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_r315803402
########## 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 = { Review comment: @cloud-fan thanks.. will change. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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