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...

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Vydané v:Applied sciences Ročník 15; číslo 11; s. 6341
Hlavní autori: Chen, Shuhan, Shen, Congqi, Wu, Chunming
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.06.2025
Predmet:
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
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Shrnutí: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.
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ISSN:2076-3417
2076-3417
DOI:10.3390/app15116341