yihua commented on code in PR #10007:
URL: https://github.com/apache/hudi/pull/10007#discussion_r1386080312
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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:
Right. @jonvex I think Spark internally handles the batch processing
(`InternalRow` vs `ColumnarBatch`) based on the boolean `supportBatch` returns.
So we don't have to do batch converter here?
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