Optimistic concurrency control by melding trees

Bernstein, Philip A.; Reid, Colin W.; Wu, Ming Chuan; Yuan, Xinhao

doi:10.14778/3402707.3402732

Cited by 16 publications

(1 citation statement)

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“…We propose to embrace semantic batching as a core design principle throughout transaction execution for OLTP systems with optimistic concurrency control (OCC) [34]. OCC is a popular concurrency control protocol due to its low overhead in low-contention settings [2,6,8,9,10,13,17,42,43,36]. However, it has been shown that OCC wastes resources when conflicts are frequent [3].…”

Section: Introductionmentioning

confidence: 99%

Improving optimistic concurrency control through transaction batching and operation reordering

2018

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OLTP systems can often improve throughput by batching transactions and processing them as a group. Batching has been used for optimizations such as message packing and group commits; however, there is little research on the benefits of a holistic approach to batching across a transaction's entire life cycle. In this paper, we present a framework to incorporate batching at multiple stages of transaction execution for OLTP systems based on optimistic concurrency control. Storage batching enables reordering of transaction reads and writes at the storage layer, reducing conflicts on the same object. Validator batching enables reordering of transactions before validation, reducing conflicts between transactions. Dependencies between transactions make transaction reordering a non-trivial problem, and we propose several efficient and practical algorithms that can be customized to various transaction precedence policies such as reducing tail latency. We also show how to reorder transactions with a thread-aware policy in multi-threaded OLTP architecture without a centralized validator. In-depth experiments on a research prototype, an opensource OLTP system, and a production OLTP system show that our techniques increase transaction throughput by up to 2.2x and reduce their tail latency by up to 71% compared with the start-of-the-art systems on workloads with high data contention.

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