HyPer: A hybrid OLTP&OLAP main memory database system based on virtual memory snapshots

HyPer: A hybrid OLTP&OLAP main memory database system based on virtual memory snapshots
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HyPer:混合 OLTP

DOI:
10.1109/icde.2011.5767867
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发表时间:
2011
期刊:
2011 IEEE 27th International Conference on Data Engineering
影响因子:
--
通讯作者:
T. Neumann
T. Neumann
中科院分区:
--
文献类型:
--
作者:
A. Kemper;T. Neumann

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在线事务处理(OLTP)和在线分析处理(OLAP)这两个领域对数据库体系结构提出了不同的挑战。目前,具有高任务关键型事务率的客户已将其数据拆分到两个独立的系统中,一个数据库用于OLTP,另一个所谓的数据仓库用于OLAP。虽然允许适当的交易率,但这种分离有许多缺点,包括由于仅定期启动提取转换加载造成的延迟而导致的数据新鲜性问题--数据分段,以及由于维护两个独立的信息系统而导致的过度资源消耗。我们提出了一种高效的混合系统,称为HYPER,通过使用硬件辅助的复制机制来维护事务数据的一致快照,该系统可以同时处理OLTP和OLAP。Hyper是一个内存数据库系统,它保证OLTP事务的ACID属性,并在相同的、任意当前的和一致的快照上执行OLAP查询会话(多个查询)。利用处理器固有的对虚拟内存管理(地址转换、缓存、更新时复制)的支持,可以同时产生以下两种结果:在并行执行这两个工作负载的单个系统上实现前所未有的高达每秒100000的事务率和非常快的OLAP查询响应时间。性能分析基于TPC-C和TPC-H的组合基准。
The two areas of online transaction processing (OLTP) and online analytical processing (OLAP) present different challenges for database architectures. Currently, customers with high rates of mission-critical transactions have split their data into two separate systems, one database for OLTP and one so-called data warehouse for OLAP. While allowing for decent transaction rates, this separation has many disadvantages including data freshness issues due to the delay caused by only periodically initiating the Extract Transform Load-data staging and excessive resource consumption due to maintaining two separate information systems. We present an efficient hybrid system, called HyPer, that can handle both OLTP and OLAP simultaneously by using hardware-assisted replication mechanisms to maintain consistent snapshots of the transactional data. HyPer is a main-memory database system that guarantees the ACID properties of OLTP transactions and executes OLAP query sessions (multiple queries) on the same, arbitrarily current and consistent snapshot. The utilization of the processor-inherent support for virtual memory management (address translation, caching, copy on update) yields both at the same time: unprecedentedly high transaction rates as high as 100000 per second and very fast OLAP query response times on a single system executing both workloads in parallel. The performance analysis is based on a combined TPC-C and TPC-H benchmark.
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