| /* |
| * 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.DecimalColumnVector; |
| 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.expressions.DecimalUtil; |
| 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 ColumnArithmeticColumnDecimal.txt, which covers binary arithmetic |
| * expressions between a column and a scalar. |
| */ |
| public class <ClassName> extends VectorExpression { |
| |
| private static final long serialVersionUID = 1L; |
| |
| public <ClassName>(int colNum1, int colNum2, int outputColumnNum) { |
| super(colNum1, colNum2, outputColumnNum); |
| } |
| |
| public <ClassName>() { |
| super(); |
| } |
| |
| @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); |
| } |
| |
| DecimalColumnVector inputColVector1 = (DecimalColumnVector) batch.cols[inputColumnNum[0]]; |
| DecimalColumnVector inputColVector2 = (DecimalColumnVector) batch.cols[inputColumnNum[1]]; |
| DecimalColumnVector outputColVector = (DecimalColumnVector) batch.cols[outputColumnNum]; |
| int[] sel = batch.selected; |
| |
| HiveDecimalWritable[] vector1 = inputColVector1.vector; |
| HiveDecimalWritable[] vector2 = inputColVector2.vector; |
| |
| /* |
| * Propagate null values for a two-input operator and set isRepeating and noNulls appropriately. |
| */ |
| NullUtil.propagateNullsColCol( |
| inputColVector1, inputColVector2, outputColVector, sel, n, batch.selectedInUse); |
| |
| /* Disregard nulls for processing. In other words, |
| * the arithmetic operation is performed even if one or |
| * more inputs are null. This is to improve speed by avoiding |
| * conditional checks in the inner loop. |
| */ |
| if (inputColVector1.isRepeating && inputColVector2.isRepeating) { |
| DecimalUtil.<Operator>Checked(0, vector1[0], vector2[0], outputColVector); |
| } else if (inputColVector1.isRepeating) { |
| if (batch.selectedInUse) { |
| for(int j = 0; j != n; j++) { |
| int i = sel[j]; |
| DecimalUtil.<Operator>Checked(i, vector1[0], vector2[i], outputColVector); |
| } |
| } else { |
| for(int i = 0; i != n; i++) { |
| DecimalUtil.<Operator>Checked(i, vector1[0], vector2[i], outputColVector); |
| } |
| } |
| } else if (inputColVector2.isRepeating) { |
| if (batch.selectedInUse) { |
| for(int j = 0; j != n; j++) { |
| int i = sel[j]; |
| DecimalUtil.<Operator>Checked(i, vector1[i], vector2[0], outputColVector); |
| } |
| } else { |
| for(int i = 0; i != n; i++) { |
| DecimalUtil.<Operator>Checked(i, vector1[i], vector2[0], outputColVector); |
| } |
| } |
| } else { |
| if (batch.selectedInUse) { |
| for(int j = 0; j != n; j++) { |
| int i = sel[j]; |
| DecimalUtil.<Operator>Checked(i, vector1[i], vector2[i], outputColVector); |
| } |
| } else { |
| for(int i = 0; i != n; i++) { |
| DecimalUtil.<Operator>Checked(i, vector1[i], vector2[i], outputColVector); |
| } |
| } |
| } |
| |
| /* For the case when the output can have null values, follow |
| * the convention that the data values must be set to a specific non-zero |
| * value. This is to prevent possible later zero-divide errors |
| * in complex arithmetic expressions like col2 / (col1 - 1) |
| * in the case when some col1 entries are null. |
| */ |
| NullUtil.setNullDataEntriesDecimal(outputColVector, batch.selectedInUse, sel, n); |
| } |
| |
| @Override |
| public String vectorExpressionParameters() { |
| return getColumnParamString(0, inputColumnNum[0]) + ", " + getColumnParamString(1, inputColumnNum[1]); |
| } |
| |
| @Override |
| public VectorExpressionDescriptor.Descriptor getDescriptor() { |
| return (new VectorExpressionDescriptor.Builder()) |
| .setMode( |
| VectorExpressionDescriptor.Mode.PROJECTION) |
| .setNumArguments(2) |
| .setArgumentTypes( |
| VectorExpressionDescriptor.ArgumentType.getType("decimal"), |
| VectorExpressionDescriptor.ArgumentType.getType("decimal")) |
| .setInputExpressionTypes( |
| VectorExpressionDescriptor.InputExpressionType.COLUMN, |
| VectorExpressionDescriptor.InputExpressionType.COLUMN).build(); |
| } |
| } |