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首页> 外文期刊>Knowledge and Data Engineering, IEEE Transactions on >In-Memory Big Data Management and Processing: A Survey
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In-Memory Big Data Management and Processing: A Survey

机译：内存中大数据管理和处理：一项调查

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摘要

Growing main memory capacity has fueled the development of in-memory big data management and processing. By eliminating disk I/O bottleneck, it is now possible to support interactive data analytics. However, in-memory systems are much more sensitive to other sources of overhead that do not matter in traditional I/O-bounded disk-based systems. Some issues such as fault-tolerance and consistency are also more challenging to handle in in-memory environment. We are witnessing a revolution in the design of database systems that exploits main memory as its data storage layer. Many of these researches have focused along several dimensions: modern CPU and memory hierarchy utilization, time/space efficiency, parallelism, and concurrency control. In this survey, we aim to provide a thorough review of a wide range of in-memory data management and processing proposals and systems, including both data storage systems and data processing frameworks. We also give a comprehensive presentation of important technology in memory management, and some key factors that need to be considered in order to achieve efficient in-memory data management and processing.
机译：主存储器容量的增长推动了内存中大数据管理和处理的发展。通过消除磁盘I / O瓶颈，现在可以支持交互式数据分析。但是，内存系统对其他开销来源更为敏感，而这些开销在传统的基于I / O的基于磁盘的系统中并不重要。诸如容错性和一致性之类的问题在内存环境中也更具挑战性。我们正在见证数据库系统设计的一场革命，该革命利用主内存作为其数据存储层。其中许多研究集中在几个方面：现代CPU和内存层次结构利用率，时间/空间效率，并行性和并发控制。在本次调查中，我们旨在彻底审查各种内存中数据管理和处理建议以及系统，包括数据存储系统和数据处理框架。我们还全面介绍了内存管理中的重要技术，以及为了实现有效的内存中数据管理和处理而需要考虑的一些关键因素。

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