Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/18849#discussion_r131700138
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala ---
@@ -611,21 +640,39 @@ private[spark] class HiveExternalCatalog(conf:
SparkConf, hadoopConf: Configurat
override def alterTableSchema(db: String, table: String, schema:
StructType): Unit = withClient {
requireTableExists(db, table)
val rawTable = getRawTable(db, table)
- val withNewSchema = rawTable.copy(schema = schema)
- verifyColumnNames(withNewSchema)
// Add table metadata such as table schema, partition columns, etc. to
table properties.
- val updatedTable = withNewSchema.copy(
- properties = withNewSchema.properties ++
tableMetaToTableProps(withNewSchema))
- try {
- client.alterTable(updatedTable)
- } catch {
- case NonFatal(e) =>
- val warningMessage =
- s"Could not alter schema of table
${rawTable.identifier.quotedString} in a Hive " +
- "compatible way. Updating Hive metastore in Spark SQL specific
format."
- logWarning(warningMessage, e)
- client.alterTable(updatedTable.copy(schema =
updatedTable.partitionSchema))
+ val updatedProperties = rawTable.properties ++
tableMetaToTableProps(rawTable, schema)
+
+ // Detect whether this is a Hive-compatible table.
+ val provider = rawTable.properties.get(DATASOURCE_PROVIDER)
+ val isHiveCompatible = if (provider.isDefined && provider !=
Some(DDLUtils.HIVE_PROVIDER)) {
--- End diff --
+1, since we still need to handle the case without the special flag for old
spark versions, it makes more sense to just detect hive compatibility by
comparing the row table schema and the table schema from table properties.
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