/** * 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.expressions.VectorExpression; import org.apache.hadoop.hive.ql.exec.vector.; 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.expressions.NullUtil; import org.apache.hadoop.hive.ql.exec.vector.VectorExpressionDescriptor; /** * Generated from template ColumnArithmeticScalar.txt, which covers binary arithmetic * expressions between a column and a scalar. */ public class extends VectorExpression { private static final long serialVersionUID = 1L; private int colNum; private value; private int outputColumn; public (int colNum, value, int outputColumn) { this.colNum = colNum; this.value = value; this.outputColumn = outputColumn; } public () { } @Override public void evaluate(VectorizedRowBatch batch) { if (childExpressions != null) { super.evaluateChildren(batch); } inputColVector = () batch.cols[colNum]; outputColVector = () batch.cols[outputColumn]; int[] sel = batch.selected; boolean[] inputIsNull = inputColVector.isNull; boolean[] outputIsNull = outputColVector.isNull; outputColVector.noNulls = inputColVector.noNulls; outputColVector.isRepeating = inputColVector.isRepeating; int n = batch.size; [] vector = inputColVector.vector; [] outputVector = outputColVector.vector; // return immediately if batch is empty if (n == 0) { return; } if (value == 0) { // Denominator is zero, convert the batch to nulls outputColVector.noNulls = false; outputColVector.isRepeating = true; outputIsNull[0] = true; } else if (inputColVector.isRepeating) { outputVector[0] = vector[0] value; // Even if there are no nulls, we always copy over entry 0. Simplifies code. outputIsNull[0] = inputIsNull[0]; } else if (inputColVector.noNulls) { if (batch.selectedInUse) { for(int j = 0; j != n; j++) { int i = sel[j]; outputVector[i] = vector[i] value; } } else { for(int i = 0; i != n; i++) { outputVector[i] = vector[i] value; } } } else /* there are nulls */ { if (batch.selectedInUse) { for(int j = 0; j != n; j++) { int i = sel[j]; outputVector[i] = vector[i] value; outputIsNull[i] = inputIsNull[i]; } } else { for(int i = 0; i != n; i++) { outputVector[i] = vector[i] value; } System.arraycopy(inputIsNull, 0, outputIsNull, 0, n); } } NullUtil.setNullOutputEntriesColScalar(outputColVector, batch.selectedInUse, sel, n); } @Override public int getOutputColumn() { return outputColumn; } @Override public String getOutputType() { return ""; } public int getColNum() { return colNum; } public void setColNum(int colNum) { this.colNum = colNum; } public getValue() { return value; } public void setValue( value) { this.value = value; } public void setOutputColumn(int outputColumn) { this.outputColumn = outputColumn; } @Override public VectorExpressionDescriptor.Descriptor getDescriptor() { return (new VectorExpressionDescriptor.Builder()) .setMode( VectorExpressionDescriptor.Mode.PROJECTION) .setNumArguments(2) .setArgumentTypes( VectorExpressionDescriptor.ArgumentType.getType(""), VectorExpressionDescriptor.ArgumentType.getType("")) .setInputExpressionTypes( VectorExpressionDescriptor.InputExpressionType.COLUMN, VectorExpressionDescriptor.InputExpressionType.SCALAR).build(); } }