Transforming Query Sequences for High-Throughput B+ Tree Processing on Many-Core Processors

Ruiqin Tian, Junqiao Qiu, Zhijia Zhao, Xu Liu, Bin Ren

Abstract: The throughput of B+ tree query processing is critical to many databases, file systems, and cloud applications. Based on bulk synchronous parallel (BSP), latch-free B+ tree query processing has shown promise by processing queries in small batches and avoiding the use of locks. As the number of cores on CPUs increases, it becomes possible to process larger batches in parallel without adding any extra delays. In this work, we argue that as the batch size increases, there will be more optimization opportunities exposed beyond parallelism, especially when the query distributions are highly skewed. These include the opportunities of avoiding the evaluations of a large ratio of redundant or unnecessary queries. To rigorously exploit the new opportunities, this work introduces a query sequence analysis and transformation framework - QTrans. QTrans can systematically reason about the redundancies at a deep level and automatically remove them from the query sequence. QTrans has interesting resemblances with the classic data-flow analysis and transformation that have been widely used in compilers. To confirm its benefits, this work integrates QTrans into an existing BSP-based B+ tree query processing system, PALM tree, to automatically eliminate redundant and unnecessary queries <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> . Evaluation shows that, by transforming the query sequence, QTrans can substantially improve the throughput of query processing on both real-world and synthesized datasets, up to 16X.