Large-scale, user-facing applications are increasingly moving from relational databases to distributed key/value stores for high-request-rate, low-latency workloads. Often, this move is motivated not only by key/value stores' ability to scale simply by adding more hardware, but also by the easy to understand predictable performance they provide for all operations. For complex queries, this approach often requires onerous explicit index management and imperative data lookup by the developer. We propose PIQL, a Performance Insightful Query Language that allows developers to express many queries found on these websites while still providing strict bounds on the number of I/O operations that will be performed.

Large-scale websites are increasingly moving from relational databases to distributed key-value stores for high request rate, low latency workloads. Often this move is motivated not only by key-value stores' ability to scale simply by adding more hardware, but also by the easy to understand predictable performance they provide for all operations. While this data model works well, lookups are only done by primary key. More complex queries require onerous, explicit index management and imperative data lookups by the developer. We demonstrate PIQL, a Performance Insightful Query Language that allows developers to express many of the queries found on these websites, while still providing strict bounds on the number of I/O operations for any query.

Napster pioneered the idea of peer-to-peer file sharing, and supported it with a centralized file search facility. Subsequent P2P systems like Gnutella adopted decentralized search algorithms. However, Gnutella's notoriously poor scaling led some to propose distributed hash table solutions to the wide-area file search problem. Contrary to that trend, we advocate retaining Gnutella's simplicity while proposing new mechanisms that greatly improve its scalability. Building upon prior research [1, 12, 22], we propose several modifications to Gnutella's design that dynamically adapt the overlay topology and the search algorithms in order to accommodate the natural heterogeneity present in most peer-to-peer systems. We test our design through simulations and the results show three to five orders of magnitude improvement in total system capacity. We also report on a prototype implementation and its deployment on a testbed.