jonvex commented on code in PR #10957: URL: https://github.com/apache/hudi/pull/10957#discussion_r1571152424
########## hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/HoodieFileGroupReaderBasedParquetFileFormat.scala: ########## @@ -107,19 +112,23 @@ class HoodieFileGroupReaderBasedParquetFileFormat(tableState: HoodieTableState, val dataSchema = StructType(tableSchema.structTypeSchema.fields.filterNot(f => partitionColumns.contains(f.name))) val outputSchema = StructType(requiredSchema.fields ++ partitionSchema.fields) spark.conf.set("spark.sql.parquet.enableVectorizedReader", supportBatchResult) - val requiredSchemaWithMandatory = generateRequiredSchemaWithMandatory(requiredSchema, dataSchema, partitionSchema) - val isCount = requiredSchemaWithMandatory.isEmpty - val requiredSchemaSplits = requiredSchemaWithMandatory.fields.partition(f => HoodieRecord.HOODIE_META_COLUMNS_WITH_OPERATION.contains(f.name)) - val requiredMeta = StructType(requiredSchemaSplits._1) - val requiredWithoutMeta = StructType(requiredSchemaSplits._2) + val isCount = requiredSchema.isEmpty && !isMOR && !isIncremental val augmentedHadoopConf = FSUtils.buildInlineConf(hadoopConf) - val (baseFileReader, preMergeBaseFileReader, readerMaps, cdcFileReader) = buildFileReaders( - spark, dataSchema, partitionSchema, requiredSchema, filters, options, augmentedHadoopConf, - requiredSchemaWithMandatory, requiredWithoutMeta, requiredMeta) + setSchemaEvolutionConfigs(augmentedHadoopConf, options) + val baseFileReader = super.buildReaderWithPartitionValues(spark, dataSchema, partitionSchema, requiredSchema, + filters ++ requiredFilters, options, new Configuration(augmentedHadoopConf)) + val cdcFileReader = super.buildReaderWithPartitionValues( + spark, + tableSchema.structTypeSchema, + StructType(Nil), + tableSchema.structTypeSchema, + Nil, + options, + new Configuration(hadoopConf)) val requestedAvroSchema = AvroConversionUtils.convertStructTypeToAvroSchema(requiredSchema, sanitizedTableName) val dataAvroSchema = AvroConversionUtils.convertStructTypeToAvroSchema(dataSchema, sanitizedTableName) - + val parquetFileReader = spark.sparkContext.broadcast(sparkAdapter.createParquetFileReader(supportBatchResult, spark.sessionState.conf, options, augmentedHadoopConf)) Review Comment: No. The spark confs don't make it to the executors if you remember. Instantiating the reader just gets the value of the configs we need so that we can send them to the executor. -- 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. To unsubscribe, e-mail: commits-unsubscr...@hudi.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org