yaooqinn commented on a change in pull request #29539:
URL: https://github.com/apache/spark/pull/29539#discussion_r478243790
##########
File path:
sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/SparkMetadataOperationSuite.scala
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@@ -333,4 +333,31 @@ class SparkMetadataOperationSuite extends
HiveThriftJdbcTest {
assert(pos === 17, "all columns should have been verified")
}
}
+
+ test("get columns operation should handle interval column properly") {
+ val viewName = "view_interval"
+ val ddl = s"CREATE GLOBAL TEMP VIEW $viewName as select interval 1 day as
i"
+
+ withJdbcStatement(viewName) { statement =>
+ statement.execute(ddl)
+ val data = statement.getConnection.getMetaData
+ val rowSet = data.getColumns("", "global_temp", viewName, null)
+ while (rowSet.next()) {
+ assert(rowSet.getString("TABLE_CAT") === null)
+ assert(rowSet.getString("TABLE_SCHEM") === "global_temp")
+ assert(rowSet.getString("TABLE_NAME") === viewName)
+ assert(rowSet.getString("COLUMN_NAME") === "i")
+ assert(rowSet.getInt("DATA_TYPE") === java.sql.Types.OTHER)
+
assert(rowSet.getString("TYPE_NAME").equalsIgnoreCase(CalendarIntervalType.sql))
Review comment:
I guess that all the meta operations should do nothing else but
specifically describe how all the objects(database/table /columns etc) stored
in the Spark system.
If we change the column meta here from INTERVAL to STRING, so the column
here becomes orderable and comparable?(JDBC users may guess), they may have no
idea about what they are dealing with and get a completely different awareness
of the meta-information comparing to those users who use spark-sql
self-contained applications.
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