Reformatted

databricks_sql_connector_core/src/databricks/sql/client.py

@@ -43,6 +43,10 @@
     TSparkParameter,
 )
 
+try:
+    import pyarrow
+except ImportError:
+    pyarrow = None
 
 logger = logging.getLogger(__name__)
 
@@ -977,14 +981,14 @@ def fetchmany(self, size: int) -> List[Row]:
         else:
             raise Error("There is no active result set")
 
-    def fetchall_arrow(self) -> pyarrow.Table:
+    def fetchall_arrow(self) -> "pyarrow.Table":
         self._check_not_closed()
         if self.active_result_set:
             return self.active_result_set.fetchall_arrow()
         else:
             raise Error("There is no active result set")
 
-    def fetchmany_arrow(self, size) -> pyarrow.Table:
+    def fetchmany_arrow(self, size) -> "pyarrow.Table":
         self._check_not_closed()
         if self.active_result_set:
             return self.active_result_set.fetchmany_arrow(size)
@@ -1171,7 +1175,7 @@ def _convert_arrow_table(self, table):
     def rownumber(self):
         return self._next_row_index
 
-    def fetchmany_arrow(self, size: int) -> pyarrow.Table:
+    def fetchmany_arrow(self, size: int) -> "pyarrow.Table":
         """
         Fetch the next set of rows of a query result, returning a PyArrow table.
 
@@ -1196,7 +1200,7 @@ def fetchmany_arrow(self, size: int) -> pyarrow.Table:
 
         return results
 
-    def fetchall_arrow(self) -> pyarrow.Table:
+    def fetchall_arrow(self) -> "pyarrow.Table":
         """Fetch all (remaining) rows of a query result, returning them as a PyArrow table."""
         results = self.results.remaining_rows()
         self._next_row_index += results.num_rows

databricks_sql_connector_core/src/databricks/sql/thrift_backend.py

@@ -37,6 +37,11 @@
     convert_column_based_set_to_arrow_table,
 )
 
+try:
+    import pyarrow
+except ImportError:
+    pyarrow = None
+
 logger = logging.getLogger(__name__)
 
 unsafe_logger = logging.getLogger("databricks.sql.unsafe")
@@ -652,6 +657,12 @@ def _get_metadata_resp(self, op_handle):
 
     @staticmethod
     def _hive_schema_to_arrow_schema(t_table_schema):
+
+        if pyarrow is None:
+            raise ImportError(
+                "pyarrow is required to convert Hive schema to Arrow schema"
+            )
+
         def map_type(t_type_entry):
             if t_type_entry.primitiveEntry:
                 return {
@@ -858,7 +869,7 @@ def execute_command(
             getDirectResults=ttypes.TSparkGetDirectResults(
                 maxRows=max_rows, maxBytes=max_bytes
             ),
-            canReadArrowResult=True,
+            canReadArrowResult=True if pyarrow else False,
             canDecompressLZ4Result=lz4_compression,
             canDownloadResult=use_cloud_fetch,
             confOverlay={

databricks_sql_connector_core/src/databricks/sql/utils.py

@@ -28,16 +28,21 @@
 
 import logging
 
+try:
+    import pyarrow
+except ImportError:
+    pyarrow = None
+
 logger = logging.getLogger(__name__)
 
 
 class ResultSetQueue(ABC):
     @abstractmethod
-    def next_n_rows(self, num_rows: int) -> pyarrow.Table:
+    def next_n_rows(self, num_rows: int):
         pass
 
     @abstractmethod
-    def remaining_rows(self) -> pyarrow.Table:
+    def remaining_rows(self):
         pass
 
 
@@ -100,7 +105,7 @@ def build_queue(
 class ArrowQueue(ResultSetQueue):
     def __init__(
         self,
-        arrow_table: pyarrow.Table,
+        arrow_table: "pyarrow.Table",
         n_valid_rows: int,
         start_row_index: int = 0,
     ):
@@ -115,7 +120,7 @@ def __init__(
         self.arrow_table = arrow_table
         self.n_valid_rows = n_valid_rows
 
-    def next_n_rows(self, num_rows: int) -> pyarrow.Table:
+    def next_n_rows(self, num_rows: int) -> "pyarrow.Table":
         """Get upto the next n rows of the Arrow dataframe"""
         length = min(num_rows, self.n_valid_rows - self.cur_row_index)
         # Note that the table.slice API is not the same as Python's slice
@@ -124,7 +129,7 @@ def next_n_rows(self, num_rows: int) -> pyarrow.Table:
         self.cur_row_index += slice.num_rows
         return slice
 
-    def remaining_rows(self) -> pyarrow.Table:
+    def remaining_rows(self) -> "pyarrow.Table":
         slice = self.arrow_table.slice(
             self.cur_row_index, self.n_valid_rows - self.cur_row_index
         )
@@ -184,7 +189,7 @@ def __init__(
         self.table = self._create_next_table()
         self.table_row_index = 0
 
-    def next_n_rows(self, num_rows: int) -> pyarrow.Table:
+    def next_n_rows(self, num_rows: int) -> "pyarrow.Table":
         """
         Get up to the next n rows of the cloud fetch Arrow dataframes.
 
@@ -216,7 +221,7 @@ def next_n_rows(self, num_rows: int) -> pyarrow.Table:
         logger.debug("CloudFetchQueue: collected {} next rows".format(results.num_rows))
         return results
 
-    def remaining_rows(self) -> pyarrow.Table:
+    def remaining_rows(self) -> "pyarrow.Table":
         """
         Get all remaining rows of the cloud fetch Arrow dataframes.
 
@@ -237,7 +242,7 @@ def remaining_rows(self) -> pyarrow.Table:
             self.table_row_index = 0
         return results
 
-    def _create_next_table(self) -> Union[pyarrow.Table, None]:
+    def _create_next_table(self) -> Union["pyarrow.Table", None]:
         logger.debug(
             "CloudFetchQueue: Trying to get downloaded file for row {}".format(
                 self.start_row_index
@@ -276,7 +281,7 @@ def _create_next_table(self) -> Union[pyarrow.Table, None]:
 
         return arrow_table
 
-    def _create_empty_table(self) -> pyarrow.Table:
+    def _create_empty_table(self) -> "pyarrow.Table":
         # Create a 0-row table with just the schema bytes
         return create_arrow_table_from_arrow_file(self.schema_bytes, self.description)
 
@@ -515,7 +520,7 @@ def transform_paramstyle(
     return output
 
 
-def create_arrow_table_from_arrow_file(file_bytes: bytes, description) -> pyarrow.Table:
+def create_arrow_table_from_arrow_file(file_bytes: bytes, description) -> "pyarrow.Table":
     arrow_table = convert_arrow_based_file_to_arrow_table(file_bytes)
     return convert_decimals_in_arrow_table(arrow_table, description)
 
@@ -542,7 +547,7 @@ def convert_arrow_based_set_to_arrow_table(arrow_batches, lz4_compressed, schema
     return arrow_table, n_rows
 
 
-def convert_decimals_in_arrow_table(table, description) -> pyarrow.Table:
+def convert_decimals_in_arrow_table(table, description) -> "pyarrow.Table":
     for i, col in enumerate(table.itercolumns()):
         if description[i][1] == "decimal":
             decimal_col = col.to_pandas().apply(