org.apache.hadoop.hive.ql.exec.vector.expressions.gen.DateScalarSubtractIntervalYearMonthColumn Maven / Gradle / Ivy
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* Licensed to the Apache Software Foundation (ASF) under one
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* 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,
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* 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 java.sql.Date;
import java.util.Arrays;
import org.apache.hadoop.hive.common.type.HiveIntervalYearMonth;
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;
import org.apache.hadoop.hive.ql.util.DateTimeMath;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.serde2.io.DateWritableV2;
/**
* Generated from template DateTimeScalarArithmeticIntervalYearMonthColumn.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 DateScalarSubtractIntervalYearMonthColumn extends VectorExpression {
private static final long serialVersionUID = 1L;
private final int colNum;
private final Date value;
private transient final HiveIntervalYearMonth scratchIntervalYearMonth2 = new HiveIntervalYearMonth();
private transient final Date outputDate = new Date(0);
private transient final DateTimeMath dtm = new DateTimeMath();
public DateScalarSubtractIntervalYearMonthColumn(long value, int colNum, int outputColumnNum) {
super(outputColumnNum);
this.value = new Date(DateWritableV2.daysToMillis((int) value));
this.colNum = colNum;
}
public DateScalarSubtractIntervalYearMonthColumn() {
super();
// Dummy final assignments.
value = null;
colNum = -1;
}
@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) throws HiveException {
// return immediately if batch is empty
final int n = batch.size;
if (n == 0) {
return;
}
if (childExpressions != null) {
super.evaluateChildren(batch);
}
// Input #2 is type Interval_Year_Month (months).
LongColumnVector inputColVector2 = (LongColumnVector) batch.cols[colNum];
// Output is type Date.
LongColumnVector outputColVector = (LongColumnVector) batch.cols[outputColumnNum];
int[] sel = batch.selected;
boolean[] inputIsNull = inputColVector2.isNull;
boolean[] outputIsNull = outputColVector.isNull;
// We do not need to do a column reset since we are carefully changing the output.
outputColVector.isRepeating = false;
long[] vector2 = inputColVector2.vector;
long[] outputVector = outputColVector.vector;
if (inputColVector2.isRepeating) {
if (inputColVector2.noNulls || !inputIsNull[0]) {
outputIsNull[0] = false;
scratchIntervalYearMonth2.set((int) vector2[0]);
dtm.subtract(
value, scratchIntervalYearMonth2, outputDate);
outputVector[0] = DateWritableV2.dateToDays(outputDate);
} else {
outputIsNull[0] = true;
outputColVector.noNulls = false;
}
outputColVector.isRepeating = true;
return;
}
if (inputColVector2.noNulls) {
if (batch.selectedInUse) {
// CONSIDER: For large n, fill n or all of isNull array and use the tighter ELSE loop.
if (!outputColVector.noNulls) {
for(int j = 0; j != n; j++) {
final int i = sel[j];
outputIsNull[i] = false;
scratchIntervalYearMonth2.set((int) vector2[i]);
dtm.subtract(
value, scratchIntervalYearMonth2, outputDate);
outputVector[i] = DateWritableV2.dateToDays(outputDate);
}
} else {
for(int j = 0; j != n; j++) {
final int i = sel[j];
scratchIntervalYearMonth2.set((int) vector2[i]);
dtm.subtract(
value, scratchIntervalYearMonth2, outputDate);
outputVector[i] = DateWritableV2.dateToDays(outputDate);
}
}
} else {
if (!outputColVector.noNulls) {
// Assume it is almost always a performance win to fill all of isNull so we can
// safely reset noNulls.
Arrays.fill(outputIsNull, false);
outputColVector.noNulls = true;
}
for(int i = 0; i != n; i++) {
scratchIntervalYearMonth2.set((int) vector2[i]);
dtm.subtract(
value, scratchIntervalYearMonth2, outputDate);
outputVector[i] = DateWritableV2.dateToDays(outputDate);
}
}
} else /* there are NULLs in the inputColVector */ {
/*
* Do careful maintenance of the outputColVector.noNulls flag.
*/
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!inputIsNull[i]) {
outputIsNull[i] = false;
scratchIntervalYearMonth2.set((int) vector2[i]);
dtm.subtract(
value, scratchIntervalYearMonth2, outputDate);
outputVector[i] = DateWritableV2.dateToDays(outputDate);
} else {
outputIsNull[i] = true;
outputColVector.noNulls = false;
}
}
} else {
for(int i = 0; i != n; i++) {
if (!inputIsNull[i]) {
outputIsNull[i] = false;
scratchIntervalYearMonth2.set((int) vector2[i]);
dtm.subtract(
value, scratchIntervalYearMonth2, outputDate);
outputVector[i] = DateWritableV2.dateToDays(outputDate);
} else {
outputIsNull[i] = true;
outputColVector.noNulls = false;
}
}
}
}
NullUtil.setNullOutputEntriesColScalar(outputColVector, batch.selectedInUse, sel, n);
}
@Override
public String vectorExpressionParameters() {
return "val " + value + ", " + getColumnParamString(1, colNum);
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
return (new VectorExpressionDescriptor.Builder())
.setMode(
VectorExpressionDescriptor.Mode.PROJECTION)
.setNumArguments(2)
.setArgumentTypes(
VectorExpressionDescriptor.ArgumentType.getType("date"),
VectorExpressionDescriptor.ArgumentType.getType("interval_year_month"))
.setInputExpressionTypes(
VectorExpressionDescriptor.InputExpressionType.SCALAR,
VectorExpressionDescriptor.InputExpressionType.COLUMN).build();
}
}