P4DB - The Case for In-Network OLTP

Jasny, Matthias; Thostrup, Lasse; Ziegler, Tobias; Binnig, Carsten

doi:10.1145/3514221.3517825

Cited by 12 publications

(1 citation statement)

References 53 publications

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“…Distributed systems suffer from two major bottlenecks related to ACP [32,62]. First, the long coordinator-side delay prolongs the latency of distributed transactions.…”

Section: Flac Ff For Failure-free Environmentmentioning

confidence: 99%

FLAC: Practical Failure-Aware Atomic Commit Protocol for Distributed Transactions

Pan¹,

Ta²,

Zhang³

et al. 2023

Preprint

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In distributed transaction processing, atomic commit protocol (ACP) is used to ensure database consistency. With the use of commodity compute nodes and networks, failures such as system crashes and network partitioning are common. It is therefore important for ACP to dynamically adapt to the operating condition for efficiency while ensuring the consistency of the database. Existing ACPs often assume stable operating conditions, hence, they are either nongeneralizable to different environments or slow in practice.In this paper, we propose a novel and practical ACP, called Failure-Aware Atomic Commit (FLAC). In essence, FLAC includes three protocols, which are specifically designed for three different environments: (i) no failure occurs, (ii) participant nodes might crash but there is no delayed connection, or (iii) both crashed nodes and delayed connection can occur. It models these environments as the failure-free, crash-failure, and network-failure robustness levels. During its operation, FLAC can monitor if any failure occurs and dynamically switch to operate the most suitable protocol, using a robustness level state machine, whose parameters are finetuned by reinforcement learning. Consequently, it improves both the response time and throughput, and effectively handles nodes distributed across the Internet where crash and network failures might occur. We implement FLAC in a distributed transactional keyvalue storage system based on Google Percolator and evaluate its performance with both a micro benchmark and a macro benchmark of real workload. The results show that FLAC achieves up to 2.22x throughput improvement and 2.82x latency speedup, compared to existing ACPs for high-contention workloads.

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“…Distributed systems suffer from two major bottlenecks related to ACP [32,62]. First, the long coordinator-side delay prolongs the latency of distributed transactions.…”

Section: Flac Ff For Failure-free Environmentmentioning

confidence: 99%

FLAC: Practical Failure-Aware Atomic Commit Protocol for Distributed Transactions

Pan¹,

Ta²,

Zhang³

et al. 2023

Preprint

View full text Add to dashboard Cite

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Knock Out 2PC with Practicality Intact: a High-performance and General Distributed Transaction Protocol

Lai

Fan

Zhou

et al. 2023

2023 IEEE 39th International Conference on Data Engineering (ICDE)

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GraphINC: Graph Pattern Mining at Network Speed

Hussein,

Lerner,

Ryser

et al. 2023

Proc. ACM Manag. Data

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Graph Pattern Mining (GPM) is a class of algorithms that identifies given shapes within a graph, e.g., cliques of a certain size. Any area of a graph can contain a shape of interest, but in real-world graphs, these shapes tend to be concentrated in areas deemed skewed. Because mining skewed areas can dominate GPM computations, the overwhelming majority of state-of-the-art GPM techniques break such areas into many small parts and load balance them across servers. This paper takes a diametrically opposite approach: we suggest a framework that concentrates rather than divides the skewed areas. Our framework, called GraphINC, relies on two key innovations. First, it introduces a new graph partitioning scheme capable of separating the skewed area from the rest of the graph. Second, it offloads the skewed part onto a new class of hardware accelerator, a programmable network switch. We implemented our framework to leverage a commercial 100 Gbps switch and obtained results 6.5 to 52.4× faster thanks to our novel offloading technique.

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P4DB - The Case for In-Network OLTP

Cited by 12 publications

References 53 publications

FLAC: Practical Failure-Aware Atomic Commit Protocol for Distributed Transactions

FLAC: Practical Failure-Aware Atomic Commit Protocol for Distributed Transactions

Knock Out 2PC with Practicality Intact: a High-performance and General Distributed Transaction Protocol

GraphINC: Graph Pattern Mining at Network Speed

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