org.apache.hadoop.hive.ql.exec.vector.expressions.gen.FilterLongColLessLongScalar Maven / Gradle / Ivy
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* to you under the Apache License, Version 2.0 (the
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*
* http://www.apache.org/licenses/LICENSE-2.0
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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.LongColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.exec.vector.VectorExpressionDescriptor;
import org.apache.hadoop.hive.ql.metadata.HiveException;
/**
* Generated from template FilterColumnCompareScalar.txt, which covers binary comparison
* expressions between a column and a scalar, however output is not produced in a separate column.
* The selected vector of the input {@link VectorizedRowBatch} is updated for in-place filtering.
*/
public class FilterLongColLessLongScalar extends VectorExpression {
private static final long serialVersionUID = 1L;
protected final int colNum;
protected final long value;
public FilterLongColLessLongScalar(int colNum, long value) {
this.colNum = colNum;
this.value = value;
}
public FilterLongColLessLongScalar() {
super();
// Dummy final assignments.
colNum = -1;
value = 0;
}
@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);
}
LongColumnVector inputColVector = (LongColumnVector) batch.cols[colNum];
int[] sel = batch.selected;
boolean[] inputIsNull = inputColVector.isNull;
long[] vector = inputColVector.vector;
if (inputColVector.noNulls) {
if (inputColVector.isRepeating) {
if (!(vector[0] < value)) {
//Entire batch is filtered out.
batch.size = 0;
}
} else if (batch.selectedInUse) {
int newSize = 0;
for(int j=0; j != n; j++) {
int i = sel[j];
if (vector[i] < value) {
sel[newSize++] = i;
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (vector[i] < value) {
sel[newSize++] = i;
}
}
if (newSize < n) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else {
if (inputColVector.isRepeating) {
if (!inputIsNull[0]) {
if (!(vector[0] < value)) {
//Entire batch is filtered out.
batch.size = 0;
}
} else {
batch.size = 0;
}
} else if (batch.selectedInUse) {
int newSize = 0;
for(int j=0; j != n; j++) {
int i = sel[j];
if (!inputIsNull[i]) {
if (vector[i] < value) {
sel[newSize++] = i;
}
}
}
//Change the selected vector
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (!inputIsNull[i]) {
if (vector[i] < value) {
sel[newSize++] = i;
}
}
}
if (newSize < n) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
}
}
@Override
public String vectorExpressionParameters() {
return getColumnParamString(0, colNum) + ", val " + value;
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
return (new VectorExpressionDescriptor.Builder())
.setMode(
VectorExpressionDescriptor.Mode.FILTER)
.setNumArguments(2)
.setArgumentTypes(
VectorExpressionDescriptor.ArgumentType.getType("long"),
VectorExpressionDescriptor.ArgumentType.getType("long"))
.setInputExpressionTypes(
VectorExpressionDescriptor.InputExpressionType.COLUMN,
VectorExpressionDescriptor.InputExpressionType.SCALAR).build();
}
}