LuciferYang commented on a change in pull request #33748:
URL: https://github.com/apache/spark/pull/33748#discussion_r690882533
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/orc/OrcPartitionReaderFactory.scala
##########
@@ -60,6 +60,7 @@ case class OrcPartitionReaderFactory(
private val capacity = sqlConf.orcVectorizedReaderBatchSize
private val orcFilterPushDown = sqlConf.orcFilterPushDown
private val ignoreCorruptFiles = sqlConf.ignoreCorruptFiles
+ private val metaCacheEnabled = sqlConf.fileMetaCacheEnabled
Review comment:
> BTW, @viirya 's suggestion about the config is a list config like
spark.sql.sources.useV1SourceList.
@dongjoon-hyun @viirya
If `useFileMetaCacheList` config is used, without change the V2 API, it
seems that it can only be hard coded as
```
val metaCacheEnabled = useFileMetaCacheList.toLowerCase(Locale.ROOT)
.split(",").map(_.trim).contains("ORC")
```
the `formatName("ORC")` is defined `OrcTable`, we can't get it through the
API here at present.
On the other hand, this config will not have corresponding implementations
for all build-in data format like `spark.sql.sources.useV1SourceList`, if the
new data format is not considered, it may only work for `Parquet` and `Orc`,
so are we sure we need to use a list config?
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