• 2 min read
Jane Street’s Incremental targets fast-changing computations
Jane Street’s Incremental library is designed to update complex computations efficiently as inputs change, with uses in spreadsheets, GUIs, and derived data.
Image: Hacker News
Jane Street has published Incremental, a library for building complex computations that update efficiently when their inputs change.
The project is inspired by the work of Umut Acar et. al. on self-adjusting computations. The idea is straightforward: instead of recomputing everything from scratch, developers can structure systems so they react only to the parts affected by new input.
According to the project description, Incremental is suited to several kinds of workloads:
- Large calculations such as spreadsheet-style systems that need to respond efficiently to changing data
- GUI views that must incorporate new data without expensive full refreshes
- Derived data pipelines that stay synchronized with source data, including tasks like filtering or inverting a mapping
Jane Street says the detailed documentation for the library is available in incremental/src/incremental_intf.ml. It also points readers to an informal introduction in a blog post and a video.
The pitch is less about flashy features than engineering discipline: keeping computed state fast, reactive, and in sync as underlying data changes.
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Computing Editor
Tomas lives in the terminal. He covers chips, laptops, and operating systems with a focus on performance and efficiency. He reads kernel changelogs the way other people read fiction, and he's always on the hunt for the perfect mechanical keyboard switch. If it processes data, Tomas has an opinion on it.
via Hacker News
