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/*
 * Copyright © 2021-present Arcade Data Ltd ([email protected])
 *
 * Licensed 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.
 *
 * SPDX-FileCopyrightText: 2021-present Arcade Data Ltd ([email protected])
 * SPDX-License-Identifier: Apache-2.0
 */
package com.arcadedb.query.sql.function.math;

import com.arcadedb.database.Identifiable;
import com.arcadedb.query.sql.executor.CommandContext;
import com.arcadedb.query.sql.executor.MultiValue;
import com.arcadedb.query.sql.function.SQLFunctionAbstract;

/**
 * Compute the variance estimation for a given field.
 * 
 * This class uses the Weldford's algorithm (presented in Donald Knuth's Art of Computer Programming) to avoid multiple distribution
 * values' passes. When executed in distributed mode it uses the Chan at al. pairwise variance algorithm to merge the results.
 * 

 * 

 * References
 * 
 *
 * 
 *
 * Cook, John D. Accurately computing running variance.
 *
 * Knuth, Donald E. (1998) The Art of Computer Programming, Volume 2: Seminumerical Algorithms, 3rd Edition.
 *
 * Welford, B. P. (1962) Note on a method for calculating corrected sums of squares and products. Technometrics
 *
 * Chan, Tony F.; Golub, Gene H.; LeVeque, Randall J. (1979), Parallel Algorithm.
 *
 * 
 *
 * @author Fabrizio Fortino
 */
public class SQLFunctionVariance extends SQLFunctionAbstract {

  public static final String NAME = "variance";

  private long   n;
  private double mean;
  private double m2;

  public SQLFunctionVariance() {
    super(NAME);
  }

  protected SQLFunctionVariance(final String name) {
    super(name);
  }

  @Override
  public Object execute(final Object iThis, final Identifiable iCurrentRecord, final Object iCurrentResult, final Object[] iParams,
      final CommandContext iContext) {
    if (iParams[0] instanceof Number) {
      addValue((Number) iParams[0]);
    } else if (MultiValue.isMultiValue(iParams[0])) {
      for (final Object n : MultiValue.getMultiValueIterable(iParams[0])) {
        addValue((Number) n);
      }
    }
    return null;
  }

  @Override
  public boolean aggregateResults() {
    return true;
  }

  @Override
  public Object getResult() {
    return this.evaluate();
  }

  @Override
  public String getSyntax() {
    return NAME + "()";
  }

  private void addValue(final Number value) {
    if (value != null) {
      ++n;
      final double doubleValue = value.doubleValue();
      final double nextM = mean + (doubleValue - mean) / n;
      m2 += (doubleValue - mean) * (doubleValue - nextM);
      mean = nextM;
    }
  }

  private Double evaluate() {
    return n > 1 ? m2 / n : null;
  }

}