Support new error messages. (#226)

### Description

Supports new error messages.

In `SparkAdapter.get_columns_in_relation`, it checks the error message when the specified table or view doesn't exist:

https://github.com/dbt-labs/dbt-spark/blob/c87b6b2c48bcefb0ce52cd64984d3129d6f14ea0/dbt/adapters/spark/impl.py#L223

but, Spark will change the error message in the future release (apache/spark#37887), which causes the function to raise the `dbt.exceptions.RuntimeException` instead of returning an empty list.

The function should also check whether the error message contains `[TABLE_OR_VIEW_NOT_FOUND]` or not.

This will be reverted once dbt-labs/dbt-spark#515 is resolved.

dbt/adapters/databricks/impl.py

@@ -11,6 +11,7 @@
 from dbt.adapters.base.relation import BaseRelation
 from dbt.adapters.spark.impl import (
     SparkAdapter,
+    GET_COLUMNS_IN_RELATION_RAW_MACRO_NAME,
     KEY_TABLE_OWNER,
     KEY_TABLE_STATISTICS,
     LIST_RELATIONS_MACRO_NAME,
@@ -162,6 +163,48 @@ def parse_describe_extended(
             for idx, column in enumerate(rows)
         ]
 
+    def get_columns_in_relation(self, relation: DatabricksRelation) -> List[DatabricksColumn]:
+        cached_relations = self.cache.get_relations(relation.database, relation.schema)
+        cached_relation = next(
+            (
+                cached_relation
+                for cached_relation in cached_relations
+                if str(cached_relation) == str(relation)
+            ),
+            None,
+        )
+        columns = []
+        if cached_relation and cached_relation.information:
+            columns = self.parse_columns_from_information(cached_relation)
+        if not columns:
+            # in open source delta 'show table extended' query output doesnt
+            # return relation's schema. if columns are empty from cache,
+            # use get_columns_in_relation spark macro
+            # which would execute 'describe extended tablename' query
+            try:
+                rows: List[Row] = self.execute_macro(
+                    GET_COLUMNS_IN_RELATION_RAW_MACRO_NAME, kwargs={"relation": relation}
+                )
+                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
+                else:
+                    raise e
+
+        # strip hudi metadata columns.
+        return [x for x in columns if x.name not in self.HUDI_METADATA_COLUMNS]
+
     def parse_columns_from_information(
         self, relation: DatabricksRelation
     ) -> List[DatabricksColumn]: