spark PullOutNondeterministic 源码

spark PullOutNondeterministic 代码

文件路径：/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/PullOutNondeterministic.scala

/*
 * 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.analysis

import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules.Rule

/**
 * Pulls out nondeterministic expressions from LogicalPlan which is not Project or Filter,
 * put them into an inner Project and finally project them away at the outer Project.
 */
object PullOutNondeterministic extends Rule[LogicalPlan] {
  override def apply(plan: LogicalPlan): LogicalPlan = plan resolveOperatorsUp applyLocally

  val applyLocally: PartialFunction[LogicalPlan, LogicalPlan] = {
    case p if !p.resolved => p // Skip unresolved nodes.
    case p: Project => p
    case f: Filter => f

    case a: Aggregate if a.groupingExpressions.exists(!_.deterministic) =>
      val nondeterToAttr = getNondeterToAttr(a.groupingExpressions)
      val newChild = Project(a.child.output ++ nondeterToAttr.values, a.child)
      a.transformExpressions { case e =>
        nondeterToAttr.get(e).map(_.toAttribute).getOrElse(e)
      }.copy(child = newChild)

    // Don't touch collect metrics. Top-level metrics are not supported (check analysis will fail)
    // and we want to retain them inside the aggregate functions.
    case m: CollectMetrics => m

    // todo: It's hard to write a general rule to pull out nondeterministic expressions
    // from LogicalPlan, currently we only do it for UnaryNode which has same output
    // schema with its child.
    case p: UnaryNode if p.output == p.child.output && p.expressions.exists(!_.deterministic) =>
      val nondeterToAttr = getNondeterToAttr(p.expressions)
      val newPlan = p.transformExpressions { case e =>
        nondeterToAttr.get(e).map(_.toAttribute).getOrElse(e)
      }
      val newChild = Project(p.child.output ++ nondeterToAttr.values, p.child)
      Project(p.output, newPlan.withNewChildren(newChild :: Nil))
  }

  private def getNondeterToAttr(exprs: Seq[Expression]): Map[Expression, NamedExpression] = {
    exprs.filterNot(_.deterministic).flatMap { expr =>
      val leafNondeterministic = expr.collect {
        case n: Nondeterministic => n
        case udf: UserDefinedExpression if !udf.deterministic => udf
      }
      leafNondeterministic.distinct.map { e =>
        val ne = e match {
          case n: NamedExpression => n
          case _ => Alias(e, "_nondeterministic")()
        }
        e -> ne
      }
    }.toMap
  }
}

相关信息

spark 源码目录

相关文章

spark AlreadyExistException 源码

spark Analyzer 源码

spark AnsiTypeCoercion 源码

spark CTESubstitution 源码

spark CannotReplaceMissingTableException 源码

spark CheckAnalysis 源码

spark DecimalPrecision 源码

spark DeduplicateRelations 源码

spark FunctionRegistry 源码

spark HintErrorLogger 源码