Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/13701#discussion_r73774422
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.scala
---
@@ -199,6 +209,19 @@ private[sql] case class FileSourceScanExec(
options = relation.options,
hadoopConf =
relation.sparkSession.sessionState.newHadoopConfWithOptions(relation.options))
+ (file: PartitionedFile) => {
+ val iter = func(file)
+ // Only for test purpose.
+ // Once the vectorized Parquet reader is initialized in the above
method, we can read its
+ // variable numRowGroups.
+ if (fileFormat != null) {
--- End diff --
hmm, VectorizedParquetRecordReader is not exposed to outside of
ParquetFileFormat. It is wrapped in a returned anonymous function that takes a
PartitionedFile and read data from it. In order to pass it to
VectorizedParquetRecordReader, we might need to change current API of
FileFormat. Is it worth doing that for this?
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