| /* |
| * 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.druid.math.expr.vector; |
| |
| import org.apache.druid.math.expr.Expr; |
| |
| /** |
| * common machinery for processing single input operators and functions, which are backed by an object value instead of |
| * a primitive value (so do not need to use the null vector, and instead can check the value vector itself for nulls) |
| */ |
| public abstract class UnivariateFunctionVectorObjectProcessor<TInput, TOutput> implements ExprVectorProcessor<TOutput> |
| { |
| final ExprVectorProcessor<TInput> processor; |
| final int maxVectorSize; |
| final boolean[] outNulls; |
| final TOutput outValues; |
| |
| public UnivariateFunctionVectorObjectProcessor( |
| ExprVectorProcessor<TInput> processor, |
| int maxVectorSize, |
| TOutput outValues |
| ) |
| { |
| this.processor = processor; |
| this.maxVectorSize = maxVectorSize; |
| this.outNulls = new boolean[maxVectorSize]; |
| this.outValues = outValues; |
| } |
| |
| @Override |
| public ExprEvalVector<TOutput> evalVector(Expr.VectorInputBinding bindings) |
| { |
| final ExprEvalVector<TInput> lhs = processor.evalVector(bindings); |
| |
| final int currentSize = bindings.getCurrentVectorSize(); |
| |
| final TInput input = lhs.values(); |
| |
| for (int i = 0; i < currentSize; i++) { |
| processIndex(input, outValues, outNulls, i); |
| } |
| return asEval(); |
| } |
| |
| public abstract void processIndex(TInput input, TOutput output, boolean[] outputNulls, int i); |
| |
| public abstract ExprEvalVector<TOutput> asEval(); |
| } |