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MemTest: A novel benchmark for in-memory database

  • East China Normal University

科研成果: 书/报告/会议事项章节章节同行评审

摘要

With the rapid development of hardware, a stand-alone computer can employ a memory which has large amounts of volumes. Several industries and research institutions have devoted more resources to develop several in-memory databases, which preload the data into memory for further processing. With the boom of in-memory databases, there emerges requirements to evaluate and compare the performance of these systems impartially and objectively. In this paper, we proposed MemTest, a novel benchmark considering the main characteristics of an in-memory database. This benchmark constructs particular metrics, which cover CPU usage, cache miss, compression ratio, minimal memory space and response time of an in-memory database and are also the core of our benchmark. We design a data model based on inter-bank transaction applications, around which a data generator is devised to support the data distributions of uniform and skew. The MemTest workload includes a set of queries and transactions against the metrics and data model. In the end, we illustrate the efficacy of MemTest through implementations on three different in-memory databases.

源语言英语
主期刊名Big Data Benchmarks, Performance Optimization, and Emerging Hardware - 4th and 5th Workshops, BPOE 2014, Revised Selected Papers
编辑Jianfeng Zhan, Rui Han, Rui Han, Chuliang Weng
出版商Springer Verlag
34-46
页数13
ISBN(电子版)9783319130200
DOI
出版状态已出版 - 2014

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
8807
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

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