Avoid show table extended command.

dbt/adapters/databricks/connections.py

@@ -357,6 +357,11 @@ def description(
     def schemas(self, catalog_name: str, schema_name: Optional[str] = None) -> None:
         self._cursor.schemas(catalog_name=catalog_name, schema_name=schema_name)
 
+    def tables(self, catalog_name: str, schema_name: str, table_name: Optional[str] = None) -> None:
+        self._cursor.tables(
+            catalog_name=catalog_name, schema_name=schema_name, table_name=table_name
+        )
+
     def __del__(self) -> None:
         if self._cursor.open:
             # This should not happen. The cursor should explicitly be closed.
@@ -526,6 +531,14 @@ def list_schemas(self, database: str, schema: Optional[str] = None) -> Table:
             lambda cursor: cursor.schemas(catalog_name=database, schema_name=schema),
         )
 
+    def list_tables(self, database: str, schema: str, identifier: Optional[str] = None) -> Table:
+        return self._execute_cursor(
+            f"GetTables(database={database}, schema={schema}, identifier={identifier})",
+            lambda cursor: cursor.tables(
+                catalog_name=database, schema_name=schema, table_name=identifier
+            ),
+        )
+
     @classmethod
     def open(cls, connection: Connection) -> Connection:
         if connection.state == ConnectionState.OPEN:

dbt/adapters/databricks/impl.py

@@ -1,10 +1,9 @@
 from concurrent.futures import Future
 from contextlib import contextmanager
 from dataclasses import dataclass
-import re
-from typing import Any, Dict, Iterable, Iterator, List, Optional, Tuple, Type, Union, cast
+from typing import Any, Dict, Iterable, Iterator, List, Optional, Tuple, Type, Union
 
-from agate import Row, Table
+from agate import Row, Table, Text
 
 from dbt.adapters.base import AdapterConfig, PythonJobHelper
 from dbt.adapters.base.impl import catch_as_completed
@@ -17,7 +16,9 @@
     KEY_TABLE_STATISTICS,
     LIST_RELATIONS_MACRO_NAME,
     LIST_SCHEMAS_MACRO_NAME,
+    TABLE_OR_VIEW_NOT_FOUND_MESSAGES,
 )
+from dbt.clients.agate_helper import empty_table
 from dbt.contracts.connection import AdapterResponse, Connection
 from dbt.contracts.graph.manifest import Manifest
 from dbt.contracts.relation import RelationType
@@ -40,6 +41,9 @@
 CURRENT_CATALOG_MACRO_NAME = "current_catalog"
 USE_CATALOG_MACRO_NAME = "use_catalog"
 
+SHOW_TABLES_MACRO_NAME = "show_tables"
+SHOW_VIEWS_MACRO_NAME = "show_views"
+
 
 @dataclass
 class DatabricksConfig(AdapterConfig):
@@ -113,9 +117,7 @@ def list_relations_without_caching(  # type: ignore[override]
     ) -> List[DatabricksRelation]:
         kwargs = {"schema_relation": schema_relation}
         try:
-            # The catalog for `show table extended` needs to match the current catalog.
-            with self._catalog(schema_relation.database):
-                results = self.execute_macro(LIST_RELATIONS_MACRO_NAME, kwargs=kwargs)
+            results = self.execute_macro(LIST_RELATIONS_MACRO_NAME, kwargs=kwargs)
         except dbt.exceptions.RuntimeException as e:
             errmsg = getattr(e, "msg", "")
             if f"Database '{schema_relation}' not found" in errmsg:
@@ -125,35 +127,79 @@ def list_relations_without_caching(  # type: ignore[override]
                 logger.debug(f"{description} {schema_relation}: {e.msg}")
                 return []
 
