Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/15997#discussion_r89405402
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
---
@@ -133,25 +135,25 @@ case class DataSource(
val partitionSchema = if (partitionColumns.isEmpty &&
catalogTable.isEmpty) {
// Try to infer partitioning, because no DataSource in the read path
provides the partitioning
// columns properly unless it is a Hive DataSource
- val resolved = tempFileCatalog.partitionSchema.map { partitionField
=>
+ val resolved = tempFileIndex.partitionSchema.map { partitionField =>
val equality = sparkSession.sessionState.conf.resolver
// SPARK-18510: try to get schema from userSpecifiedSchema,
otherwise fallback to inferred
userSpecifiedSchema.flatMap(_.find(f => equality(f.name,
partitionField.name))).getOrElse(
partitionField)
}
StructType(resolved)
} else {
- // in streaming mode, we have already inferred and registered
partition columns, we will
- // never have to materialize the lazy val below
- lazy val inferredPartitions = tempFileCatalog.partitionSchema
// maintain old behavior before SPARK-18510. If userSpecifiedSchema
is empty used inferred
// partitioning
if (userSpecifiedSchema.isEmpty) {
+ val inferredPartitions = tempFileIndex.partitionSchema
--- End diff --
Still keep the `inferredPartitions` variable to document the meaning of
`tempFileIndex.partitionSchema`.
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