Github user mallman commented on a diff in the pull request:
https://github.com/apache/spark/pull/22905#discussion_r233175025
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.scala
---
@@ -306,7 +306,15 @@ case class FileSourceScanExec(
withOptPartitionCount
}
- withSelectedBucketsCount
+ val withOptColumnCount = relation.fileFormat match {
+ case columnar: ColumnarFileFormat =>
+ val sqlConf = relation.sparkSession.sessionState.conf
+ val columnCount = columnar.columnCountForSchema(sqlConf,
requiredSchema)
+ withSelectedBucketsCount + ("ColumnCount" -> columnCount.toString)
--- End diff --
I'll reiterate a sample use case:
> Consider also the case of the beeline user connecting to a multiuser
thriftserver. They are pretty far from the log file, whereas running an
'explain' is right there in the terminal.
This also matters to users planning/debugging queries in a Jupyter
notebook, as we have in VideoAmp. The LOE for these users to go to a driver log
file is quite high by comparison to inspecting a query plan.
When you refer to logging, which log are you referring to? When would this
information be logged? And at what log level?
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