-        relations = []
-        for row in results:
-            if len(row) != 4:
-                raise dbt.exceptions.RuntimeException(
-                    f'Invalid value from "show table extended ...", '
-                    f"got {len(row)} values, expected 4"
-                )
-            _schema, name, _, information = row
-            rel_type = RelationType.View if "Type: VIEW" in information else RelationType.Table
-            is_delta = "Provider: delta" in information
-            is_hudi = "Provider: hudi" in information
-            relation = self.Relation.create(
-                database=schema_relation.database,
-                # Use `_schema` retrieved from the cluster to avoid mismatched case
-                # between the profile and the cluster.
-                schema=_schema,
+        return [
+            self.Relation.create(
+                database=database,
+                schema=schema,
                 identifier=name,
-                type=rel_type,
-                information=information,
-                is_delta=is_delta,
-                is_hudi=is_hudi,
+                type=self.Relation.get_relation_type(kind),
+            )
+            for database, schema, name, kind in results.select(
+                ["database_name", "schema_name", "name", "kind"]
+            )
+        ]
+
+    @available.parse(lambda *a, **k: empty_table())
+    def get_relations_without_caching(self, relation: DatabricksRelation) -> Table:
+        kwargs = {"relation": relation}
+
+        new_rows: List[Tuple]
+        if relation.database is not None:
+            assert relation.schema is not None
+            tables = self.connections.list_tables(
+                database=relation.database, schema=relation.schema
             )
-            relations.append(relation)
+            new_rows = [
+                (row["TABLE_CAT"], row["TABLE_SCHEM"], row["TABLE_NAME"], row["TABLE_TYPE"].lower())
+                for row in tables
+            ]
+        else:
+            tables = self.execute_macro(SHOW_TABLES_MACRO_NAME, kwargs=kwargs)
+            new_rows = [
+                (relation.database, row["database"], row["tableName"], "") for row in tables
+            ]
+
+        if any(not row[3] for row in new_rows):
+            with self._catalog(relation.database):
+                views = self.execute_macro(SHOW_VIEWS_MACRO_NAME, kwargs=kwargs)
+
+            view_names = set(views.columns["viewName"].values())
+            new_rows = [
+                (
+                    row[0],
+                    row[1],
+                    row[2],
+                    str(RelationType.View if row[2] in view_names else RelationType.Table),
+                )
+                for row in new_rows
+            ]
+
+        return Table(
+            new_rows,
+            column_names=["database_name", "schema_name", "name", "kind"],
+            column_types=[Text(), Text(), Text(), Text()],
+        )
+
+    def get_relation(
+        self,
+        database: Optional[str],
+        schema: str,
+        identifier: str,
+        *,
+        needs_information: bool = False,
+    ) -> Optional[DatabricksRelation]:
+        cached: Optional[DatabricksRelation] = super(SparkAdapter, self).get_relation(
+            database=database, schema=schema, identifier=identifier
+        )
 
-        return relations
+        if not needs_information:
+            return cached
+
+        return self._set_relation_information(cached) if cached else None
 
     def parse_describe_extended(  # type: ignore[override]
         self, relation: DatabricksRelation, raw_rows: List[Row]
-    ) -> List[DatabricksColumn]:
+    ) -> Tuple[Dict[str, Any], List[DatabricksColumn]]:
         # Convert the Row to a dict
         dict_rows = [dict(zip(row._keys, row._values)) for row in raw_rows]
         # Find the separator between the rows and the metadata provided
@@ -166,7 +212,7 @@ def parse_describe_extended(  # type: ignore[override]
 
         raw_table_stats = metadata.get(KEY_TABLE_STATISTICS)
         table_stats = DatabricksColumn.convert_table_stats(raw_table_stats)
-        return [
+        return metadata, [
             DatabricksColumn(
                 table_database=relation.database,
                 table_schema=relation.schema,
@@ -184,56 +230,47 @@ def parse_describe_extended(  # type: ignore[override]
     def get_columns_in_relation(  # type: ignore[override]
         self, relation: DatabricksRelation
     ) -> List[DatabricksColumn]:
-        columns = []
+        return self._get_updated_relation(relation)[1]
+
+    def _get_updated_relation(
+        self, relation: DatabricksRelation
+    ) -> Tuple[DatabricksRelation, List[DatabricksColumn]]:
         try:
-            rows: List[Row] = self.execute_macro(
+            rows = self.execute_macro(
                 GET_COLUMNS_IN_RELATION_RAW_MACRO_NAME, kwargs={"relation": relation}
             )
-            columns = self.parse_describe_extended(relation, rows)
+            metadata, columns = self.parse_describe_extended(relation, rows)
         except dbt.exceptions.RuntimeException as e:
             # spark would throw error when table doesn't exist, where other
             # CDW would just return and empty list, normalizing the behavior here
             errmsg = getattr(e, "msg", "")
-            if any(
-                msg in errmsg
-                for msg in (
-                    "[TABLE_OR_VIEW_NOT_FOUND]",
-                    "Table or view not found",
-                    "NoSuchTableException",
-                )
-            ):
-                pass
+            found_msgs = (msg in errmsg for msg in TABLE_OR_VIEW_NOT_FOUND_MESSAGES)
+            if any(found_msgs):
+                metadata = None
+                columns = []
             else:
                 raise e
 
         # strip hudi metadata columns.
-        return [x for x in columns if x.name not in self.HUDI_METADATA_COLUMNS]
+        columns = [x for x in columns if x.name not in self.HUDI_METADATA_COLUMNS]
+
+        return (
+            self.Relation.create(
+                database=relation.database,
+                schema=relation.schema,
+                identifier=relation.identifier,
+                type=relation.type,
+                metadata=metadata,
+            ),
+            columns,
+        )
 
