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New Contributor III

I'm using a shared access cluster and am getting this error while trying to upload to Qdrant. This is the error. Anyway I can make it worked on shared access mode? It works on the personal cluster.

[UC_COMMAND_NOT_SUPPORTED.WITHOUT_RECOMMENDATION] The command(s): AppendData are not supported in Unity Catalog.  SQLSTATE: 0AKUC
File <command-2604385794497207>, line 65
     48 #embeddings_df = embeddings_df.limit(5)
     50 options = {
     51     "qdrant_url": QDRANT_GRPC_URL,
     52     "api_key": QDRANT_API_KEY,
     60     "batch_size":"128",
     61 }
     63 embeddings_df.write.format("io.qdrant.spark.Qdrant").options(**options).mode(
     64     "append"
---> 65 ).save()

File /databricks/spark/python/pyspark/sql/connect/, in, path, format, mode, partitionBy, **options)
    668     self.format(format)
    669 self._write.path = path
--> 670 self._spark.client.execute_command(
    671     self._write.command(self._spark.client), self._write.observations
    672 )
File /databricks/spark/python/pyspark/sql/connect/client/, in SparkConnectClient.execute_command(self, command, observations, extra_request_metadata)
   1201     req.user_context.user_id = self._user_id
   1202 req.plan.command.CopyFrom(command)
-> 1203 data, _, _, _, properties = self._execute_and_fetch(
   1204     req, observations or {}, extra_request_metadata
   1205 )
   1206 if data is not None:
   1207     return (data.to_pandas(), properties)
File /databricks/spark/python/pyspark/sql/connect/client/, in SparkConnectClient._execute_and_fetch(self, req, observations, extra_request_metadata, self_destruct)
   1621 schema: Optional[StructType] = None
   1622 properties: Dict[str, Any] = {}
-> 1624 for response in self._execute_and_fetch_as_iterator(
   1625     req, observations, extra_request_metadata or []
   1626 ):
   1627     if isinstance(response, StructType):
   1628         schema = response
File /databricks/spark/python/pyspark/sql/connect/client/, in SparkConnectClient._execute_and_fetch_as_iterator(self, req, observations, extra_request_metadata)
   1599                     yield from handle_response(b)
   1600 except Exception as error:
-> 1601     self._handle_error(error)
File /databricks/spark/python/pyspark/sql/connect/client/, in SparkConnectClient._handle_error(self, error)
   1908 self.thread_local.inside_error_handling = True
   1909 if isinstance(error, grpc.RpcError):
-> 1910     self._handle_rpc_error(error)
   1911 elif isinstance(error, ValueError):
   1912     if "Cannot invoke RPC" in str(error) and "closed" in str(error):
File /databricks/spark/python/pyspark/sql/connect/client/, in SparkConnectClient._handle_rpc_error(self, rpc_error)
   1982             info = error_details_pb2.ErrorInfo()
   1983             d.Unpack(info)
-> 1985             raise convert_exception(
   1986                 info,
   1987                 status.message,
   1988                 self._fetch_enriched_error(info),
   1989                 self._display_server_stack_trace(),
   1990             ) from None
   1992     raise SparkConnectGrpcException(status.message) from None

 This is the code.

#embeddings_df = embeddings_df.limit(5)

options = {
    "qdrant_url": QDRANT_GRPC_URL,
    "api_key": QDRANT_API_KEY,
    "collection_name": QDRANT_COLLECTION_NAME,
    "vector_fields": "dense_vector",
    "vector_names": "dense",
    "schema": embeddings_df.schema.json(),




Community Manager
Community Manager

Hi @Awoke101

  • Shared access clusters in Databricks have certain restrictions due to Unity Catalog limitations.
  • I recommend trying the single-user Unity Catalog cluster or configuring data persistence outside the container. Let me know if you need further assistance! 
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