基于整数规划的关系型OLTP数据库的垂直划分
Vertical partitioning of relational OLTP databases using integer programming
摘要：
优化关系行存储数据库性能的一种方法是通过将表垂直划分为表部分来减小行宽度，以便最小化每个事务读取的不相关列/属性的数量。本文认为垂直分区算法的关系行存储OLTP数据库与H存储的架构，这意味着我们要最大限度地提高单站点事务的数量。我们提出了一个模型的垂直分区的问题，给定的模式连同垂直分区和工作量，估计成本（字节读/写的存储层访问方法和字节之间的站点传输）评估给定分区的工作量。成本模型允许任意优先考虑站点的负载均衡与总成本最小化。我们发现，在这个模型中找到一个最低成本的垂直分区是NP-难的，并提出了两个算法返回的解决方案，其中单站点的读取查询被保留，同时允许列复制（这可能会允许大幅降低成本相比，不相交分区）。第一个算法是一个二次整数规划，找到最优的最小成本的解决方案，相对于模型，第二个算法是一个更可扩展的启发式基于模拟退火。实验表明，该算法可以降低成本的模型目标的37%时，应用到TPC-C的基准和启发式获得的解决方案的成本接近使用二次规划。
英文摘要：
A way to optimize performance of relational row store databases is to reduce the row widths by vertically partitioning tables into table fractions in order to minimize the number of irrelevant columns/attributes read by each transaction. This paper considers vertical partitioning algorithms for relational row-store OLTP databases with an H-store-like architecture, meaning that we would like to maximize the number of single-sited transactions. We present a model for the vertical partitioning problem that, given a schema together with a vertical partitioning and a workload, estimates the costs (bytes read/written by storage layer access methods and bytes transferred between sites) of evaluating the workload on the given partitioning. The cost model allows for arbitrarily prioritizing load balancing of sites vs. total cost minimization. We show that finding a minimum-cost vertical partitioning in this model is NP-hard and present two algorithms returning solutions in which single-sitedness of read queries is preserved while allowing column replication (which may allow a drastically reduced cost compared to disjoint partitioning). The first algorithm is a quadratic integer program that finds optimal minimum-cost solutions with respect to the model, and the second algorithm is a more scalable heuristic based on simulated annealing. Experiments show that the algorithms can reduce the cost of the model objective by 37% when applied to the TPC-C benchmark and the heuristic is shown to obtain solutions with cost close to the ones found using the quadratic program.
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