Intelligent Transaction Scheduling to Enhance Concurrency in High-Contention Workloads

Concurrency control (CC) scheme based on transaction decomposition has significantly enhanced the concurrency performance of multicore in-memory databases, surpassing traditional CC schemes such as two-phase locking (2PL) or optimistic concurrency control (OCC), particularly in high-contention scena...

Full description

Saved in:
Bibliographic Details
Published in:Applied sciences Vol. 15; no. 11; p. 6341
Main Authors: Chen, Shuhan, Shen, Congqi, Wu, Chunming
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.06.2025
Subjects:
Concurrency control
Critical path
Decomposition
deep reinforcement learning
high-contention workloads
Horticulture
in-memory database
Online transaction processing
Protocol
Scheduling
transaction decomposition
transaction dependency
Workloads
ISSN:2076-3417, 2076-3417
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Concurrency control (CC) scheme based on transaction decomposition has significantly enhanced the concurrency performance of multicore in-memory databases, surpassing traditional CC schemes such as two-phase locking (2PL) or optimistic concurrency control (OCC), particularly in high-contention scenarios. However, this performance improvement introduces new challenges, as balancing transaction dependency constraints with enhanced concurrency optimization remains a persistent issue, especially with the increased number of concurrent client requests, which can lead to complex transaction dependencies. To address these challenges, we propose Dynamic Contention Scheduling (DCoS), a novel method that enhances transaction concurrency via a dual-granularity architecture. DCoS integrates a deep reinforcement learning (DRL)-based executor to schedule high-contention transactions while preserving dependency correctness. DCoS employs a one-shot execution model that enables fine-grained scheduling in high-contention scenarios, while retaining lightweight in-partition execution under low-contention conditions. The experimental results on both micro- and macro-benchmarks demonstrate that DCoS achieves a throughput up to three times higher than state-of-the-art CC protocols under high-contention workloads.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app15116341