Jiajian He

dblp:337/7327 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 60% Memory systems · 40%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems
key-value storage
0.812024
Boosting Write Performance of KV Stores: An NVM - Enabled Storage Collaboration Approach · ICDE 2024
Storage systems › key-value storage
LSM-tree
0.812024
Boosting Write Performance of KV Stores: An NVM - Enabled Storage Collaboration Approach · ICDE 2024
Memory systems
non-volatile memory
0.812024
Boosting Write Performance of KV Stores: An NVM - Enabled Storage Collaboration Approach · ICDE 2024
Memory systems › non-volatile memory
NVRAM
0.812024
Boosting Write Performance of KV Stores: An NVM - Enabled Storage Collaboration Approach · ICDE 2024
Storage systems › flash and SSD › flash memory management › garbage collection
write amplification
0.812024
Boosting Write Performance of KV Stores: An NVM - Enabled Storage Collaboration Approach · ICDE 2024

Methods — techniques the papers use, named apart from their topics

synchronization · 0.8storage collaboration · 0.8ZigZagDB · 0.8
YearPublicationVenuePosition
2024 Boosting Write Performance of KV Stores: An NVM - Enabled Storage Collaboration Approach
abstract
As the most common data structure for key-value stores, LogStructured Merge Tree (LSM-tree) can eliminate random write operations and keep acceptable read performance. However, write stall and write amplification introduced by the leveled compaction of LSM-tree significantly degrade the system performance. The emerging non-volatile memory (NVM) provides byte-addressable access and low-latency data persistence. Integrating DIMM-interface NVM in the design of the LSM-tree can potentially alleviate the write stall and write amplification issue, as the access speed of NVM is several orders of magnitude faster than hard disk drives or flash memory-based solid-state drives. This hybrid storage should be carefully designed, requiring new architectural and key-value structural support. This paper presents ZigZagDB, an NVM-enabled data man-agement scheme for LSM-tree-based key-value stores. ZigZagDB adds additional layers of key-value stores and uses non-volatile memory as the storage media to hold these additional layers of data. The newly designed key-value stores alternately access the data from either SSD or NVM. This ‘ZigZag’ shape of storage collaboration and synchronization can benefit write efficiency and space utilization. By utilizing the NVM with very limited capacity, the redesigned organization of LSM-tree can effectively solve the write stall and write amplification issue. We demonstrate the viability of the proposed ZigZagDB using a set of extensive experiments. Experimental results show that ZigZagDB can significantly reduce the write amplification and boost the throughput in comparison with representative schemes.
Yi Wang 0003, Jiajian He, Kaoyi Sun, Yunhao Dong, Jiaxian Chen, Chenlin Ma, Amelie Chi Zhou, Rui Mao 0001
ICDE2