SEA: Cleanup

src/databricks/sql/backend/sea/backend.py → src/databricks/sql/backend/sea/client.py

@@ -620,7 +620,6 @@ def get_execution_result(
         return SeaResultSet(
             connection=cursor.connection,
             execute_response=execute_response,
-            sea_client=self,
             result_data=response.result,
             manifest=response.manifest,
             buffer_size_bytes=cursor.buffer_size_bytes,

src/databricks/sql/backend/sea/queue.py

@@ -3,7 +3,7 @@
 from abc import ABC
 from typing import List, Optional, Tuple
 
-from databricks.sql.backend.sea.backend import SeaDatabricksClient
+from databricks.sql.backend.sea.client import SeaDatabricksClient
 from databricks.sql.backend.sea.models.base import ResultData, ResultManifest
 from databricks.sql.backend.sea.utils.constants import ResultFormat
 from databricks.sql.exc import ProgrammingError

src/databricks/sql/backend/sea/result_set.py

@@ -4,7 +4,7 @@
 
 import logging
 
-from databricks.sql.backend.sea.backend import SeaDatabricksClient
+from databricks.sql.backend.sea.client import SeaDatabricksClient
 from databricks.sql.backend.sea.models.base import ResultData, ResultManifest
 from databricks.sql.backend.sea.utils.conversion import SqlTypeConverter
 
@@ -31,7 +31,6 @@ def __init__(
         self,
         connection: Connection,
         execute_response: ExecuteResponse,
-        sea_client: SeaDatabricksClient,
         result_data: ResultData,
         manifest: ResultManifest,
         buffer_size_bytes: int = 104857600,
@@ -43,7 +42,6 @@ def __init__(
         Args:
             connection: The parent connection
             execute_response: Response from the execute command
-            sea_client: The SeaDatabricksClient instance for direct access
             buffer_size_bytes: Buffer size for fetching results
             arraysize: Default number of rows to fetch
             result_data: Result data from SEA response
@@ -56,32 +54,38 @@ def __init__(
         if statement_id is None:
             raise ValueError("Command ID is not a SEA statement ID")
 
-        results_queue = SeaResultSetQueueFactory.build_queue(
-            result_data,
-            self.manifest,
-            statement_id,
-            description=execute_response.description,
-            max_download_threads=sea_client.max_download_threads,
-            sea_client=sea_client,
-            lz4_compressed=execute_response.lz4_compressed,
-        )
-
         # Call parent constructor with common attributes
         super().__init__(
             connection=connection,
-            backend=sea_client,
             arraysize=arraysize,
             buffer_size_bytes=buffer_size_bytes,
             command_id=execute_response.command_id,
             status=execute_response.status,
             has_been_closed_server_side=execute_response.has_been_closed_server_side,
-            results_queue=results_queue,
             description=execute_response.description,
             is_staging_operation=execute_response.is_staging_operation,
             lz4_compressed=execute_response.lz4_compressed,
             arrow_schema_bytes=execute_response.arrow_schema_bytes,
         )
 
+        # Assert that the backend is of the correct type
+        assert isinstance(
+            self.backend, SeaDatabricksClient
+        ), "Backend must be a SeaDatabricksClient"
+
+        results_queue = SeaResultSetQueueFactory.build_queue(
+            result_data,
+            self.manifest,
+            statement_id,
+            description=execute_response.description,
+            max_download_threads=self.backend.max_download_threads,
+            sea_client=self.backend,
+            lz4_compressed=execute_response.lz4_compressed,
+        )
+
+        # Set the results queue
+        self.results = results_queue
+
     def _convert_json_types(self, row: List[str]) -> List[Any]:
         """
         Convert string values in the row to appropriate Python types based on column metadata.
@@ -160,6 +164,9 @@ def fetchmany_json(self, size: int) -> List[List[str]]:
         if size < 0:
             raise ValueError(f"size argument for fetchmany is {size} but must be >= 0")
 
