/*
 * 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.spark.sql.catalyst.optimizer

import org.apache.spark.sql.catalyst.plans.logical.{GlobalLimit, LocalLimit, LogicalPlan, Project}
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.catalyst.trees.TreePattern.{LIMIT, PROJECT}

/**
 * Pushes Project operator through Limit operator.
 */
object PushProjectionThroughLimit extends Rule[LogicalPlan] {
  def apply(plan: LogicalPlan): LogicalPlan = plan.transformWithPruning(
    _.containsAllPatterns(PROJECT, LIMIT)) {

    case p @ Project(projectList, limit @ LocalLimit(_, child))
        if projectList.forall(_.deterministic) =>
      limit.copy(child = p.copy(projectList, child))

    case p @ Project(projectList, g @ GlobalLimit(_, limit @ LocalLimit(_, child)))
        if projectList.forall(_.deterministic) =>
      g.copy(child = limit.copy(child = p.copy(projectList, child)))
  }
}
