Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14155#discussion_r75446103
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveExternalCatalog.scala ---
@@ -200,22 +375,77 @@ private[spark] class HiveExternalCatalog(client:
HiveClient, hadoopConf: Configu
* Alter a table whose name that matches the one specified in
`tableDefinition`,
* assuming the table exists.
*
- * Note: As of now, this only supports altering table properties, serde
properties,
- * and num buckets!
+ * Note: As of now, this doesn't support altering table schema,
partition column names and bucket
+ * specification. We will ignore them even if users do specify different
values for these fields.
*/
override def alterTable(tableDefinition: CatalogTable): Unit =
withClient {
assert(tableDefinition.identifier.database.isDefined)
val db = tableDefinition.identifier.database.get
requireTableExists(db, tableDefinition.identifier.table)
- client.alterTable(tableDefinition)
+ verifyTableProperties(tableDefinition)
+
+ if (tableDefinition.provider == Some("hive") ||
tableDefinition.tableType == VIEW) {
+ client.alterTable(tableDefinition)
+ } else {
+ val oldDef = client.getTable(db, tableDefinition.identifier.table)
+ // Sets the `schema`, `partitionColumnNames` and `bucketSpec` from
the old table definition,
+ // to retain the spark specific format if it is.
+ // Also add table meta properties to table properties, to retain the
data source table format.
+ val newDef = tableDefinition.copy(
+ schema = oldDef.schema,
+ partitionColumnNames = oldDef.partitionColumnNames,
+ bucketSpec = oldDef.bucketSpec,
+ properties = tableMetadataToProperties(tableDefinition) ++
tableDefinition.properties)
+
+ client.alterTable(newDef)
+ }
}
override def getTable(db: String, table: String): CatalogTable =
withClient {
- client.getTable(db, table)
+ restoreTableMetadata(client.getTable(db, table))
}
override def getTableOption(db: String, table: String):
Option[CatalogTable] = withClient {
- client.getTableOption(db, table)
+ client.getTableOption(db, table).map(restoreTableMetadata)
+ }
+
+ /**
+ * Restores table metadata from the table properties if it's a datasouce
table. This method is
+ * kind of a opposite version of [[createTable]].
+ *
+ * It reads table schema, provider, partition column names and bucket
specification from table
+ * properties, and filter out these special entries from table
properties.
+ */
+ private def restoreTableMetadata(table: CatalogTable): CatalogTable = {
+ if (table.tableType == VIEW) {
+ table
+ } else {
+ getProviderFromTableProperties(table).map { provider =>
+ // SPARK-15269: Persisted data source tables always store the
location URI as a storage
+ // property named "path" instead of standard Hive `dataLocation`,
because Hive only
+ // allows directory paths as location URIs while Spark SQL data
source tables also
+ // allows file paths. So the standard Hive `dataLocation` is
meaningless for Spark SQL
+ // data source tables.
+ // Spark SQL may also save external data source in Hive compatible
format when
+ // possible, so that these tables can be directly accessed by
Hive. For these tables,
+ // `dataLocation` is still necessary. Here we also check for input
format because only
+ // these Hive compatible tables set this field.
+ val storage = if (table.tableType == EXTERNAL &&
table.storage.inputFormat.isEmpty) {
+ table.storage.copy(locationUri = None)
+ } else {
+ table.storage
+ }
+ table.copy(
+ storage = storage,
+ schema = getSchemaFromTableProperties(table),
+ provider = Some(provider),
+ partitionColumnNames =
getPartitionColumnsFromTableProperties(table),
+ bucketSpec = getBucketSpecFromTableProperties(table),
+ properties = getOriginalTableProperties(table))
--- End diff --
you can take a look at the SQL syntax for data source table, we can't set
table properties for data source tables currently. But external catalog doesn't
need to make this assumption.
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