+        if self.results is None:
+            raise RuntimeError("Results queue is not initialized")
+
         results = self.results.next_n_rows(size)
         self._next_row_index += len(results)
 
@@ -173,6 +180,9 @@ def fetchall_json(self) -> List[List[str]]:
             Columnar table containing all remaining rows
         """
 
+        if self.results is None:
+            raise RuntimeError("Results queue is not initialized")
+
         results = self.results.remaining_rows()
         self._next_row_index += len(results)
 

src/databricks/sql/backend/sea/utils/filters.py

@@ -12,14 +12,13 @@
     Optional,
     Any,
     Callable,
-    cast,
     TYPE_CHECKING,
 )
 
 if TYPE_CHECKING:
     from databricks.sql.backend.sea.result_set import SeaResultSet
 
-from databricks.sql.backend.types import ExecuteResponse
+from databricks.sql.backend.types import ExecuteResponse, CommandId, CommandState
 
 logger = logging.getLogger(__name__)
 
@@ -45,6 +44,9 @@ def _filter_sea_result_set(
         """
 
         # Get all remaining rows
+        if result_set.results is None:
+            raise RuntimeError("Results queue is not initialized")
+
         all_rows = result_set.results.remaining_rows()
 
         # Filter rows
@@ -69,7 +71,7 @@ def _filter_sea_result_set(
 
         result_data = ResultData(data=filtered_rows, external_links=None)
 
-        from databricks.sql.backend.sea.backend import SeaDatabricksClient
+        from databricks.sql.backend.sea.client import SeaDatabricksClient
         from databricks.sql.backend.sea.result_set import SeaResultSet
 
         # Create a new SeaResultSet with the filtered data
@@ -79,7 +81,6 @@ def _filter_sea_result_set(
         filtered_result_set = SeaResultSet(
             connection=result_set.connection,
             execute_response=execute_response,
-            sea_client=cast(SeaDatabricksClient, result_set.backend),
             result_data=result_data,
             manifest=manifest,
             buffer_size_bytes=result_set.buffer_size_bytes,

src/databricks/sql/backend/thrift_backend.py

@@ -856,7 +856,6 @@ def get_execution_result(
         return ThriftResultSet(
             connection=cursor.connection,
             execute_response=execute_response,
-            thrift_client=self,
             buffer_size_bytes=cursor.buffer_size_bytes,
             arraysize=cursor.arraysize,
             use_cloud_fetch=cursor.connection.use_cloud_fetch,
@@ -987,7 +986,6 @@ def execute_command(
             return ThriftResultSet(
                 connection=cursor.connection,
                 execute_response=execute_response,
-                thrift_client=self,
                 buffer_size_bytes=max_bytes,
                 arraysize=max_rows,
                 use_cloud_fetch=use_cloud_fetch,
@@ -1027,7 +1025,6 @@ def get_catalogs(
         return ThriftResultSet(
             connection=cursor.connection,
             execute_response=execute_response,
-            thrift_client=self,
             buffer_size_bytes=max_bytes,
             arraysize=max_rows,
             use_cloud_fetch=cursor.connection.use_cloud_fetch,
@@ -1071,7 +1068,6 @@ def get_schemas(
         return ThriftResultSet(
             connection=cursor.connection,
             execute_response=execute_response,
-            thrift_client=self,
             buffer_size_bytes=max_bytes,
             arraysize=max_rows,
             use_cloud_fetch=cursor.connection.use_cloud_fetch,
@@ -1119,7 +1115,6 @@ def get_tables(
         return ThriftResultSet(
             connection=cursor.connection,
             execute_response=execute_response,
-            thrift_client=self,
             buffer_size_bytes=max_bytes,
             arraysize=max_rows,
             use_cloud_fetch=cursor.connection.use_cloud_fetch,
@@ -1167,7 +1162,6 @@ def get_columns(
         return ThriftResultSet(
             connection=cursor.connection,
             execute_response=execute_response,
-            thrift_client=self,
             buffer_size_bytes=max_bytes,
             arraysize=max_rows,
             use_cloud_fetch=cursor.connection.use_cloud_fetch,

src/databricks/sql/result_set.py

@@ -20,6 +20,7 @@
 from databricks.sql.utils import (
     ColumnTable,
     ColumnQueue,
+    ResultSetQueue,
 )
 from databricks.sql.backend.types import CommandId, CommandState, ExecuteResponse
 
