dilipbiswal commented on a change in pull request #24759: [SPARK-27395][SQL][WIP] Improve EXPLAIN command URL: https://github.com/apache/spark/pull/24759#discussion_r315804244
########## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/ExplainUtils.scala ########## @@ -0,0 +1,214 @@ +/* + * 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.execution + +import scala.collection.mutable +import scala.collection.mutable.ArrayBuffer + +import org.apache.spark.sql.AnalysisException +import org.apache.spark.sql.catalyst.expressions.{Expression, PlanExpression} +import org.apache.spark.sql.catalyst.plans.QueryPlan +import org.apache.spark.sql.catalyst.trees.TreeNodeTag + +object ExplainUtils { + /** + * Given a input physical plan, performs the following tasks. + * 1. Generate the plan -> operator id map. + * 2. Generate the plan -> codegen id map + * 3. Generate the two part explain output for this plan. + * 1. First part explains the operator tree with each operator tagged with an unique + * identifier. + * 2. Second part explans each operator in a verbose manner. + * + * Note : This function skips over subqueries. They are handled by its caller. + */ + private def processPlanSkippingSubqueries[T <: QueryPlan[T]]( + plan: => QueryPlan[T], + append: String => Unit, + startOperatorID: Int): Int = { + + // ReusedSubqueryExecs are skipped over + if (plan.isInstanceOf[BaseSubqueryExec]) { + return startOperatorID + } + + val operationIDs = new mutable.ArrayBuffer[(Int, QueryPlan[_])]() + var currentOperatorID = startOperatorID + try { + currentOperatorID = generateOperatorIDs(plan, currentOperatorID, operationIDs) + generateWholeStageCodegenIdMap(plan) + + QueryPlan.append( + plan, + append, + verbose = false, + addSuffix = false, + printOperatorId = true) + + append("\n") + var i: Integer = 0 + for ((opId, curPlan) <- operationIDs) { + append(curPlan.verboseStringWithOperatorId()) + } + } catch { + case e: AnalysisException => append(e.toString) + } + currentOperatorID + } + + /** + * Given a input physical plan, performs the following tasks. + * 1. Generates the explain output for the input plan excluding the subquery plans. + * 2. Generates the explain output for each subquery referenced in the plan. + */ + def processPlan[T <: QueryPlan[T]]( + plan: => QueryPlan[T], + append: String => Unit): Unit = { + try { + val subqueries = ArrayBuffer.empty[(SparkPlan, Expression, SparkPlan)] + var currentOperatorID = 0 + currentOperatorID = processPlanSkippingSubqueries(plan, append, currentOperatorID) + getSubqueries(plan, subqueries) + var i = 0 + + // Process all the subqueries in the plan. + for (sub <- subqueries) { + if (i == 0) { + append("\n===== Subqueries =====\n\n") + } + i = i + 1 + append(s"Subquery:$i Hosting operator id = " + + s"${getOpId(sub._1)} Hosting Expression = ${sub._2}\n") + + // For each subquery expression in the parent plan, process its child plan to compute + // the explain output. + currentOperatorID = processPlanSkippingSubqueries( + sub._3, + append, + currentOperatorID) + append("\n") + } + } finally { + removeTags(plan) + } + } + + /** + * Traverses the supplied input plan in a bottem-up fashion to produce the following two maps : + * 1. operator -> operator identifier + * 2. operator identifier -> operator + * Note : + * 1. Operator such as WholeStageCodegenExec and InputAdapter are skipped as they don't + * appear in the explain output. + * 2. operator identifier starts at startIdx + 1 + */ + private def generateOperatorIDs( + plan: QueryPlan[_], + startOperatorID: Int, + operatorIDs: mutable.ArrayBuffer[(Int, QueryPlan[_])]): Int = { + var currentOperationID = startOperatorID + // Skip the subqueries as they are not printed as part of main query block. + if (plan.isInstanceOf[BaseSubqueryExec]) { + return currentOperationID + } + plan.foreachUp { + case p: WholeStageCodegenExec => + case p: InputAdapter => + case other: QueryPlan[_] => + if (!other.getTagValue(QueryPlan.opidTag).isDefined) { + currentOperationID += 1 + other.setTagValue(QueryPlan.opidTag, currentOperationID) + operatorIDs += ((currentOperationID, other)) + } + other.innerChildren.foreach { plan => + currentOperationID = generateOperatorIDs(plan, + currentOperationID, + operatorIDs) + } + } + currentOperationID + } + /** + * Traverses the supplied input plan in a top-down fashion to produce the following map: + * 1. operator -> whole stage codegen id + */ + private def generateWholeStageCodegenIdMap(plan: QueryPlan[_]): Unit = { + // Skip the subqueries as they are not printed as part of main query block. + if (plan.isInstanceOf[BaseSubqueryExec]) { + return + } + var currentCodegenId = -1 + plan.foreach { + case p: WholeStageCodegenExec => currentCodegenId = p.codegenStageId + case p: InputAdapter => currentCodegenId = -1 + case other: QueryPlan[_] => + if (currentCodegenId != -1) { + other.setTagValue(QueryPlan.codegenTag, currentCodegenId) + } + other.innerChildren.foreach { plan => + generateWholeStageCodegenIdMap(plan) + } + } + } + + /** + * Given a input plan, returns an array of tuples comprising of : + * 1. Hosting opeator id. + * 2. Hosting expression + * 3. Subquery plan + */ + private def getSubqueries[T <: QueryPlan[T]]( + plan: => QueryPlan[_], + subqueries: ArrayBuffer[(SparkPlan, Expression, SparkPlan)]): Unit = { Review comment: @cloud-fan Since this function is recursive, i think having it this way is more optimal ? Or else we may need to create more objects and do more copying ? https://stackoverflow.com/questions/27886116/how-to-return-an-arraylist-with-an-recursive-function ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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