fix(hive): Regression in #21794 (#22794)

superset/db_engine_specs/hive.py

@@ -22,7 +22,7 @@ import re
 import tempfile
 import time
 from datetime import datetime
-from typing import Any, Dict, List, Optional, Tuple, TYPE_CHECKING
+from typing import Any, Dict, List, Optional, Set, Tuple, TYPE_CHECKING
 from urllib import parse
 
 import numpy as np
@@ -576,3 +576,38 @@ class HiveEngineSpec(PrestoEngineSpec):
         """
 
         return True
+
+    @classmethod
+    def get_view_names(
+        cls,
+        database: "Database",
+        inspector: Inspector,
+        schema: Optional[str],
+    ) -> Set[str]:
+        """
+        Get all the view names within the specified schema.
+
+        Per the SQLAlchemy definition if the schema is omitted the database’s default
+        schema is used, however some dialects infer the request as schema agnostic.
+
+        Note that PyHive's Hive SQLAlchemy dialect does not adhere to the specification
+        where the `get_view_names` method returns both real tables and views. Futhermore
+        the dialect wrongfully infers the request as schema agnostic when the schema is
+        omitted.
+
+        :param database: The database to inspect
+        :param inspector: The SQLAlchemy inspector
+        :param schema: The schema to inspect
+        :returns: The view names
+        """
+
+        sql = "SHOW VIEWS"
+
+        if schema:
+            sql += f" IN `{schema}`"
+
+        with database.get_raw_connection(schema=schema) as conn:
+            cursor = conn.cursor()
+            cursor.execute(sql)
+            results = cursor.fetchall()
+            return {row[0] for row in results}

superset/db_engine_specs/presto.py

@@ -638,9 +638,10 @@ class PrestoEngineSpec(PrestoBaseEngineSpec):
         Per the SQLAlchemy definition if the schema is omitted the database’s default
         schema is used, however some dialects infer the request as schema agnostic.
 
-        Note that PyHive's Hive and Presto SQLAlchemy dialects do not implement the
-        `get_view_names` method. To ensure consistency with the `get_table_names` method
-        the request is deemed schema agnostic when the schema is omitted.
+        Note that PyHive's Presto SQLAlchemy dialect does not adhere to the
+        specification as the `get_view_names` method is not defined. Futhermore the
+        dialect wrongfully infers the request as schema agnostic when the schema is
+        omitted.
 
         :param database: The database to inspect
         :param inspector: The SQLAlchemy inspector

tests/integration_tests/db_engine_specs/hive_tests.py

@@ -403,3 +403,41 @@ def test__latest_partition_from_df():
         ["ds=01-01-19/hour=1", "ds=01-03-19/hour=1", "ds=01-02-19/hour=2"],
         ["01-03-19", "1"],
     )
+
+
+def test_get_view_names_with_schema():
+    database = mock.MagicMock()
+    mock_execute = mock.MagicMock()
+    database.get_raw_connection().__enter__().cursor().execute = mock_execute
+    database.get_raw_connection().__enter__().cursor().fetchall = mock.MagicMock(
+        return_value=[["a", "b,", "c"], ["d", "e"]]
+    )
+
+    schema = "schema"
+    result = HiveEngineSpec.get_view_names(database, mock.Mock(), schema)
+    mock_execute.assert_called_once_with(f"SHOW VIEWS IN `{schema}`")
+    assert result == {"a", "d"}
+
+
+def test_get_view_names_without_schema():
+    database = mock.MagicMock()
+    mock_execute = mock.MagicMock()
+    database.get_raw_connection().__enter__().cursor().execute = mock_execute
+    database.get_raw_connection().__enter__().cursor().fetchall = mock.MagicMock(
+        return_value=[["a", "b,", "c"], ["d", "e"]]
+    )
+    result = HiveEngineSpec.get_view_names(database, mock.Mock(), None)
+    mock_execute.assert_called_once_with("SHOW VIEWS")
+    assert result == {"a", "d"}
+
+
+@mock.patch("superset.db_engine_specs.base.BaseEngineSpec.get_table_names")
+@mock.patch("superset.db_engine_specs.hive.HiveEngineSpec.get_view_names")
+def test_get_table_names(
+    mock_get_view_names,
+    mock_get_table_names,
+):
+    mock_get_view_names.return_value = {"view1", "view2"}
+    mock_get_table_names.return_value = {"table1", "table2", "view1", "view2"}
+    tables = HiveEngineSpec.get_table_names(mock.Mock(), mock.Mock(), None)
+    assert tables == {"table1", "table2"}