[SPARK-19611][SQL][FOLLOWUP] set dataSchema correctly in HiveMetastoreCatalog.convertToLogicalRelation

We made a mistake in #16944 . In `HiveMetastoreCatalog#inferIfNeeded` we infer the data schema, merge with full schema, and return the new full schema. At caller side we treat the full schema as data schema and set it to `HadoopFsRelation`.

This doesn't cause any problem because both parquet and orc can work with a wrong data schema that has extra columns, but it's better to fix this mistake.

N/A

Author: Wenchen Fan <wenchen@databricks.com>

Closes #19615 from cloud-fan/infer.

(cherry picked from commit 4d9ebf3)
Signed-off-by: Wenchen Fan <wenchen@databricks.com>

Author: cloud-fan

sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala

@@ -164,13 +164,12 @@ private[hive] class HiveMetastoreCatalog(sparkSession: SparkSession) extends Log
             }
           }
 
-          val (dataSchema, updatedTable) =
-            inferIfNeeded(relation, options, fileFormat, Option(fileIndex))
+          val updatedTable = inferIfNeeded(relation, options, fileFormat, Option(fileIndex))
 
           val fsRelation = HadoopFsRelation(
             location = fileIndex,
             partitionSchema = partitionSchema,
-            dataSchema = dataSchema,
+            dataSchema = updatedTable.dataSchema,
             // We don't support hive bucketed tables, only ones we write out.
             bucketSpec = None,
             fileFormat = fileFormat,
@@ -192,13 +191,13 @@ private[hive] class HiveMetastoreCatalog(sparkSession: SparkSession) extends Log
           fileFormatClass,
           None)
         val logicalRelation = cached.getOrElse {
-          val (dataSchema, updatedTable) = inferIfNeeded(relation, options, fileFormat)
+          val updatedTable = inferIfNeeded(relation, options, fileFormat)
           val created =
             LogicalRelation(
               DataSource(
                 sparkSession = sparkSession,
                 paths = rootPath.toString :: Nil,
-                userSpecifiedSchema = Option(dataSchema),
+                userSpecifiedSchema = Option(updatedTable.dataSchema),
                 // We don't support hive bucketed tables, only ones we write out.
                 bucketSpec = None,
                 options = options,
@@ -226,7 +225,7 @@ private[hive] class HiveMetastoreCatalog(sparkSession: SparkSession) extends Log
       relation: HiveTableRelation,
       options: Map[String, String],
       fileFormat: FileFormat,
-      fileIndexOpt: Option[FileIndex] = None): (StructType, CatalogTable) = {
+      fileIndexOpt: Option[FileIndex] = None): CatalogTable = {
     val inferenceMode = sparkSession.sessionState.conf.caseSensitiveInferenceMode
     val shouldInfer = (inferenceMode != NEVER_INFER) && !relation.tableMeta.schemaPreservesCase
     val tableName = relation.tableMeta.identifier.unquotedString
@@ -243,21 +242,22 @@ private[hive] class HiveMetastoreCatalog(sparkSession: SparkSession) extends Log
           sparkSession,
           options,
           fileIndex.listFiles(Nil, Nil).flatMap(_.files))
-        .map(mergeWithMetastoreSchema(relation.tableMeta.schema, _))
+        .map(mergeWithMetastoreSchema(relation.tableMeta.dataSchema, _))
 
       inferredSchema match {
-        case Some(schema) =>
+        case Some(dataSchema) =>
+          val schema = StructType(dataSchema ++ relation.tableMeta.partitionSchema)
           if (inferenceMode == INFER_AND_SAVE) {
             updateCatalogSchema(relation.tableMeta.identifier, schema)
           }
-          (schema, relation.tableMeta.copy(schema = schema))
+          relation.tableMeta.copy(schema = schema)
         case None =>
           logWarning(s"Unable to infer schema for table $tableName from file format " +
             s"$fileFormat (inference mode: $inferenceMode). Using metastore schema.")
-          (relation.tableMeta.schema, relation.tableMeta)
+          relation.tableMeta
       }
     } else {
-      (relation.tableMeta.schema, relation.tableMeta)
+      relation.tableMeta
     }
   }