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org.apache.hadoop.hive.ql.exec.vector.expressions.gen.FilterTimestampColGreaterEqualTimestampColumn Maven / Gradle / Ivy
/*
* 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.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.TimestampColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.*;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.exec.vector.VectorExpressionDescriptor;
import org.apache.hadoop.hive.serde2.io.HiveDecimalWritable;
import org.apache.hadoop.hive.ql.metadata.HiveException;
/**
* Generated from template FilterTimestampColumnCompareColumn.txt, which covers binary comparison
* filter expressions between two columns. Output is not produced in a separate column.
* The selected vector of the input {@link VectorizedRowBatch} is updated for in-place filtering.
*/
public class FilterTimestampColGreaterEqualTimestampColumn extends VectorExpression {
private static final long serialVersionUID = 1L;
private final int colNum1;
private final int colNum2;
public FilterTimestampColGreaterEqualTimestampColumn(int colNum1, int colNum2) {
super();
this.colNum1 = colNum1;
this.colNum2 = colNum2;
}
public FilterTimestampColGreaterEqualTimestampColumn() {
super();
// Dummy final assignments.
colNum1 = -1;
colNum2 = -1;
}
@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 timestamp.
TimestampColumnVector inputColVector1 = (TimestampColumnVector) batch.cols[colNum1];
// Input #2 is type timestamp.
TimestampColumnVector inputColVector2 = (TimestampColumnVector) batch.cols[colNum2];
int[] sel = batch.selected;
boolean[] nullPos1 = inputColVector1.isNull;
boolean[] nullPos2 = inputColVector2.isNull;
// handle case where neither input has nulls
if (inputColVector1.noNulls && inputColVector2.noNulls) {
if (inputColVector1.isRepeating && inputColVector2.isRepeating) {
/* Either all must remain selected or all will be eliminated.
* Repeating property will not change.
*/
if (!(inputColVector1.compareTo(0, inputColVector2, 0) >= 0)) {
batch.size = 0;
}
} else if (inputColVector1.isRepeating) {
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (inputColVector1.compareTo(0, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (inputColVector1.compareTo(0, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else if (inputColVector2.isRepeating) {
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (inputColVector1.compareTo(i, inputColVector2, 0) >= 0) {
sel[newSize++] = i;
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (inputColVector1.compareTo(i, inputColVector2, 0) >= 0) {
sel[newSize++] = i;
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (inputColVector1.compareTo(i, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (inputColVector1.compareTo(i, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
// handle case where only input 2 has nulls
} else if (inputColVector1.noNulls) {
if (inputColVector1.isRepeating && inputColVector2.isRepeating) {
if (nullPos2[0] ||
!(inputColVector1.compareTo(0, inputColVector2, 0) >= 0)) {
batch.size = 0;
}
} else if (inputColVector1.isRepeating) {
// no need to check for nulls in input 1
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!nullPos2[i]) {
if (inputColVector1.compareTo(0, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (!nullPos2[i]) {
if (inputColVector1.compareTo(0, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else if (inputColVector2.isRepeating) {
if (nullPos2[0]) {
// no values will qualify because every comparison will be with NULL
batch.size = 0;
return;
}
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (inputColVector1.compareTo(i, inputColVector2, 0) >= 0) {
sel[newSize++] = i;
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (inputColVector1.compareTo(i, inputColVector2, 0) >= 0) {
sel[newSize++] = i;
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else { // neither input is repeating
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!nullPos2[i]) {
if (inputColVector1.compareTo(i, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (!nullPos2[i]) {
if (inputColVector1.compareTo(i, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
}
// handle case where only input 1 has nulls
} else if (inputColVector2.noNulls) {
if (inputColVector1.isRepeating && inputColVector2.isRepeating) {
if (nullPos1[0] ||
!(inputColVector1.compareTo(0, inputColVector2, 0) >= 0)) {
batch.size = 0;
return;
}
} else if (inputColVector1.isRepeating) {
if (nullPos1[0]) {
// if repeating value is null then every comparison will fail so nothing qualifies
batch.size = 0;
return;
}
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (inputColVector1.compareTo(0, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (inputColVector1.compareTo(0, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else if (inputColVector2.isRepeating) {
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!nullPos1[i]) {
if (inputColVector1.compareTo(i, inputColVector2, 0) >= 0) {
sel[newSize++] = i;
}
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (!nullPos1[i]) {
if (inputColVector1.compareTo(i, inputColVector2, 0) >= 0) {
sel[newSize++] = i;
}
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else { // neither input is repeating
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!nullPos1[i]) {
if (inputColVector1.compareTo(i, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (!nullPos1[i]) {
if (inputColVector1.compareTo(i, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
}
// handle case where both inputs have nulls
} else {
if (inputColVector1.isRepeating && inputColVector2.isRepeating) {
if (nullPos1[0] || nullPos2[0] ||
!(inputColVector1.compareTo(0, inputColVector2, 0) >= 0)) {
batch.size = 0;
}
} else if (inputColVector1.isRepeating) {
if (nullPos1[0]) {
batch.size = 0;
return;
}
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!nullPos2[i]) {
if (inputColVector1.compareTo(0, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (!nullPos2[i]) {
if (inputColVector1.compareTo(0, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else if (inputColVector2.isRepeating) {
if (nullPos2[0]) {
batch.size = 0;
return;
}
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!nullPos1[i]) {
if (inputColVector1.compareTo(i, inputColVector2, 0) >= 0) {
sel[newSize++] = i;
}
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (!nullPos1[i]) {
if (inputColVector1.compareTo(i, inputColVector2, 0) >= 0) {
sel[newSize++] = i;
}
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
} else { // neither input is repeating
if (batch.selectedInUse) {
int newSize = 0;
for(int j = 0; j != n; j++) {
int i = sel[j];
if (!nullPos1[i] && !nullPos2[i]) {
if (inputColVector1.compareTo(i, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
batch.size = newSize;
} else {
int newSize = 0;
for(int i = 0; i != n; i++) {
if (!nullPos1[i] && !nullPos2[i]) {
if (inputColVector1.compareTo(i, inputColVector2, i) >= 0) {
sel[newSize++] = i;
}
}
}
if (newSize < batch.size) {
batch.size = newSize;
batch.selectedInUse = true;
}
}
}
}
}
@Override
public String vectorExpressionParameters() {
return getColumnParamString(0, colNum1) + ", " + getColumnParamString(1, colNum2);
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
return (new VectorExpressionDescriptor.Builder())
.setMode(
VectorExpressionDescriptor.Mode.FILTER)
.setNumArguments(2)
.setArgumentTypes(
VectorExpressionDescriptor.ArgumentType.getType("timestamp"),
VectorExpressionDescriptor.ArgumentType.getType("timestamp"))
.setInputExpressionTypes(
VectorExpressionDescriptor.InputExpressionType.COLUMN,
VectorExpressionDescriptor.InputExpressionType.COLUMN).build();
}
}