@@ -36,14 +37,12 @@ class ResultSet(ABC):
     def __init__(
         self,
         connection: "Connection",
-        backend: "DatabricksClient",
         arraysize: int,
         buffer_size_bytes: int,
         command_id: CommandId,
         status: CommandState,
         has_been_closed_server_side: bool = False,
         is_direct_results: bool = False,
-        results_queue=None,
         description: List[Tuple] = [],
         is_staging_operation: bool = False,
         lz4_compressed: bool = False,
@@ -54,32 +53,30 @@ def __init__(
 
         Parameters:
             :param connection: The parent connection
-            :param backend: The backend client
             :param arraysize: The max number of rows to fetch at a time (PEP-249)
             :param buffer_size_bytes: The size (in bytes) of the internal buffer + max fetch
             :param command_id: The command ID
             :param status: The command status
             :param has_been_closed_server_side: Whether the command has been closed on the server
             :param is_direct_results: Whether the command has more rows
-            :param results_queue: The results queue
             :param description: column description of the results
             :param is_staging_operation: Whether the command is a staging operation
         """
 
-        self.connection = connection
-        self.backend = backend
-        self.arraysize = arraysize
-        self.buffer_size_bytes = buffer_size_bytes
-        self._next_row_index = 0
-        self.description = description
-        self.command_id = command_id
-        self.status = status
-        self.has_been_closed_server_side = has_been_closed_server_side
-        self.is_direct_results = is_direct_results
-        self.results = results_queue
-        self._is_staging_operation = is_staging_operation
-        self.lz4_compressed = lz4_compressed
-        self._arrow_schema_bytes = arrow_schema_bytes
+        self.connection: "Connection" = connection
+        self.backend: DatabricksClient = connection.session.backend
+        self.arraysize: int = arraysize
+        self.buffer_size_bytes: int = buffer_size_bytes
+        self._next_row_index: int = 0
+        self.description: List[Tuple] = description
+        self.command_id: CommandId = command_id
+        self.status: CommandState = status
+        self.has_been_closed_server_side: bool = has_been_closed_server_side
+        self.is_direct_results: bool = is_direct_results
+        self.results: Optional[ResultSetQueue] = None  # Children will set this
+        self._is_staging_operation: bool = is_staging_operation
+        self.lz4_compressed: bool = lz4_compressed
+        self._arrow_schema_bytes: Optional[bytes] = arrow_schema_bytes
 
     def __iter__(self):
         while True:
@@ -190,7 +187,6 @@ def __init__(
         self,
         connection: "Connection",
         execute_response: "ExecuteResponse",
-        thrift_client: "ThriftDatabricksClient",
         buffer_size_bytes: int = 104857600,
         arraysize: int = 10000,
         use_cloud_fetch: bool = True,
@@ -205,7 +201,6 @@ def __init__(
         Parameters:
             :param connection: The parent connection
             :param execute_response: Response from the execute command
-            :param thrift_client: The ThriftDatabricksClient instance for direct access
             :param buffer_size_bytes: Buffer size for fetching results
             :param arraysize: Default number of rows to fetch
             :param use_cloud_fetch: Whether to use cloud fetch for retrieving results
@@ -238,20 +233,28 @@ def __init__(
         # Call parent constructor with common attributes
         super().__init__(
             connection=connection,
-            backend=thrift_client,
             arraysize=arraysize,
             buffer_size_bytes=buffer_size_bytes,
             command_id=execute_response.command_id,
             status=execute_response.status,
             has_been_closed_server_side=execute_response.has_been_closed_server_side,
             is_direct_results=is_direct_results,
-            results_queue=results_queue,
             description=execute_response.description,
             is_staging_operation=execute_response.is_staging_operation,
             lz4_compressed=execute_response.lz4_compressed,
             arrow_schema_bytes=execute_response.arrow_schema_bytes,
         )
 
