Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/12047#discussion_r58415966
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala ---
@@ -175,10 +175,11 @@ private[sql] case class DataSourceScan(
}
private def canProcessBatches(): Boolean = {
+ lazy val conf = SQLContext.getActive().get.conf
relation match {
case r: HadoopFsRelation if r.fileFormat.isInstanceOf[ParquetSource]
&&
-
SQLContext.getActive().get.conf.getConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED)
&&
-
SQLContext.getActive().get.conf.getConf(SQLConf.WHOLESTAGE_CODEGEN_ENABLED) =>
+ conf.parquetVectorizedReaderEnabled &&
+ conf.wholeStageEnabled && schema.length <=
conf.wholeStageMaxNumFields =>
--- End diff --
We really need to move all of this logic into the planner. I don't think
it would be that hard after the refactoring we did.
I think main complication is that the parquet reader only supports a subset
of possible schemata. So you have to branch based both on the format but also
arbitrary functions of the schema.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
