org.apache.hadoop.hive.ql.exec.vector.expressions.VectorElt Maven / Gradle / Ivy
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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;
import org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.LongColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.VectorExpressionDescriptor;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
public class VectorElt extends VectorExpression {
private static final long serialVersionUID = 1L;
private int [] inputColumns;
private int outputColumn;
public VectorElt(int [] inputColumns, int outputColumn) {
this();
this.inputColumns = inputColumns;
this.outputColumn = outputColumn;
}
public VectorElt() {
super();
}
@Override
public void evaluate(VectorizedRowBatch batch) {
if (childExpressions != null) {
super.evaluateChildren(batch);
}
int[] sel = batch.selected;
int n = batch.size;
BytesColumnVector outputVector = (BytesColumnVector) batch.cols[outputColumn];
if (n <= 0) {
return;
}
outputVector.init();
outputVector.noNulls = false;
outputVector.isRepeating = false;
LongColumnVector inputIndexVector = (LongColumnVector) batch.cols[inputColumns[0]];
long[] indexVector = inputIndexVector.vector;
if (inputIndexVector.isRepeating) {
int index = (int)indexVector[0];
if (index > 0 && index < inputColumns.length) {
BytesColumnVector cv = (BytesColumnVector) batch.cols[inputColumns[index]];
if (cv.isRepeating) {
outputVector.setElement(0, 0, cv);
outputVector.isRepeating = true;
} else if (batch.selectedInUse) {
for (int j = 0; j != n; j++) {
int i = sel[j];
outputVector.setVal(i, cv.vector[0], cv.start[0], cv.length[0]);
}
} else {
for (int i = 0; i != n; i++) {
outputVector.setVal(i, cv.vector[0], cv.start[0], cv.length[0]);
}
}
} else {
outputVector.isNull[0] = true;
outputVector.isRepeating = true;
}
} else if (batch.selectedInUse) {
for (int j = 0; j != n; j++) {
int i = sel[j];
int index = (int)indexVector[i];
if (index > 0 && index < inputColumns.length) {
BytesColumnVector cv = (BytesColumnVector) batch.cols[inputColumns[index]];
int cvi = cv.isRepeating ? 0 : i;
outputVector.setVal(i, cv.vector[cvi], cv.start[cvi], cv.length[cvi]);
} else {
outputVector.isNull[i] = true;
}
}
} else {
for (int i = 0; i != n; i++) {
int index = (int)indexVector[i];
if (index > 0 && index < inputColumns.length) {
BytesColumnVector cv = (BytesColumnVector) batch.cols[inputColumns[index]];
int cvi = cv.isRepeating ? 0 : i;
outputVector.setVal(i, cv.vector[cvi], cv.start[cvi], cv.length[cvi]);
} else {
outputVector.isNull[i] = true;
}
}
}
}
@Override
public int getOutputColumn() {
return outputColumn;
}
@Override
public String getOutputType() {
return outputType;
}
public int [] getInputColumns() {
return inputColumns;
}
public void setInputColumns(int [] inputColumns) {
this.inputColumns = inputColumns;
}
public void setOutputColumn(int outputColumn) {
this.outputColumn = outputColumn;
}
@Override
public VectorExpressionDescriptor.Descriptor getDescriptor() {
// Descriptor is not defined because it takes variable number of arguments with different
// data types.
throw new UnsupportedOperationException("Undefined descriptor");
}
}