org.apache.hadoop.hive.ql.exec.vector.expressions.gen.TimestampScalarSubtractDateColumn Maven / Gradle / Ivy
The newest version!
/**
* 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.expressions.VectorExpression;
import org.apache.hadoop.hive.ql.exec.vector.VectorExpressionDescriptor;
import org.apache.hadoop.hive.ql.exec.vector.*;
/*
* Because of the templatized nature of the code, either or both
* of these ColumnVector imports may be needed. Listing both of them
* rather than using ....vectorization.*;
*/
import org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.LongColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.exec.vector.expressions.NullUtil;
/**
* Generated from template ScalarArithmeticColumnWithConvert.txt.
* Implements a vectorized arithmetic operator with a scalar on the left and a
* column vector on the right. The result is output to an output column vector.
*/
public class TimestampScalarSubtractDateColumn extends VectorExpression {
private static final long serialVersionUID = 1L;
private int colNum;
private long value;
private int outputColumn;
public TimestampScalarSubtractDateColumn(long value, int colNum, int outputColumn) {
this.colNum = colNum;
this.value = (value);
this.outputColumn = outputColumn;
}
public TimestampScalarSubtractDateColumn() {
}
@Override
/**
* Method to evaluate scalar-column operation in vectorized fashion.
*
* @batch a package of rows with each column stored in a vector
*/
public void evaluate(VectorizedRowBatch batch) {
if (childExpressions != null) {
super.evaluateChildren(batch);
}
LongColumnVector inputColVector = (LongColumnVector) batch.cols[colNum];
LongColumnVector outputColVector = (LongColumnVector) batch.cols[outputColumn];
int[] sel = batch.selected;
boolean[] inputIsNull = inputColVector.isNull;
boolean[] outputIsNull = outputColVector.isNull;
outputColVector.noNulls = inputColVector.noNulls;
outputColVector.isRepeating = inputColVector.isRepeating;
int n = batch.size;
long[] vector = inputColVector.vector;
long[] outputVector = outputColVector.vector;
// return immediately if batch is empty
if (n == 0) {
return;
}
if (inputColVector.isRepeating) {
outputVector[0] = value - TimestampUtils.daysToNanoseconds(vector[0]);
// Even if there are no nulls, we always copy over entry 0. Simplifies code.
outputIsNull[0] = inputIsNull[0];
} else if (inputColVector.noNulls) {
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
outputVector[i] = value - TimestampUtils.daysToNanoseconds(vector[i]);
}
} else {
for(int i = 0; i != n; i++) {
outputVector[i] = value - TimestampUtils.daysToNanoseconds(vector[i]);
}
}
} else { /* there are nulls */
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
outputVector[i] = value - TimestampUtils.daysToNanoseconds(vector[i]);
outputIsNull[i] = inputIsNull[i];
}
} else {
for(int i = 0; i != n; i++) {
outputVector[i] = value - TimestampUtils.daysToNanoseconds(vector[i]);
}
System.arraycopy(inputIsNull, 0, outputIsNull, 0, n);
}
}
NullUtil.setNullOutputEntriesColScalar(outputColVector, batch.selectedInUse, sel, n);
}
@Override
public int getOutputColumn() {
return outputColumn;
}
@Override
public String getOutputType() {
return "long";
}
public int getColNum() {
return colNum;
}
public void setColNum(int colNum) {
this.colNum = colNum;
}
public long getValue() {
return value;
}
public void setValue(long value) {
this.value = value;
}
public void setOutputColumn(int outputColumn) {
this.outputColumn = outputColumn;
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
return (new VectorExpressionDescriptor.Builder())
.setMode(
VectorExpressionDescriptor.Mode.PROJECTION)
.setNumArguments(2)
.setArgumentTypes(
VectorExpressionDescriptor.ArgumentType.getType("timestamp"),
VectorExpressionDescriptor.ArgumentType.getType("date"))
.setInputExpressionTypes(
VectorExpressionDescriptor.InputExpressionType.SCALAR,
VectorExpressionDescriptor.InputExpressionType.COLUMN).build();
}
}