/*
 * 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();
}