2;
outputVector[i] = result;
if (Math.abs(result) > outputDecimal64AbsMax) {
outputColVector.noNulls = false;
outputIsNull[i] = true;
}
}
} else {
for(int i = 0; i != n; i++) {
final long result = vector1[i] <OperatorSymbol> repeatedValue2;
outputVector[i] = result;
if (Math.abs(result) > outputDecimal64AbsMax) {
outputColVector.noNulls = false;
outputIsNull[i] = true;
}
}
}
} else {
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
final long result = vector1[i] <OperatorSymbol> vector2[i];
outputVector[i] = result;
if (Math.abs(result) > outputDecimal64AbsMax) {
outputColVector.noNulls = false;
outputIsNull[i] = true;
}
}
} else {
for(int i = 0; i != n; i++) {
final long result = vector1[i] <OperatorSymbol> vector2[i];
outputVector[i] = result;
if (Math.abs(result) > outputDecimal64AbsMax) {
outputColVector.noNulls = false;
outputIsNull[i] = true;
}
}
}
}
// Currently, we defer division, etc to regular HiveDecimal so we don't do any null
// default value setting here.
}
@Override
public String vectorExpressionParameters() {
return getColumnParamString(0, inputColumnNum[0]) + ", " + getColumnParamString(1, inputColumnNum[1]);
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
return (new VectorExpressionDescriptor.Builder())
.setMode(
VectorExpressionDescriptor.Mode.PROJECTION)
.setNumArguments(2)
.setArgumentTypes(
VectorExpressionDescriptor.ArgumentType.DECIMAL_64,
VectorExpressionDescriptor.ArgumentType.DECIMAL_64)
.setInputExpressionTypes(
VectorExpressionDescriptor.InputExpressionType.COLUMN,
VectorExpressionDescriptor.InputExpressionType.COLUMN).build();
}
@Override
public boolean shouldConvertDecimal64ToDecimal() {
return false;
}
}