Alias database to allow matching between rows and Manifest

Currently the docs generation is broken because we need to supply
the database name when fetching the relations:

if dct['table_database'] is None:
    dct['table_database'] = dct['table_schema']

However, when we get the manifest we don't get the database:

{CatalogKey(database='', schema='fokko', name='logistical_configuration_data'):
	['model.dbtlake.logistical_configuration_data']}

Therefore the keys never line up, and we can't match the Catalogs:

https://github.com/fishtown-analytics/dbt/blob/9d0eab630511723cd0bc328f6f11d3ffe6c8f879/core/dbt/task/generate.py#L108

We get from the describe relations:

CatalogKey(database='fokko', schema='fokko', name='logistical_configuration_data')

Due to the logic above.

dbt/adapters/spark/connections.py

@@ -40,6 +40,9 @@ class SparkCredentials(Credentials):
  organization: str = '0'
  connect_retries: int = 0
  connect_timeout: int = 10
+ _ALIASES = {
+ 'database': 'schema'
+ }
 
  def __post_init__(self):
  # spark classifies database and schema as the same thing

dbt/adapters/spark/impl.py

@@ -3,7 +3,7 @@
 import agate
 import dbt.exceptions
 import dbt
-from dbt.adapters.base.relation import SchemaSearchMap
+from dbt.adapters.base.relation import SchemaSearchMap, RelationType
 from dbt.adapters.sql import SQLAdapter
 from dbt.node_types import NodeType
 
@@ -117,7 +117,8 @@ def list_relations_without_caching(
 
  relations = []
  for _schema, name, _, information in results:
- rel_type = ('view' if 'Type: VIEW' in information else 'table')
+ rel_type = (RelationType.View
+ if 'Type: VIEW' in information else RelationType.Table)
  relation = self.Relation.create(
  schema=_schema,
  identifier=name,
@@ -132,7 +133,6 @@ def get_relation(
  ) -> Optional[BaseRelation]:
  if not self.Relation.include_policy.database:
  database = None
-
  return super().get_relation(database, schema, identifier)
 
  def parse_describe_extended(
@@ -256,9 +256,8 @@ def _parse_relation(relation: Relation,
 
  return columns
 
- def _massage_column_for_catalog(
- self, column: SparkColumn
- ) -> Dict[str, Any]:
+ @staticmethod
+ def _massage_column_for_catalog(column: SparkColumn) -> Dict[str, Any]:
  dct = column.to_dict()
  # different expectations here - Column.column is the name
  dct['column_name'] = dct.pop('column')
@@ -279,7 +278,7 @@ def _get_catalog_for_relations(self, database: str, schema: str):
  )
  return agate.Table.from_object(columns)
 
- def _get_cache_schemas(self, manifest, exec_only=False):
+ def _get_cache_schemas(self, manifest, exec_only=False) -> SchemaSearchMap:
  info_schema_name_map = SchemaSearchMap()
  for node in manifest.nodes.values():
  if exec_only and node.resource_type not in NodeType.executable():