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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 java.util.Arrays;
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.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.exec.vector.VectorExpressionDescriptor;
import org.apache.hadoop.hive.ql.exec.vector.*;
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 DateColumnArithmeticTimestampScalarBase.txt, a base class
* which covers binary arithmetic expressions between a date column and a timestamp scalar.
*/
public class <ClassName> extends VectorExpression {
private static final long serialVersionUID = 1L;
private final <HiveOperandType2> value;
private transient final Timestamp scratchTimestamp1 = new Timestamp(0);
private transient final DateTimeMath dtm = new DateTimeMath();
public <ClassName>(int colNum, <HiveOperandType2> value, int outputColumnNum) {
super(colNum, outputColumnNum);
this.value = value;
}
public <ClassName>() {
super();
// Dummy final assignments.
value = null;
}
@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);
}
// Input #1 is type date (days). For the math we convert it to a timestamp.
LongColumnVector inputColVector1 = (LongColumnVector) batch.cols[inputColumnNum[0]];
// Output is type <ReturnType>.
<OutputColumnVectorType> outputColVector = (<OutputColumnVectorType>) batch.cols[outputColumnNum];
int[] sel = batch.selected;
boolean[] inputIsNull = inputColVector1.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[] vector1 = inputColVector1.vector;
if (inputColVector1.isRepeating) {
if (inputColVector1.noNulls || !inputIsNull[0]) {
outputIsNull[0] = false;
scratchTimestamp1.setTime(DateWritableV2.daysToMillis((int) vector1[0]));
dtm.<OperatorMethod>(
scratchTimestamp1, value, outputColVector.getScratch<CamelReturnType>());
outputColVector.setFromScratch<CamelReturnType>(0);
} else {
outputIsNull[0] = true;
outputColVector.noNulls = false;
}
outputColVector.isRepeating = true;
return;
}
if (inputColVector1.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;
scratchTimestamp1.setTime(DateWritableV2.daysToMillis((int) vector1[i]));
dtm.<OperatorMethod>(
scratchTimestamp1, value, outputColVector.getScratch<CamelReturnType>());
outputColVector.setFromScratch<CamelReturnType>(i);
}
} else {
for(int j = 0; j != n; j++) {
final int i = sel[j];
scratchTimestamp1.setTime(DateWritableV2.daysToMillis((int) vector1[i]));
dtm.<OperatorMethod>(
scratchTimestamp1, value, outputColVector.getScratch<CamelReturnType>());
outputColVector.setFromScratch<CamelReturnType>(i);
}
}
} 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++) {
scratchTimestamp1.setTime(DateWritableV2.daysToMillis((int) vector1[i]));
dtm.<OperatorMethod>(
scratchTimestamp1, value, outputColVector.getScratch<CamelReturnType>());
outputColVector.setFromScratch<CamelReturnType>(i);
}
}
} 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;
scratchTimestamp1.setTime(DateWritableV2.daysToMillis((int) vector1[i]));
dtm.<OperatorMethod>(
scratchTimestamp1, value, outputColVector.getScratch<CamelReturnType>());
outputColVector.setFromScratch<CamelReturnType>(i);
} else {
outputIsNull[i] = true;
outputColVector.noNulls = false;
}
}
} else {
for(int i = 0; i != n; i++) {
if (!inputIsNull[i]) {
outputIsNull[i] = false;
scratchTimestamp1.setTime(DateWritableV2.daysToMillis((int) vector1[i]));
dtm.<OperatorMethod>(
scratchTimestamp1, value, outputColVector.getScratch<CamelReturnType>());
outputColVector.setFromScratch<CamelReturnType>(i);
} else {
outputIsNull[i] = true;
outputColVector.noNulls = false;
}
}
}
}
NullUtil.setNullOutputEntriesColScalar(outputColVector, batch.selectedInUse, sel, n);
}
@Override
public String vectorExpressionParameters() {
return getColumnParamString(0, inputColumnNum[0]) + ", val " + TimestampUtils.timestampScalarTypeToString(value);
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
return (new VectorExpressionDescriptor.Builder())
.setMode(
VectorExpressionDescriptor.Mode.PROJECTION)
.setNumArguments(2)
.setArgumentTypes(
VectorExpressionDescriptor.ArgumentType.getType("date"),
VectorExpressionDescriptor.ArgumentType.getType("<OperandType2>"))
.setInputExpressionTypes(
VectorExpressionDescriptor.InputExpressionType.COLUMN,
VectorExpressionDescriptor.InputExpressionType.SCALAR).build();
}
}