/*
 *   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.wayang.api.dataquanta.builder

import org.apache.wayang.api.JavaPlanBuilder
import org.apache.wayang.api.dataquanta.{DataQuanta, DataQuantaBuilder}
import org.apache.wayang.api.util.TypeTrap
import org.apache.wayang.basic.operators.MapOperator
import org.apache.wayang.core.function.FunctionDescriptor.{SerializableFunction, SerializablePredicate}
import org.apache.wayang.core.optimizer.ProbabilisticDoubleInterval
import org.apache.wayang.core.optimizer.costs.{LoadProfile, LoadProfileEstimator}
import org.apache.wayang.core.types.DataSetType
import org.apache.wayang.core.util.ReflectionUtils

/**
 * [[DataQuantaBuilder]] implementation for [[org.apache.wayang.basic.operators.MapOperator]]s.
 *
 * @param inputDataQuanta [[DataQuantaBuilder]] for the input [[DataQuanta]]
 * @param udf             UDF for the [[MapOperator]]
 */
class FilterDataQuantaBuilder[T](inputDataQuanta: DataQuantaBuilder[_, T], udf: SerializablePredicate[T])
                                (implicit javaPlanBuilder: JavaPlanBuilder)
  extends BasicDataQuantaBuilder[FilterDataQuantaBuilder[T], T] {

  // Reuse the input TypeTrap to enforce type equality between input and output.
  override def getOutputTypeTrap: TypeTrap = inputDataQuanta.outputTypeTrap

  /** [[LoadProfileEstimator]] to estimate the [[LoadProfile]] of the [[udf]]. */
  private var udfLoadProfileEstimator: LoadProfileEstimator = _

  /** Selectivity of the filter predicate. */
  private var selectivity: ProbabilisticDoubleInterval = _

  /** SQL UDF implementing the filter predicate. */
  private var sqlUdf: String = _

  // Try to infer the type classes from the udf.
  locally {
    val parameters = ReflectionUtils.getTypeParameters(udf.getClass, classOf[SerializableFunction[_, _]])
    parameters.get("Input") match {
      case cls: Class[T] => this.outputTypeTrap.dataSetType = DataSetType.createDefault(cls)
      case _ => logger.warn("Could not infer types from {}.", udf)
    }
  }


  /**
   * Set a [[LoadProfileEstimator]] for the load of the UDF.
   *
   * @param udfLoadProfileEstimator the [[LoadProfileEstimator]]
   * @return this instance
   */
  def withUdfLoad(udfLoadProfileEstimator: LoadProfileEstimator) = {
    this.udfLoadProfileEstimator = udfLoadProfileEstimator
    this
  }

  /**
   * Add a SQL implementation of the UDF.
   *
   * @param sqlUdf a SQL condition that can be plugged into a `WHERE` clause
   * @return this instance
   */
  def withSqlUdf(sqlUdf: String) = {
    this.sqlUdf = sqlUdf
    this
  }

  /**
   * Specify the selectivity of the UDF.
   *
   * @param lowerEstimate the lower bound of the expected selectivity
   * @param upperEstimate the upper bound of the expected selectivity
   * @param confidence    the probability of the actual selectivity being within these bounds
   * @return this instance
   */
  def withSelectivity(lowerEstimate: Double, upperEstimate: Double, confidence: Double) = {
    this.selectivity = new ProbabilisticDoubleInterval(lowerEstimate, upperEstimate, confidence)
    this
  }

  override protected def build = inputDataQuanta.dataQuanta().filterJava(
    udf, this.sqlUdf, this.selectivity, this.udfLoadProfileEstimator
  )

}