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Zhanfeng Ma

dblp:325/9793 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none

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

Databases, data management, data science and information retrieval · 2 · 2 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.

Databases, data mining, and information retrieval
2 papers
Transaction processing and concurrency control · 52% Distributed and cloud data management · 43% Database system architecture and tuning · 4%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 7 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Transaction processing and concurrency control
distributed transaction processing
0.712023
Knock Out 2PC with Practicality Intact: a High-performance and General Distributed Transaction Protocol · ICDE 2023
Transaction processing and concurrency control
two-phase commit avoidance
0.712023
Knock Out 2PC with Practicality Intact: a High-performance and General Distributed Transaction Protocol · ICDE 2023
Distributed and cloud data management › cloud database
cloud-native database
0.612022
PolarDB-X: An Elastic Distributed Relational Database for Cloud-Native Applications · ICDE 2022
Distributed and cloud data management › distributed database architecture
distributed relational database
0.612022
PolarDB-X: An Elastic Distributed Relational Database for Cloud-Native Applications · ICDE 2022
Transaction processing and concurrency control › isolation levels
snapshot isolation
0.612022
PolarDB-X: An Elastic Distributed Relational Database for Cloud-Native Applications · ICDE 2022
Transaction processing and concurrency control › commit processing
group commit
0.212023
Knock Out 2PC with Practicality Intact: a High-performance and General Distributed Transaction Protocol · ICDE 2023
Database system architecture and tuning
hybrid transactional and analytical processing
0.212022
PolarDB-X: An Elastic Distributed Relational Database for Cloud-Native Applications · ICDE 2022

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

asynchronous group commit · 1.3paxos · 0.6hybrid logical clock · 0.6MPP engine · 0.6
YearPublicationVenuePosition
2023 Knock Out 2PC with Practicality Intact: a High-performance and General Distributed Transaction Protocol
abstract
Two-phase-commit (2PC) has been widely adopted for distributed transaction processing, but it also jeopardizes throughput by introducing two rounds of network communications and two durable log writes to a transaction's critical path. Despite the various proposals that eliminate 2PC such as deterministic database and access localization, 2PC remains the de facto standard since the alternatives often lack generality (e.g., requiring workloads without branches based on query results). In this paper, we present Primo, a distributed transaction protocol that supports a more general set of workloads without 2PC. Primo features write-conflict-free concurrency control that guarantees once a transaction enters the commit phase, no concurrency conflict (e.g., deadlock) would occur when installing the write-set — hence the prepare phase is no longer needed to account for any potential conflict from any partition. In addition, Primo further optimizes the transaction path using asynchronous group commit. With that, the durability delay is also taken off the transaction's critical path. Empirical results on Primo are encouraging – in YCSB and TPC-C, Primo attains 1.42× to 8.25× higher throughput than state-of-the-art general protocols including Sundial and COCO, while having similar latency as COCO which also employs group commit.
Ziliang Lai, Hua Fan 0002, Wenchao Zhou, Zhanfeng Ma, Feifei Li 0001, Eric Lo 0001
ICDE4
2022 PolarDB-X: An Elastic Distributed Relational Database for Cloud-Native Applications
abstract
Cloud computing is on the rise, which promotes new breeds of database systems to accommodate the cloud environment. The development of cloud-native databases reveals three trends. One is the adoption of multi-datacenter (DC) deployment to survive the downtime of any single site. Another is the separation of computation and storage resources to achieve higher elasticity and scalability. The last is the support of HTAP to eliminate data redundancy and system complexity from heterogeneous databases. To cater to these trends, we design a distributed relational database called PolarDB-X, which is built on top of the cloud-native database PolarDB. It hence inherits many cloud-native features, such as multi-datacenter deployment and elasticity. To achieve cross-DC capability, it leverages Paxos and hybrid logical clock to achieve durability and snapshot-isolation consistency with low coordination costs. For resource elasticity, since the underlying PolarDB supports rapid migration of tenants between nodes, PolarDB-X can quickly scale the cluster to cope with a sudden traffic increase. For HTAP support, with the help of read replicas and a HTAP executor, PolarDB-X can improve the latency and parallelism of analytical queries without impacting concurrently-running TP workloads. Using its MPP engine and an in-memory column index, the efficiency of analytical queries can be further enhanced. PolarDB-X is now a cloud database service at Alibaba Cloud. We have learned many useful lessons from its development and operation, and have incorporated those into our design and analysis.
Wei Cao 0006, Feifei Li 0001, Gui Huang, Jianghang Lou, Dengcheng He, Mengshi Sun, Yingqiang Zhang, Sheng Wang 0011, Xueqiang Wu, Han Liao, Zilin Chen, Xiaojian Fang, Chenghui Liang, Yanxin Luo, Huanming Wang, Songlei Wang, Zhanfeng Ma, Xinjun Yang, Yubin Ruan, Qingda Hu, Junbin Kang
ICDE19