Name
Abstract | ||
|---|---|---|
Using persistent memory (PM) for an in-memory database (IMDB) system significantly extends data processing capacity and reduces service downtime for the recovery process in case of system failure. However, it requires an index structure tailored for the characteristics of PM to recover the consistent state from system failure. The processor flushes data with the cache line size to the memory controller, whereas the PM media writes with the media-write unit size, which is four times larger than the cache line size. This mismatch in write sizes amplifies the quantity of data written by an index structure at the physical media level. Additionally, the PM-aware index structures explicitly and frequently flush cache lines to ensure memory write orders, which worsen the write amplification factor. The write amplification not only degrades the performance but also shortens the lifespan of PM media. This study analyzes the write amplification and performance of various PM-aware index structures at the memory controller and physical media levels. Furthermore, this paper proposes four optimization techniques based on our observation: removal of unintended bloat, cache flush coalescing, early eviction of volatile data, and XPLine-aware unit sizing. Our analysis demonstrated that up to 3.9 times as many writes could occur depending on the choice of the index structure. We also revealed that the proposed optimization techniques could save up to 51% of physical media write operations and improve throughput by up to 63%. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ACCESS.2021.3136459 | IEEE ACCESS |
Keywords | DocType | Volume |
Indexes, Media, Optimization, Databases, Arrays, Random access memory, Licenses, Persistent memory, index structure, write amplification, in-memory databases | Journal | 9 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Youngjoo Woo | 1 | 0 | 0.34 |
| Taesoo Kim | 2 | 809 | 51.85 |
| Sungin Jung | 3 | 0 | 0.34 |
| Euiseong Seo | 4 | 0 | 0.68 |