yabola commented on code in PR #39950:
URL: https://github.com/apache/spark/pull/39950#discussion_r1143531801
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/parquet/ParquetPartitionReaderFactory.scala:
##########
@@ -88,12 +88,18 @@ case class ParquetPartitionReaderFactory(
private def getFooter(file: PartitionedFile): ParquetMetadata = {
val conf = broadcastedConf.value.value
val filePath = file.toPath
+ val split = new FileSplit(file.toPath, file.start, file.length,
Array.empty[String])
- if (aggregation.isEmpty) {
- ParquetFooterReader.readFooter(conf, filePath, SKIP_ROW_GROUPS)
- } else {
+ if (aggregation.isDefined) {
// For aggregate push down, we will get max/min/count from footer
statistics.
ParquetFooterReader.readFooter(conf, filePath, NO_FILTER)
+ } else if (enableVectorizedReader) {
+ // This can avoid reading the footer twice(currently only optimize for
vectorized read).
+ // Read all the row groups in advance and filter the row groups later if
there are
+ // filters that need push down.
+ ParquetFooterReader.readFooter(conf, split,
ParquetFooterReader.WITH_ROW_GROUPS)
+ } else {
Review Comment:
I think we can use
```java
if (aggregation.isDefined || enableVectorizedReader) {
ParquetFooterReader.readFooter(conf, split,
ParquetFooterReader.WITH_ROW_GROUPS)
}
```
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