+        # Assert that the backend is of the correct type
+        from databricks.sql.backend.thrift_backend import ThriftDatabricksClient
+
+        assert isinstance(
+            self.backend, ThriftDatabricksClient
+        ), "Backend must be a ThriftDatabricksClient"
+
+        # Set the results queue
+        self.results = results_queue
+
         # Initialize results queue if not provided
         if not self.results:
             self._fill_results_buffer()
@@ -307,6 +310,10 @@ def fetchmany_arrow(self, size: int) -> "pyarrow.Table":
         """
         if size < 0:
             raise ValueError("size argument for fetchmany is %s but must be >= 0", size)
+
+        if self.results is None:
+            raise RuntimeError("Results queue is not initialized")
+
         results = self.results.next_n_rows(size)
         n_remaining_rows = size - results.num_rows
         self._next_row_index += results.num_rows
@@ -332,6 +339,9 @@ def fetchmany_columnar(self, size: int):
         if size < 0:
             raise ValueError("size argument for fetchmany is %s but must be >= 0", size)
 
+        if self.results is None:
+            raise RuntimeError("Results queue is not initialized")
+
         results = self.results.next_n_rows(size)
         n_remaining_rows = size - results.num_rows
         self._next_row_index += results.num_rows
@@ -351,6 +361,9 @@ def fetchmany_columnar(self, size: int):
 
     def fetchall_arrow(self) -> "pyarrow.Table":
         """Fetch all (remaining) rows of a query result, returning them as a PyArrow table."""
+        if self.results is None:
+            raise RuntimeError("Results queue is not initialized")
+
         results = self.results.remaining_rows()
         self._next_row_index += results.num_rows
 
@@ -377,6 +390,9 @@ def fetchall_arrow(self) -> "pyarrow.Table":
 
     def fetchall_columnar(self):
         """Fetch all (remaining) rows of a query result, returning them as a Columnar table."""
+        if self.results is None:
+            raise RuntimeError("Results queue is not initialized")
+
         results = self.results.remaining_rows()
         self._next_row_index += results.num_rows
 
@@ -393,6 +409,9 @@ def fetchone(self) -> Optional[Row]:
         Fetch the next row of a query result set, returning a single sequence,
         or None when no more data is available.
         """
+        if self.results is None:
+            raise RuntimeError("Results queue is not initialized")
+
         if isinstance(self.results, ColumnQueue):
             res = self._convert_columnar_table(self.fetchmany_columnar(1))
         else:

src/databricks/sql/session.py

@@ -8,7 +8,7 @@
 from databricks.sql import __version__
 from databricks.sql import USER_AGENT_NAME
 from databricks.sql.backend.thrift_backend import ThriftDatabricksClient
-from databricks.sql.backend.sea.backend import SeaDatabricksClient
+from databricks.sql.backend.sea.client import SeaDatabricksClient
 from databricks.sql.backend.databricks_client import DatabricksClient
 from databricks.sql.backend.types import SessionId, BackendType
 

src/databricks/sql/utils.py

@@ -13,7 +13,7 @@
 
 import lz4.frame
 
-from databricks.sql.backend.sea.backend import SeaDatabricksClient
+from databricks.sql.backend.sea.client import SeaDatabricksClient
 from databricks.sql.backend.sea.models.base import ResultData, ResultManifest
 
 try: