Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/14207#discussion_r73968228
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/command/createDataSourceTables.scala
---
@@ -95,17 +95,39 @@ case class CreateDataSourceTableCommand(
}
// Create the relation to validate the arguments before writing the
metadata to the metastore.
- DataSource(
- sparkSession = sparkSession,
- userSpecifiedSchema = userSpecifiedSchema,
- className = provider,
- bucketSpec = None,
- options = optionsWithPath).resolveRelation(checkPathExist = false)
+ val dataSource: BaseRelation =
+ DataSource(
+ sparkSession = sparkSession,
+ userSpecifiedSchema = userSpecifiedSchema,
+ className = provider,
+ bucketSpec = None,
+ options = optionsWithPath).resolveRelation(checkPathExist = false)
+
+ val partitionColumns = if (userSpecifiedSchema.nonEmpty) {
+ userSpecifiedPartitionColumns
+ } else {
+ val res = dataSource match {
+ case r: HadoopFsRelation => r.partitionSchema.fieldNames
+ case _ => Array.empty[String]
+ }
+ if (userSpecifiedPartitionColumns.length > 0) {
+ // The table does not have a specified schema, which means that
the schema will be inferred
+ // when we load the table. So, we are not expecting partition
columns and we will discover
+ // partitions when we load the table. However, if there are
specified partition columns,
+ // we simply ignore them and provide a warning message.
+ logWarning(
+ s"Specified partition columns
(${userSpecifiedPartitionColumns.mkString(",")}) will be " +
+ s"ignored. The schema and partition columns of table
$tableIdent are inferred. " +
+ s"Schema: ${dataSource.schema.simpleString}; " +
+ s"Partition columns: ${res.mkString("(", ", ", ")")}")
+ }
+ res
+ }
CreateDataSourceTableUtils.createDataSourceTable(
sparkSession = sparkSession,
tableIdent = tableIdent,
- userSpecifiedSchema = userSpecifiedSchema,
+ schema = dataSource.schema,
--- End diff --
Here, `dataSource.schema` could be inferred. Previously, we do not store
the inferred schema. After this PR, we did and thus we use `dataSource.schema`.
Actually, after re-checking the code, I found the schema might be adjusted
a little even if users specify the schema. For example, the nullability could
be changed :
https://github.com/apache/spark/blob/64529b186a1c33740067cc7639d630bc5b9ae6e8/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala#L407
I think we should make such a change but maybe we should test and log it?
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