NoSQL数据库中物化视图选择和并发控制机制的比较分析
A Comparative Analysis of Materialized Views Selection and Concurrency Control Mechanisms in NoSQL Databases
摘要：
不断增长的资源需求要求关系数据库能够扩展。虽然关系数据库非常适合垂直扩展，但专用硬件可能很昂贵。相反，新兴的NewSQL和NoSQL数据存储旨在水平扩展。NewSQL数据库提供ACID事务支持;但是，连接仅限于分区键，导致查询表达能力受限。另一方面，NoSQL数据库被设计为在商用硬件上线性扩展;然而，它们受到连接性能缓慢的限制。因此，我们考虑是否可以在确保ACID语义且不会大幅牺牲写性能、磁盘利用率和查询表达能力的情况下提高NoSQL连接性能。本文介绍了协同系统，利用模式和工作负载驱动的机制，以确定物化视图和一个专门的并发控制系统上的NoSQL数据库，使可扩展的数据管理与熟悉的关系公约。Synergy以轻微的写入性能下降和更高的磁盘利用率换取更快的连接性能（与标准NoSQL数据库相比）和更好的查询表现力（与NewSQL数据库相比）。使用TPC-W基准测试的实验结果表明，对于一个数据库填充1M客户，协同系统表现出最大的性能提高80.5%相比，其他评估系统。
英文摘要：
Increasing resource demands require relational databases to scale. While relational databases are well suited for vertical scaling, specialized hardware can be expensive. Conversely, emerging NewSQL and NoSQL data stores are designed to scale horizontally. NewSQL databases provide ACID transaction support; however, joins are limited to the partition keys, resulting in restricted query expressiveness. On the other hand, NoSQL databases are designed to scale out linearly on commodity hardware; however, they are limited by slow join performance. Hence, we consider if the NoSQL join performance can be improved while ensuring ACID semantics and without drastically sacrificing write performance, disk utilization and query expressiveness. This paper presents the Synergy system that leverages schema and workload driven mechanism to identify materialized views and a specialized concurrency control system on top of a NoSQL database to enable scalable data management with familiar relational conventions. Synergy trades slight write performance degradation and increased disk utilization for faster join performance (compared to standard NoSQL databases) and improved query expressiveness (compared to NewSQL databases). Experimental results using the TPC-W benchmark show that, for a database populated with 1M customers, the Synergy system exhibits a maximum performance improvement of 80.5% as compared to other evaluated systems.
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