/**
* 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;
import java.sql.Timestamp;
import org.apache.hadoop.hive.common.type.HiveIntervalDayTime;
import org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression;
import org.apache.hadoop.hive.ql.exec.vector.expressions.NullUtil;
import org.apache.hadoop.hive.ql.exec.vector.*;
import org.apache.hadoop.hive.ql.util.DateTimeMath;
import org.apache.hadoop.hive.serde2.io.DateWritable;
// A type date (LongColumnVector storing epoch days) minus a type date produces a
// type interval_day_time (IntervalDayTimeColumnVector storing nanosecond interval in 2 longs).
public class DateColSubtractDateColumn extends VectorExpression {
private static final long serialVersionUID = 1L;
private int colNum1;
private int colNum2;
private int outputColumn;
private Timestamp scratchTimestamp1;
private Timestamp scratchTimestamp2;
private DateTimeMath dtm = new DateTimeMath();
public DateColSubtractDateColumn(int colNum1, int colNum2, int outputColumn) {
this.colNum1 = colNum1;
this.colNum2 = colNum2;
this.outputColumn = outputColumn;
scratchTimestamp1 = new Timestamp(0);
scratchTimestamp2 = new Timestamp(0);
}
public DateColSubtractDateColumn() {
}
@Override
public void evaluate(VectorizedRowBatch batch) {
if (childExpressions != null) {
super.evaluateChildren(batch);
}
// Input #1 is type date (epochDays).
LongColumnVector inputColVector1 = (LongColumnVector) batch.cols[colNum1];
// Input #2 is type date (epochDays).
LongColumnVector inputColVector2 = (LongColumnVector) batch.cols[colNum2];
// Output is type interval_day_time.
IntervalDayTimeColumnVector outputColVector = (IntervalDayTimeColumnVector) batch.cols[outputColumn];
int[] sel = batch.selected;
int n = batch.size;
long[] vector1 = inputColVector1.vector;
long[] vector2 = inputColVector2.vector;
// return immediately if batch is empty
if (n == 0) {
return;
}
outputColVector.isRepeating =
inputColVector1.isRepeating && inputColVector2.isRepeating
|| inputColVector1.isRepeating && !inputColVector1.noNulls && inputColVector1.isNull[0]
|| inputColVector2.isRepeating && !inputColVector2.noNulls && inputColVector2.isNull[0];
// Handle nulls first
NullUtil.propagateNullsColCol(
inputColVector1, inputColVector2, outputColVector, sel, n, batch.selectedInUse);
HiveIntervalDayTime resultIntervalDayTime = outputColVector.getScratchIntervalDayTime();
/* 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) {
scratchTimestamp1.setTime(DateWritable.daysToMillis((int) vector1[0]));
scratchTimestamp2.setTime(DateWritable.daysToMillis((int) vector2[0]));
dtm.subtract(scratchTimestamp1, scratchTimestamp2, outputColVector.getScratchIntervalDayTime());
outputColVector.setFromScratchIntervalDayTime(0);
} else if (inputColVector1.isRepeating) {
scratchTimestamp1.setTime(DateWritable.daysToMillis((int) vector1[0]));
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
scratchTimestamp2.setTime(DateWritable.daysToMillis((int) vector2[i]));
dtm.subtract(scratchTimestamp1, scratchTimestamp2, outputColVector.getScratchIntervalDayTime());
outputColVector.setFromScratchIntervalDayTime(i);
}
} else {
for(int i = 0; i != n; i++) {
scratchTimestamp2.setTime(DateWritable.daysToMillis((int) vector2[i]));
dtm.subtract(scratchTimestamp1, scratchTimestamp2, outputColVector.getScratchIntervalDayTime());
outputColVector.setFromScratchIntervalDayTime(i);
}
}
} else if (inputColVector2.isRepeating) {
scratchTimestamp2.setTime(DateWritable.daysToMillis((int) vector2[0]));
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
scratchTimestamp1.setTime(DateWritable.daysToMillis((int) vector1[i]));
dtm.subtract(scratchTimestamp1, scratchTimestamp2, outputColVector.getScratchIntervalDayTime());
outputColVector.setFromScratchIntervalDayTime(i);
}
} else {
for(int i = 0; i != n; i++) {
scratchTimestamp1.setTime(DateWritable.daysToMillis((int) vector1[i]));
dtm.subtract(scratchTimestamp1, scratchTimestamp2, outputColVector.getScratchIntervalDayTime());
outputColVector.setFromScratchIntervalDayTime(i);
}
}
} else {
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
scratchTimestamp1.setTime(DateWritable.daysToMillis((int) vector1[i]));
scratchTimestamp2.setTime(DateWritable.daysToMillis((int) vector2[i]));
dtm.subtract(scratchTimestamp1, scratchTimestamp2, outputColVector.getScratchIntervalDayTime());
outputColVector.setFromScratchIntervalDayTime(i);
}
} else {
for(int i = 0; i != n; i++) {
scratchTimestamp1.setTime(DateWritable.daysToMillis((int) vector1[i]));
scratchTimestamp2.setTime(DateWritable.daysToMillis((int) vector2[i]));
dtm.subtract(scratchTimestamp1, scratchTimestamp2, outputColVector.getScratchIntervalDayTime());
outputColVector.setFromScratchIntervalDayTime(i);
}
}
}
/* For the case when the output can have null values, follow
* the convention that the data values must be 1 for long and
* NaN for double. This is to prevent possible later zero-divide errors
* in complex arithmetic expressions like col2 / (col1 - 1)
* in the case when some col1 entries are null.
*/
NullUtil.setNullDataEntriesIntervalDayTime(outputColVector, batch.selectedInUse, sel, n);
}
@Override
public int getOutputColumn() {
return outputColumn;
}
@Override
public String getOutputType() {
return "timestamp";
}
public String vectorExpressionParameters() {
return "col " + colNum1 + ", col " + colNum2;
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
return (new VectorExpressionDescriptor.Builder())
.setMode(
VectorExpressionDescriptor.Mode.PROJECTION)
.setNumArguments(2)
.setArgumentTypes(
VectorExpressionDescriptor.ArgumentType.getType("date"),
VectorExpressionDescriptor.ArgumentType.getType("date"))
.setInputExpressionTypes(
VectorExpressionDescriptor.InputExpressionType.COLUMN,
VectorExpressionDescriptor.InputExpressionType.COLUMN).build();
}
}