rahil-c commented on code in PR #17904: URL: https://github.com/apache/hudi/pull/17904#discussion_r2730015063
########## hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/execution/datasources/lance/LanceFileFormatHelper.scala: ########## @@ -0,0 +1,152 @@ +/* + * 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.datasources.lance + +import org.apache.spark.sql.HoodieSchemaUtils +import org.apache.spark.sql.catalyst.expressions.{Attribute, Cast, Expression, Literal, UnsafeProjection} +import org.apache.spark.sql.catalyst.expressions.codegen.GenerateUnsafeProjection +import org.apache.spark.sql.types.{DataType, DateType, DecimalType, DoubleType, FloatType, IntegerType, LongType, StringType, StructField, StructType} + +/** + * Helper for Lance file format schema evolution. + */ +object LanceFileFormatHelper { + + /** + * Build schema change info for Lance files. + * + * @param fileStruct The schema from the Lance file + * @param requiredSchema The schema requested by the query + * @return A tuple of (type change map, required schema) + */ + def buildSchemaChangeInfo(fileStruct: StructType, + requiredSchema: StructType): (java.util.Map[Integer, org.apache.hudi.common.util.collection.Pair[DataType, DataType]], StructType) = { + val implicitTypeChangeInfo: java.util.Map[Integer, org.apache.hudi.common.util.collection.Pair[DataType, DataType]] = new java.util.HashMap() + + // Create a map of field names to types from the file schema + val fileStructMap = fileStruct.fields.map(f => (f.name, f.dataType)).toMap + + // Build the request schema, using FILE types for fields with type changes + val sparkRequestStructFields = requiredSchema.map { f => + val requiredType = f.dataType + if (fileStructMap.contains(f.name) && !isDataTypeEqual(requiredType, fileStructMap(f.name))) { + val fileType = fileStructMap(f.name) + // Record the type change: (required type, file type) + implicitTypeChangeInfo.put(new Integer(requiredSchema.fieldIndex(f.name)), + org.apache.hudi.common.util.collection.Pair.of(requiredType, fileType)) + // Return field with FILE type so Lance reads data in its original type + StructField(f.name, fileType, f.nullable) + } else { + f + } + } + + (implicitTypeChangeInfo, StructType(sparkRequestStructFields)) + } + + /** + * Check if two data types are equal. + * For basic type promotion, we simply check equality. + * + * @param requiredType The required data type + * @param fileType The data type from the file + * @return true if the types are equal, false otherwise + */ + def isDataTypeEqual(requiredType: DataType, fileType: DataType): Boolean = { + //TODO to revisit this for further cases (illegal cast, nested types, etc) + requiredType == fileType + } + + /** + * Cast expression from source type to destination type. + * Handles special cases that require intermediate String cast for precision. + * + * @param expr The expression to cast + * @param srcType The source data type + * @param dstType The destination data type + * @param timeZoneId Optional timezone ID for time-aware casts + * @return The cast expression + */ + private def castPrimitiveExpression(expr: Expression, + srcType: DataType, + dstType: DataType, + timeZoneId: Option[String]): Expression = { + lazy val needTimeZone = Cast.needsTimeZone(srcType, dstType) + (srcType, dstType) match { + case (FloatType, DoubleType) => + // Float → String → Double for precision + val toStr = Cast(expr, StringType, if (needTimeZone) timeZoneId else None) + Cast(toStr, dstType, if (needTimeZone) timeZoneId else None) + + case (IntegerType | LongType | FloatType | DoubleType, dec: DecimalType) => + // Numeric → String → Decimal + val toStr = Cast(expr, StringType, if (needTimeZone) timeZoneId else None) + Cast(toStr, dec, if (needTimeZone) timeZoneId else None) + + case (StringType, dec: DecimalType) => + Cast(expr, dec, if (needTimeZone) timeZoneId else None) + + case (StringType, DateType) => + Cast(expr, DateType, if (needTimeZone) timeZoneId else None) + + case _ => + // Standard cast for all other primitive types (Int→Long, Long→Float, etc.) + Cast(expr, dstType, if (needTimeZone) timeZoneId else None) + } + } + + /** + * Generate unsafe projection for schema evolution. + * + * @param inputAttributes The attributes we read from the file (only existing fields) + * @param requiredSchema The required schema (all fields including missing ones) + * @param partitionSchema The partition schema + * @param schemaUtils Schema utilities + * @param typeChangeInfo Map of field index to (required type, file type) pairs + * @return UnsafeProjection to transform rows + */ + def generateUnsafeProjection(inputAttributes: Seq[Attribute], + requiredSchema: StructType, + partitionSchema: StructType, + schemaUtils: HoodieSchemaUtils, + typeChangeInfo: java.util.Map[Integer, org.apache.hudi.common.util.collection.Pair[DataType, DataType]]): UnsafeProjection = { + + val inputFieldMap = inputAttributes.map(a => a.name -> a).toMap + + val expressions = requiredSchema.fields.zipWithIndex.map { case (field, i) => + inputFieldMap.get(field.name) match { + case Some(attr) => + if (typeChangeInfo.containsKey(i)) { + // Type changed - apply appropriate cast + val srcType = typeChangeInfo.get(i).getRight // file type + val dstType = typeChangeInfo.get(i).getLeft // required type + castPrimitiveExpression(attr, srcType, dstType, None) + } else { + // No type change + attr + } + case None => + // Field missing from file, use NULL + Literal(null, field.dataType) + } + } + GenerateUnsafeProjection.generate(expressions, inputAttributes) Review Comment: Feedback from tim: see if we can resue the generate unsafe projection code from our parquet equivalent path -- This is an automated message from the Apache Git Service. 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