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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.LongColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.TimestampColumnVector;
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.VectorizedRowBatch;
import java.sql.Timestamp;
import org.apache.hadoop.hive.ql.metadata.HiveException;
/**
* Compute IF(expr1, expr2, expr3) for 3 input column expressions.
* The first is always a boolean (LongColumnVector).
* The second is a column or non-constant expression result.
* The third is a constant value.
*/
public class IfExprTimestampColumnScalar extends VectorExpression {
private static final long serialVersionUID = 1L;
private final int arg1Column;
private final int arg2Column;
private final Timestamp arg3Scalar;
public IfExprTimestampColumnScalar(int arg1Column, int arg2Column, Timestamp arg3Scalar,
int outputColumnNum) {
super(outputColumnNum);
this.arg1Column = arg1Column;
this.arg2Column = arg2Column;
this.arg3Scalar = arg3Scalar;
}
public IfExprTimestampColumnScalar() {
super();
// Dummy final assignments.
arg1Column = -1;
arg2Column = -1;
arg3Scalar = null;
}
@Override
public void evaluate(VectorizedRowBatch batch) throws HiveException {
if (childExpressions != null) {
super.evaluateChildren(batch);
}
LongColumnVector arg1ColVector = (LongColumnVector) batch.cols[arg1Column];
TimestampColumnVector arg2ColVector = (TimestampColumnVector) batch.cols[arg2Column];
boolean[] arg2IsNull = arg2ColVector.isNull;
TimestampColumnVector outputColVector = (TimestampColumnVector) batch.cols[outputColumnNum];
int[] sel = batch.selected;
boolean[] outputIsNull = outputColVector.isNull;
// We do not need to do a column reset since we are carefully changing the output.
outputColVector.isRepeating = false;
int n = batch.size;
long[] vector1 = arg1ColVector.vector;
// return immediately if batch is empty
if (n == 0) {
return;
}
if (arg1ColVector.isRepeating) {
if ((arg1ColVector.noNulls || !arg1ColVector.isNull[0]) && vector1[0] == 1) {
arg2ColVector.copySelected(batch.selectedInUse, sel, n, outputColVector);
} else {
outputColVector.fill(arg3Scalar);
}
return;
}
// Extend any repeating values and noNulls indicator in the inputs to
// reduce the number of code paths needed below.
arg2ColVector.flatten(batch.selectedInUse, sel, n);
if (arg1ColVector.noNulls) {
// FUTURE: We could check arg2ColVector.noNulls and optimize these loops.
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
if (vector1[i] == 1) {
if (!arg2IsNull[i]) {
outputIsNull[i] = false;
outputColVector.set(i, arg2ColVector.asScratchTimestamp(i));
} else {
outputIsNull[i] = true;
outputColVector.noNulls = false;
}
} else {
outputIsNull[i] = false;
outputColVector.set(i, arg3Scalar);
}
}
} else {
for(int i = 0; i != n; i++) {
if (vector1[i] == 1) {
if (!arg2IsNull[i]) {
outputIsNull[i] = false;
outputColVector.set(i, arg2ColVector.asScratchTimestamp(i));
} else {
outputIsNull[i] = true;
outputColVector.noNulls = false;
}
} else {
outputIsNull[i] = false;
outputColVector.set(i, arg3Scalar);
}
}
}
} else /* there are nulls */ {
if (batch.selectedInUse) {
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!arg1ColVector.isNull[i] && vector1[i] == 1) {
if (!arg2IsNull[i]) {
outputIsNull[i] = false;
outputColVector.set(i, arg2ColVector.asScratchTimestamp(i));
} else {
outputIsNull[i] = true;
outputColVector.noNulls = false;
}
} else {
outputIsNull[i] = false;
outputColVector.set(i, arg3Scalar);
}
}
} else {
for(int i = 0; i != n; i++) {
if (!arg1ColVector.isNull[i] && vector1[i] == 1) {
if (!arg2IsNull[i]) {
outputIsNull[i] = false;
outputColVector.set(i, arg2ColVector.asScratchTimestamp(i));
} else {
outputIsNull[i] = true;
outputColVector.noNulls = false;
}
} else {
outputIsNull[i] = false;
outputColVector.set(i, arg3Scalar);
}
}
}
}
// restore repeating and no nulls indicators
arg2ColVector.unFlatten();
}
@Override
public String vectorExpressionParameters() {
return getColumnParamString(0, arg1Column) + ", " + getColumnParamString(1, arg2Column) +
", val "+ arg3Scalar;
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
return (new VectorExpressionDescriptor.Builder())
.setMode(
VectorExpressionDescriptor.Mode.PROJECTION)
.setNumArguments(3)
.setArgumentTypes(
VectorExpressionDescriptor.ArgumentType.getType("int_family"),
VectorExpressionDescriptor.ArgumentType.getType("timestamp"),
VectorExpressionDescriptor.ArgumentType.getType("timestamp"))
.setInputExpressionTypes(
VectorExpressionDescriptor.InputExpressionType.COLUMN,
VectorExpressionDescriptor.InputExpressionType.COLUMN,
VectorExpressionDescriptor.InputExpressionType.SCALAR).build();
}
}
