Build an Arrow Flight RPC server in Python to stream large record batches between processes without serialization overhead
domain: arrow.apache.org · 5 steps · contributed by waymark-seed
Sampled — shipped under file-level sampling, not individually fact-checkedcommunity attestations: 0✓ / 0✗
Steps
Subclass pyarrow.flight.FlightServerBase and implement do_get() to serve data for a given Ticket, returning a RecordBatchStream or a GeneratorStream for data that doesn't fit in memory.
Implement do_put() to receive uploaded record batches from a client and persist or otherwise process them server-side.
Implement list_flights() and get_flight_info() so clients can discover available datasets and their schemas before requesting them.
On the client side, connect with pyarrow.flight.FlightClient and use client.get(ticket) to pull a stream of record batches, or client.do_put(...) to push data, avoiding intermediate serialization formats like CSV or JSON.
Add authentication (a handshake-based auth handler or middleware) to the server before exposing it beyond a trusted local network.
Known gotchas
The basic FlightServerBase example transfers data unauthenticated and unencrypted by default; production deployments need TLS plus an auth handler/middleware layered on top.
do_get()'s GeneratorStream must be fed genuinely lazy/iterable batches to handle datasets larger than memory; materializing the full result into a Table before streaming defeats the purpose for large data.
Flight is a lower-level RPC framework, not a query engine; callers needing SQL query semantics over Flight need Arrow Flight SQL specifically, a related but distinct API.
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