Understand and troubleshoot Flight responses
Learn how to handle responses and troubleshoot errors encountered when querying InfluxDB Cloud Dedicated with Flight+gRPC and Arrow Flight clients.
InfluxDB Flight responses
InfluxDB Cloud Dedicated provides an InfluxDB-specific Arrow Flight remote procedure calls (RPC) and Flight SQL service that uses gRPC, a high performance RPC framework, to transport data in Arrow format. Flight defines a set of RPC methods that servers and clients can use to exchange information. Flight SQL uses Flight RPC and defines additional methods to query database metadata, execute queries, and manipulate prepared statements. To learn more about Flight SQL, see Introducing Apache Arrow Flight SQL: Accelerating Database Access.
To query data or retrieve information about data stored in InfluxDB Cloud Dedicated, use a Flight client to send a call to an InfluxDB Flight RPC or Flight SQL service method.
For example, if you use the influxdb3-python
Python client library and call the InfluxDBClient3.query()
method, the client in turn calls the pyarrow.flight.FlightClient.do_get()
method and passes a Flight ticket containing your credentials and query to InfluxDB’s Flight DoGet(FlightCallOptions, Ticket)
method.
InfluxDB responds with one of the following:
- A stream in Arrow IPC streaming format
- An error status code and an optional
details
field that contains the status and a message that describes the error
Stream
InfluxDB provides Flight RPC methods and implements server-side streaming for clients to retrieve and download data. In a gRPC server-side streaming scenario, a client sends an RPC call in a request to a server. Because the server can return a stream of multiple responses to the client, the client request contains an identifier that the client and server use to keep track of the request and associated responses. As the server sends responses, they are associated with the corresponding stream on the client side.
An Arrow Flight service, such as InfluxDB, sends a stream in Arrow IPC streaming format that defines the structure of the stream and each response, or message, in the stream.
Flight client libraries, such as pyarrow.flight
and the Go Arrow Flight package, implement an Arrow interface for retrieving the data, schema, and metadata from the stream.
After InfluxDB Cloud Dedicated successfully processes a query, it sends a stream that contains the following:
- A Schema that applies to all record batches in the stream
- RecordBatch messages with query result data
- The request status (
OK
) - Optional: trailing metadata
Schema
An InfluxDB Flight response stream contains a Flight schema that describes the data type and InfluxDB data element type (timestamp, tag, or field) for columns in the data set. All data chunks, or record batches, in the same stream have the same schema. Data transformation tools can use the schema when converting Arrow data to other formats and back to Arrow.
Example
Given the following query:
SELECT co, delete, hum, room, temp, time
FROM home
WHERE time >= now() - INTERVAL '90 days'
ORDER BY time
The Python client library outputs the following schema representation:
Schema:
co: int64
-- field metadata --
iox::column::type: 'iox::column_type::field::integer'
delete: string
-- field metadata --
iox::column::type: 'iox::column_type::tag'
hum: double
-- field metadata --
iox::column::type: 'iox::column_type::field::float'
room: string
-- field metadata --
iox::column::type: 'iox::column_type::tag'
temp: double
-- field metadata --
iox::column::type: 'iox::column_type::field::float'
time: timestamp[ns] not null
-- field metadata --
iox::column::type: 'iox::column_type::timestamp'
Using PyArrow, you can access the schema through the FlightStreamReader.schema
attribute.
See InfluxDBClient3.query()
examples for retrieving the schema.
RecordBatch
RecordBatch
messages in the InfluxDB Cloud Dedicated response stream contain query result data in Arrow format.
When the Flight client receives a stream, it reads each record batch from the stream until there are no more messages to read.
The client considers the request complete when it has received all the messages.
Flight clients and InfluxDB v3 client libraries provide methods for reading record batches, or “data chunks,” from a stream.
The InfluxDB v3 Python client library uses the pyarrow.flight.FlightStreamReader
class and provides the following reader methods:
all
: Read all record batches into apyarrow.Table
.pandas
: Read all record batches into apandas.DataFrame
.chunk
: Read the next batch and metadata, if available.reader
: Convert theFlightStreamReader
instance into aRecordBatchReader
.
Flight clients implement Flight interfaces, however client library classes, methods, and implementations may differ for each language and library.
InfluxDB status and error codes
In gRPC, every call returns a status object that contains an integer code and a string message. During a request, the gRPC client and server may each return a status–for example:
- The server fails to process the query; responds with status
internal error
and gRPC status13
. - The request is missing a token; the server responds with status
unauthenticated
and gRPC status16
. - The server responds with a stream, but the client loses the connection due to a network failure and returns status
unavailable
.
gRPC defines the integer status codes and definitions for servers and clients and
Arrow Flight defines a FlightStatusDetail
class and the error codes that a Flight RPC service may implement.
