Jon Gjengset, Malte Schwarzkopf, Jonathan Behrens, and Lara Timbó Araújo, MIT CSAIL; Martin Ek, Norwegian University of Science and Technology; Eddie Kohler, Harvard University; M. Frans Kaashoek and Robert Morris, MIT CSAIL
We introduce partially-stateful data-flow, a new streaming data-flow model that supports eviction and reconstruction of data-flow state on demand. By avoiding state explosion and supporting live changes to the data-flow graph, this model makes data-flow viable for building long-lived, low-latency applications, such as web applications. Our implementation, Noria, simplifies the backend infrastructure for read-heavy web applications while improving their performance.
A Noria application supplies a relational schema and a set of parameterized queries, which Noria compiles into a data-flow program that pre-computes results for reads and incrementally applies writes. Noria makes it easy to write high-performance applications without manual performance tuning or complex-to-maintain caching layers. Partial statefulness helps Noria limit its in-memory state without prior data-flow systems’ restriction to windowed state, and helps Noria adapt its data-flow to schema and query changes while on-line. Unlike prior data-flow systems, Noria also shares state and computation across related queries, eliminating duplicate work.
On a real web application’s queries, our prototype scales to 5× higher load than a hand-optimized MySQL baseline. Noria also outperforms a typical MySQL/memcached stack and the materialized views of a commercial database. It scales to tens of millions of reads and millions of writes per second over multiple servers, outperforming a state-of-the-art streaming data-flow system.
Open Access Media
USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.