Using WebAssembly for in-database Machine Learning
summary
Builds a Rust WebAssembly module from a Rust port of Vader sentiment, compiles and deploys it into SingleStore DB with the push wasm tool, and exposes it as a wasm table-valued UDF. The demo loads the wasm into a demo database, runs the function over a 25,000-row IMDb reviews table, returns compound/positive/negative/neutral scores per row, reports successful creation, and shows practical near‑native performance inside a sandboxed database runtime.
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chapters (10)
- 0:00introduction
- 0:17agenda
- 4:39install the software
- 7:03initialise the source tree
- 7:31create the interface Definition file
- 8:22implement and compile
- 10:56deploy wasm
- 12:25run in the database
- 16:39summary
- 17:14resources
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