codope commented on code in PR #10007:
URL: https://github.com/apache/hudi/pull/10007#discussion_r1385970457
##########
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/NewHoodieParquetFileFormat.scala:
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@@ -74,11 +76,25 @@ class NewHoodieParquetFileFormat(tableState:
Broadcast[HoodieTableState],
override def supportBatch(sparkSession: SparkSession, schema: StructType):
Boolean = {
if (!supportBatchCalled) {
supportBatchCalled = true
- supportBatchResult = !isMOR && super.supportBatch(sparkSession, schema)
+ supportBatchResult = !isMOR && legacyFF.supportBatch(sparkSession,
schema)
}
supportBatchResult
}
+ private def wrapWithBatchConverter(reader: PartitionedFile =>
Iterator[InternalRow]): PartitionedFile => Iterator[InternalRow] = {
Review Comment:
why is this needed? i think the flatmap per row could incur some significant
cost for a large batch. Instead of wrapping everytime, can it be guarded for
some cases such as when schema on read is enabled?
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