%0 Journal Article %A ZHANG Jun %A LIAO Xuehua %A YU Xuling %A LEI Meng %T Research on Realizing Relational Database In-Memory Storage Model %D 2021 %R 10.3778/j.issn.1002-8331.2009-0508 %J Computer Engineering and Applications %P 123-128 %V 57 %N 19 %X

In a big data environment, the disk database has I/O bottleneck in high concurrent scenarios, while disk data memorization is an effective solution to solve this, and existing memory technologies have problems such as data loss, complex configuration. Based on the in-memory database Redis and taking MySQL as an example, it proposes a lightweight memorization scheme that solves the disk read-write bottleneck of relational databases. This scheme not only improves the database's throughput in high-concurrency scenarios, but also enables access to massive hotspot data efficiently. Row-Based Key-Value storage conversion Model(RB-KVM) and Piecewise Column-Based Key-Value Cross storage conversion Model(PCB-KVCM) are constructed to realize the transformation of heterogeneous database storage model and automated data migration. Finally, it analyzes and compares the two models, and shows RB-KVM has higher data access efficiency, and PCB-KVCM has higher memory utilization and lower time cost.

%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2009-0508