SIREN: A Memory-Conserving, Snapshot-Consistent Checkpoint Algorithm for in-Memory Databases
SIREN: A Memory-Conserving, Snapshot-Consistent Checkpoint Algorithm for in-Memory Databases
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DOI：
10.1109/icde.2006.140
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发表时间：
2006-04
期刊：
影响因子：
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通讯作者：
Antti-Pekka Liedes;A. Wolski
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文献类型：
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作者：
Antti-Pekka Liedes;A. Wolski
内存数据库的检查点是持续的数据库图像的主要来源，在软件崩溃或电力中断中幸存下来，并且与交易日志一起，是交易耐用性的基础。倾向于减少数据库吞吐量并增加当前方法的内存足迹。交易障碍行为引入了方法的算法，对所提出的算法的分析和实验分析显示，与具有撤消/重做日志的模糊检查点方法相比，交易量的内存使用情况显着降低，交易吞吐量高达30％。
Checkpoint of an in-memory database is the main source of a persistent database image surviving a software crash, or a power outage, and is, together with transactions logs, a foundation for transaction durability. Since checkpoints are created simultaneously with transaction processing, they tend to decrease database throughput and increase its memory footprint. Of the current methods, most efficient are the fuzzy checkpoint algorithms that write dirty pages to disk and require transaction logs for reconstructing a consistent state. Known consistency-preserving methods suffer from excessive memory usage or a transaction-blocking behavior. In this paper, we present a consistency-preserving and memory-efficient checkpoint method. It is based on tuple shadowing as opposed to known page shadowing methods, and rearranging of tuples between pages for minimal memory usage overhead. The method’s algorithms are introduced and both analytical and experimental analysis of the proposed algorithms show significant reduction in the memory usage overhead, and up to 30% higher transaction throughput compared with a fuzzy checkpoint method with undo/redo log.