TB-Collect: Efficient Garbage Collection for Non-Volatile Memory Online Transaction Processing Engines

Guardado en:
Detalles Bibliográficos
Publicado en:Electronics vol. 14, no. 10 (2025), p. 2080
Autor principal: Jianhao, Wei
Otros Autores: Zhang, Qian, Xiang Yiwen, Gong Xueqing
Publicado:
MDPI AG
Materias:
Acceso en línea:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

MARC

LEADER 00000nab a2200000uu 4500
001 3211939574
003 UK-CbPIL
022 |a 2079-9292 
024 7 |a 10.3390/electronics14102080  |2 doi 
035 |a 3211939574 
045 2 |b d20250101  |b d20251231 
084 |a 231458  |2 nlm 
100 1 |a Jianhao, Wei 
245 1 |a TB-Collect: Efficient Garbage Collection for Non-Volatile Memory Online Transaction Processing Engines 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Existing databases supporting Online Transaction Processing (OLTP) workloads based on non-volatile memory (NVM) almost all use Multi-Version Concurrency Control (MVCC) protocol to ensure data consistency. MVCC allows multiple transactions to execute concurrently without lock conflicts, reducing the wait time between read and write operations, and thereby significantly increasing the throughput of NVM OLTP engines. However, it requires garbage collection (GC) to clean up the obsolete tuple versions to prevent storage overflow, which consumes additional system resources. Furthermore, existing GC approaches in NVM OLTP engines are inefficient because they are based on methods designed for dynamic random access memory (DRAM) OLTP engines, without considering the significant differences in read/write bandwidth and cache line size between NVM and DRAM. These approaches either involve excessive random NVM access (traversing tuple versions) or lead to too many additional NVM write operations, both of which degrade the performance and durability of NVM. In this paper, we propose TB-Collect, a high-performance GC approach specifically designed for NVM OLTP engines. On the one hand, TB-Collect separates tuple headers and contents, storing data in an append-only manner, which greatly reduces NVM writes. On the other hand, TB-Collect performs GC at the block level, eliminating the need to traverse tuple versions and improving the utilization of reclaimed space. We have implemented TB-Collect on DBx1000 and MySQL. Experimental results show that TB-Collect achieves 1.15 to 1.58 times the throughput of existing methods when running TPCC and YCSB workloads. 
653 |a Online transaction processing 
653 |a Dynamic random access memory 
653 |a Concurrency control 
653 |a Storage 
653 |a Garbage collection 
653 |a Bandwidths 
653 |a Headers 
653 |a Workload 
653 |a Design 
653 |a Transaction processing 
653 |a Sanitation services 
653 |a Engines 
653 |a Space allocation 
653 |a Performance evaluation 
653 |a Efficiency 
700 1 |a Zhang, Qian 
700 1 |a Xiang Yiwen 
700 1 |a Gong Xueqing 
773 0 |t Electronics  |g vol. 14, no. 10 (2025), p. 2080 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3211939574/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3211939574/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3211939574/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch