Michael Armbrust, a PhD candidate at UC Berkeley, was our very FIRST guest speaker for the Groupinar series, coming in to discuss Scale Independent Relational Query Processing w/ PIQL. A little more about the talk in his words..."The rapid growth of data volumes has led many developers to abandon traditional relational databases in favor of distributed key/values stores and map/reduce programs. While these alternatives often provide trivial scalability for developers, they lack many of the benefits of high-level declarative languages such as optimization and data independence. Instead, I propose extending the relational model with scale independence, a new type of data independence, that ensures consistent performance for all queries in an application, independent of the data size. My implementation, PIQL – the Performance Insightful Query Language, provides a scale-independent relational system on top of existing distributed key/values stores using several techniques. First, PIQL uses bounded worst-case cost instead of average minimum cost as the objective function for query optimization. Additionally, the system automatically selects and maintains required indexes and materialized views. In this talk I will present PIQL’s extensions to standard SQL, the techniques used by the optimizer to ensure bounded resource requirements in the worst case, and performance results demonstrating linear scalability with consistent response time as an application’s data grows by an order of magnitude."
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