-    def parse_columns_from_information(  # type: ignore[override]
-        self, relation: DatabricksRelation
-    ) -> List[DatabricksColumn]:
-        owner_match = re.findall(self.INFORMATION_OWNER_REGEX, cast(str, relation.information))
-        owner = owner_match[0] if owner_match else None
-        matches = re.finditer(self.INFORMATION_COLUMNS_REGEX, cast(str, relation.information))
-        columns = []
-        stats_match = re.findall(self.INFORMATION_STATISTICS_REGEX, cast(str, relation.information))
-        raw_table_stats = stats_match[0] if stats_match else None
-        table_stats = DatabricksColumn.convert_table_stats(raw_table_stats)
-        for match_num, match in enumerate(matches):
-            column_name, column_type, nullable = match.groups()
-            column = DatabricksColumn(
-                table_database=relation.database,
-                table_schema=relation.schema,
-                table_name=relation.table,
-                table_type=relation.type,
-                column_index=(match_num + 1),
-                table_owner=owner,
-                column=column_name,
-                dtype=column_type,
-                table_stats=table_stats,
-            )
-            columns.append(column)
-        return columns
+    def _set_relation_information(self, relation: DatabricksRelation) -> DatabricksRelation:
+        """Update the information of the relation, or return it if it already exists."""
+        if relation.has_information():
+            return relation
+
+        return self._get_updated_relation(relation)[0]
 
     def get_catalog(self, manifest: Manifest) -> Tuple[Table, List[Exception]]:
         schema_map = self._get_catalog_schemas(manifest)
@@ -253,7 +290,7 @@ def get_catalog(self, manifest: Manifest) -> Tuple[Table, List[Exception]]:
     def _get_columns_for_catalog(  # type: ignore[override]
         self, relation: DatabricksRelation
     ) -> Iterable[Dict[str, Any]]:
-        columns = self.parse_columns_from_information(relation)
+        columns = self.get_columns_in_relation(relation)
 
         for column in columns:
             # convert DatabricksRelation into catalog dicts

dbt/adapters/databricks/relation.py

@@ -1,12 +1,22 @@
 from dataclasses import dataclass
-from typing import Any, Dict
+from typing import Any, Dict, Optional
 
-from dbt.adapters.base.relation import Policy
-from dbt.adapters.spark.relation import SparkRelation
+from dbt.adapters.base.relation import BaseRelation, Policy
+from dbt.adapters.spark.impl import KEY_TABLE_OWNER, KEY_TABLE_STATISTICS
 
 from dbt.adapters.databricks.utils import remove_undefined
 
 
+KEY_TABLE_PROVIDER = "Provider"
+
+
+@dataclass
+class DatabricksQuotePolicy(Policy):
+    database: bool = False
+    schema: bool = False
+    identifier: bool = False
+
+
 @dataclass
 class DatabricksIncludePolicy(Policy):
     database: bool = True
@@ -15,8 +25,12 @@ class DatabricksIncludePolicy(Policy):
 
 
 @dataclass(frozen=True, eq=False, repr=False)
-class DatabricksRelation(SparkRelation):
-    include_policy: DatabricksIncludePolicy = DatabricksIncludePolicy()  # type: ignore[assignment]
+class DatabricksRelation(BaseRelation):
+    quote_policy = DatabricksQuotePolicy()
+    include_policy = DatabricksIncludePolicy()
+    quote_character: str = "`"
+
+    metadata: Optional[Dict[str, Any]] = None
 
     @classmethod
     def __pre_deserialize__(cls, data: Dict[Any, Any]) -> Dict[Any, Any]:
@@ -27,8 +41,23 @@ def __pre_deserialize__(cls, data: Dict[Any, Any]) -> Dict[Any, Any]:
             data["path"]["database"] = remove_undefined(data["path"]["database"])
         return data
 
-    def __post_init__(self) -> None:
-        return
+    def has_information(self) -> bool:
+        return self.metadata is not None
+
+    @property
+    def is_delta(self) -> bool:
+        assert self.metadata is not None
+        return self.metadata.get(KEY_TABLE_PROVIDER) == "delta"
+
+    @property
+    def is_hudi(self) -> bool:
+        assert self.metadata is not None
+        return self.metadata.get(KEY_TABLE_PROVIDER) == "hudi"
+
+    @property
+    def owner(self) -> Optional[str]:
+        return self.metadata.get(KEY_TABLE_OWNER) if self.metadata is not None else None
 
-    def render(self) -> str:
-        return super(SparkRelation, self).render()
+    @property
+    def stats(self) -> Optional[str]:
+        return self.metadata.get(KEY_TABLE_STATISTICS) if self.metadata is not None else None