While Flight defines the status codes available for servers, a server can choose which status to return for an RPC call.
In error responses, the status details
field contains an error code that clients can use to determine if the error should be displayed to users (for example, if the client should retry the request).
Troubleshoot errors
Internal Error: Received RST_STREAM
Example:
Flight returned internal error, with message: Received RST_STREAM with error code 2. gRPC client debug context: UNKNOWN:Error received from peer ipv4:34.196.233.7:443 {grpc_message:"Received RST_STREAM with error code 2"}
Potential reasons:
- The connection to the server was reset unexpectedly.
- Network issues between the client and server.
- Server might have closed the connection due to an internal error.
- The client exceeded the server’s maximum number of concurrent streams.
Internal Error: stream terminated by RST_STREAM with NO_ERROR
Example:
pyarrow._flight.FlightInternalError: Flight returned internal error, with message: stream terminated by RST_STREAM with error code: NO_ERROR. gRPC client debug context: UNKNOWN:Error received from peer ipv4:3.123.149.45:443 {created_time:"2023-07-26T14:12:44.992317+02:00", grpc_status:13, grpc_message:"stream terminated by RST_STREAM with error code: NO_ERROR"}. Client context: OK
Potential reasons:
- The server terminated the stream, but there wasn’t any specific error associated with it.
- Possible network disruption, even if it’s temporary.
- The server might have reached its maximum capacity or other internal limits.
Invalid Argument: Invalid ticket
Example:
pyarrow.lib.ArrowInvalid: Flight returned invalid argument error, with message: Invalid ticket. Error: Invalid ticket. gRPC client debug context: UNKNOWN:Error received from peer ipv4:54.158.68.83:443 {created_time:"2023-08-31T17:56:42.909129-05:00", grpc_status:3, grpc_message:"Invalid ticket. Error: Invalid ticket"}. Client context: IOError: Server never sent a data message. Detail: Internal
Potential reasons:
- The request is missing the database name or some other required metadata value.
- The request contains bad query syntax.
Timeout: Deadline exceeded
pyarrow._flight.FlightTimedOutError: Flight returned timeout error, with message: Deadline Exceeded. gRPC client debug context: UNKNOWN:Deadline Exceeded {grpc_status:4, created_time:"2023-09-27T15:30:58.540385-05:00"}. Client context: IOError: Server never sent a data message. Detail: Internal
Potential reasons:
- The server’s response time exceeded the number of seconds allowed by the client.
See how to specify
timeout
in FlightCallOptions.
Unauthenticated: Unauthenticated
Example:
Flight returned unauthenticated error, with message: unauthenticated. gRPC client debug context: UNKNOWN:Error received from peer ipv4:34.196.233.7:443 {grpc_message:"unauthenticated", grpc_status:16, created_time:"2023-08-28T15:38:33.380633-05:00"}. Client context: IOError: Server never sent a data message. Detail: Internal
Potential reason:
- Token is missing from the request.
- The specified token doesn’t exist for the specified organization.
Unauthorized: Permission denied
Example:
pyarrow._flight.FlightUnauthorizedError: Flight returned unauthorized error, with message: Permission denied. gRPC client debug context: UNKNOWN:Error received from peer ipv4:54.158.68.83:443 {grpc_message:"Permission denied", grpc_status:7, created_time:"2023-08-31T17:51:08.271009-05:00"}. Client context: IOError: Server never sent a data message. Detail: Internal
Potential reason:
- The specified token doesn’t have read permission for the specified database.
FlightUnavailableError: Could not get default pem root certs
Example:
If unable to locate a root certificate for gRPC+TLS, the Flight client returns errors similar to the following:
UNKNOWN:Failed to load file... filename:"/usr/share/grpc/roots.pem",
children:[UNKNOWN:No such file or directory
...
Could not get default pem root certs...
pyarrow._flight.FlightUnavailableError: Flight returned unavailable error,
with message: empty address list: . gRPC client debug context:
UNKNOWN:empty address list
...
Potential reason:
Non-POSIX-compliant systems (such as Windows) need to specify the root certificates in SslCredentialsOptions for the gRPC client, since the defaults are only configured for POSIX filesystems. Specify the root certificate path For Windows User to config the Flight gRPC client.
For more information about gRPC SSL/TLS client-server authentication, see Using client-side SSL/TLS in the gRPC.io Authentication guide.
Was this page helpful?
Thank you for your feedback!
Support and feedback
Thank you for being part of our community! We welcome and encourage your feedback and bug reports for InfluxDB and this documentation. To find support, use the following resources:
Customers with an annual or support contract can contact InfluxData Support.