ueshin commented on code in PR #47884: URL: https://github.com/apache/spark/pull/47884#discussion_r1735198983
########## sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveTranspose.scala: ########## @@ -0,0 +1,183 @@ +/* + * 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.AnalysisException +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.{Alias, Ascending, Attribute, AttributeReference, Cast, IsNotNull, Literal, SortOrder} +import org.apache.spark.sql.catalyst.plans.logical.{Filter, Limit, LocalRelation, LogicalPlan, Project, Sort, Transpose} +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.catalyst.trees.TreePattern +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.types.{AtomicType, DataType, StringType} +import org.apache.spark.unsafe.types.UTF8String + + +class ResolveTranspose(sparkSession: SparkSession) extends Rule[LogicalPlan] { + + private def leastCommonType(dataTypes: Seq[DataType]): DataType = { + if (dataTypes.isEmpty) { + StringType + } else { + dataTypes.reduce { (dt1, dt2) => + TypeCoercion.findTightestCommonType(dt1, dt2).getOrElse { + throw new AnalysisException( + errorClass = "TRANSPOSE_NO_LEAST_COMMON_TYPE", + messageParameters = Map( + "dt1" -> dt1.toString, + "dt2" -> dt2.toString) + ) + } + } + } + } + + private def transposeMatrix( + fullCollectedRows: Array[InternalRow], + nonIndexColumnNames: Seq[String], + nonIndexColumnDataTypes: Seq[DataType]): Array[Array[Any]] = { + val numTransposedRows = fullCollectedRows.head.numFields - 1 + val numTransposedCols = fullCollectedRows.length + 1 + val finalMatrix = Array.ofDim[Any](numTransposedRows, numTransposedCols) + + // Example of the original DataFrame: + // +---+-----+-----+ + // | id|col1 |col2 | + // +---+-----+-----+ + // | 1| 10 | 20 | + // | 2| 30 | 40 | + // +---+-----+-----+ + // + // After transposition, the finalMatrix will look like: + // [ + // ["col1", 10, 30], // Transposed row for col1 + // ["col2", 20, 40] // Transposed row for col2 + // ] + + for (i <- 0 until numTransposedRows) { + // Insert non-index column name as the first element in each transposed row + finalMatrix(i)(0) = UTF8String.fromString(nonIndexColumnNames(i)) + + for (j <- 1 until numTransposedCols) { + // Insert the transposed data + + // Example: If j = 2, then row = fullCollectedRows(1) + // This corresponds to the second row of the original DataFrame: InternalRow(2, 30, 40) + val row = fullCollectedRows(j - 1) + + // Example: If i = 0 (for "col1"), and j = 2, + // then finalMatrix(0)(2) corresponds to row.get(1, nonIndexColumnDataTypes(0)), + // which accesses the value 30 from InternalRow(2, 30, 40) + finalMatrix(i)(j) = row.get(i + 1, nonIndexColumnDataTypes(i)) + } + } + finalMatrix + } + + override def apply(plan: LogicalPlan): LogicalPlan = plan.resolveOperatorsWithPruning( + _.containsPattern(TreePattern.UNRESOLVED_TRANSPOSE)) { + case t @ UnresolvedTranspose(indexColumn, child) if indexColumn.resolved && child.resolved => + + // Cast the index column to StringType + val indexColumnAsString = indexColumn match { + case attr: Attribute if attr.dataType.isInstanceOf[AtomicType] => + Alias(Cast(attr, StringType), attr.name)() + case attr: Attribute => + throw new AnalysisException( + errorClass = "INVALID_INDEX_COLUMN", + messageParameters = Map( + "reason" -> s"Index column must be of atomic type, but found: ${attr.dataType}") + ) + case _ => + throw new AnalysisException( + errorClass = "INVALID_INDEX_COLUMN", + messageParameters = Map( + "reason" -> s"Index column must be an atomic attribute") + ) + } + + // Cast non-index columns to the least common type + val nonIndexColumnsAttr = child.output.filterNot( + _.exprId == indexColumn.asInstanceOf[Attribute].exprId) + val nonIndexTypes = nonIndexColumnsAttr.map(_.dataType) + val commonType = leastCommonType(nonIndexTypes) + val nonIndexColumnsAsLCT = nonIndexColumnsAttr.map { attr => + Alias(Cast(attr, commonType), attr.name)() + } + + // Exclude nulls and sort index column values, and collect the casted frame + val allCastCols = indexColumnAsString +: nonIndexColumnsAsLCT + val nonNullChild = Filter(IsNotNull(indexColumn), child) + val sortedChild = Sort( + Seq(SortOrder(indexColumn.asInstanceOf[Attribute], Ascending)), + global = true, + nonNullChild + ) + val projectAllCastCols = Project(allCastCols, sortedChild) + val maxValues = sparkSession.sessionState.conf.dataFrameTransposeMaxValues + val limit = Literal(maxValues + 1) + val limitedProject = Limit(limit, projectAllCastCols) + val queryExecution = sparkSession.sessionState.executePlan(limitedProject) + val fullCollectedRows = queryExecution.executedPlan.executeCollect() + + if (fullCollectedRows.isEmpty) { + // Return a DataFrame with a single column "key" containing non-index column names + val keyAttr = AttributeReference("key", StringType, nullable = false)() + val keyValues = nonIndexColumnsAttr.map( + _.name).map(name => UTF8String.fromString(name)) + val keyRows = keyValues.map(value => InternalRow(value)) + + LocalRelation(Seq(keyAttr), keyRows) + } else { + val rowCount = fullCollectedRows.length + if (rowCount > maxValues) { + throw new AnalysisException( + errorClass = "EXCEED_ROW_LIMIT", + messageParameters = Map( + "maxValues" -> maxValues.toString, + "config" -> SQLConf.DATAFRAME_TRANSPOSE_MAX_VALUES.key)) + } + + // Transpose the matrix + val nonIndexColumnNames = nonIndexColumnsAttr.map(_.name) + val nonIndexColumnDataTypes = projectAllCastCols.output.tail.map(attr => attr.dataType) + val transposedMatrix = transposeMatrix( + fullCollectedRows, nonIndexColumnNames, nonIndexColumnDataTypes) + val transposedInternalRows = transposedMatrix.map { row => + InternalRow.fromSeq(row.toIndexedSeq) + } + + // Construct output attributes + val keyAttr = AttributeReference("key", StringType, nullable = false)() + val transposedColumnNames = fullCollectedRows.map { row => row.getString(0) } + val valueAttrs = transposedColumnNames.map { value => + AttributeReference( + value, + commonType + )() + } + + val hasNonIndexColumns = nonIndexColumnsAttr.nonEmpty + val transposeOutput = (keyAttr +: valueAttrs).toIndexedSeq + val transposeData = transposedInternalRows.toIndexedSeq + println("are we here 2") Review Comment: remove this? -- This is an automated message from the Apache Git Service. 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