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Zhan-Feng Ma

dblp:224/6811 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

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

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

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.

Databases, data mining, and information retrieval
1 paper
Database system architecture and tuning · 50% Transaction processing and concurrency control · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Transaction processing and concurrency control › OLTP
in-memory transaction processing
0.312018
BTrim - Hybrid In-Memory Database Architecture for Extreme Transaction Processing in VLDBs · Proc. VLDB Endow. 2018
Storage systems › buffer management
buffer cache management
0.112018
BTrim - Hybrid In-Memory Database Architecture for Extreme Transaction Processing in VLDBs · Proc. VLDB Endow. 2018

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

in-memory row store · 0.7data tiering · 0.7
YearPublicationVenuePosition
2018 BTrim - Hybrid In-Memory Database Architecture for Extreme Transaction Processing in VLDBs
abstract
To address the need for extreme OLTP performance on commodity multi-core hardware supporting large amounts of memory, SAP ASE is re-architected to tightly integrate an In-Memory Row Store (IMRS) within the existing database engine. The IMRS is both a store and a caching layer to host "hot" rows in-memory, in a row-oriented format. The IMRS is an extension to the traditional buffer-cache which deals with data in a page-oriented storage format (referred to as the page-store). Data in individual tables marked as IMRS-enabled can be fully memory-resident or can straddle the page store and the IMRS. Cold data in the IMRS is organically identified, harvested, and "packed" back to the page store. SQL statements and transactions can access data transparently from both stores for the same table. All Transact-SQL capabilities and language constructs are supported with no application or stored procedure code changes required. Full durability for in-memory data is provided, including support for backup and restore of database archives and periodic transaction dumps. The high-level system design supporting this architecture, along with experimental results and performance benefits is presented.
Aditya Gurajada, Dheren Gala, Amit Pathak, Zhan-Feng Ma
Proc. VLDB Endow.5