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Transparent speculation in geo-replicated transactional data stores

机译:地理复制事务数据存储中的透明猜测

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This work presents Speculative Transaction Replication (STR), a protocol that exploits transparent speculation techniques to enhance performance of geo-distributed, partially replicated transactional data stores. In addition, we define a new consistency model, Speculative Snapshot Isolation (SPSI), a variant of Snapshot Isolation (SI), which shelters applications from the subtle anomalies that arise when using speculative transaction processing techniques. STR provides a form of speculation that is fully transparent for programmers (it does not expose the effects of misspeculations to clients). Since the speculation techniques employed by STR satisfy SPSI, they can be leveraged by application programs in a transparent way, without requiring any source-code modification to applications designed to operate using SI. STR combines two key techniques: speculative reads, which allow transactions to observe pre-committed versions, which can reduce the 'effective duration' of pre-commit locks and enhance throughput; Precise Clocks, a novel timestamping mechanism that uses per-item timestamps with physical clocks, which together greatly enhance the probability of successful speculation. We assess STR's performance on up to nine geo-distributed Amazon EC2 data centers, using both synthetic benchmarks as well as realistic benchmarks (TPC-C and RUBiS). Our evaluation shows that STR achieves throughput gains up to 11 × and latency reduction up to 10× (with respect to non-speculative systems that ensure SI) in workloads characterized by low inter-data center contention. Furthermore, thanks to a self-tuning mechanism that dynamically and transparently enables and disables speculation, STR offers robust performance even when faced with unfavorable workloads that suffer from high misspeculation rates.
机译:这项工作提出了推测性的事务复制(STR),一种用于利用透明投机技术来增强地理分布的部分复制的事务数据存储的性能的协议。此外,我们定义了一种新的一致性模型,推测快照隔离(SPSI),快照隔离(SI)的变体,其从使用推测事务处理技术时出现的微妙异常侵蚀所产生的应用。 STR提供了一种对程序员完全透明的猜测形式(它不会将误操作对客户的影响暴露)。由于STR满足SPSI采用的猜测技术,它们可以以透明的方式通过应用程序利用,而不需要任何源代码修改,该应用程序旨在使用SI操作。 STR组合了两个关键技术:推测读取,允许事务观察预先提交版本,这可以降低预先提交锁的“有效持续时间”并增强吞吐量;精确的时钟,一种使用具有物理时钟的每项时间戳的新型时间戳机制,其共同提高了成功猜测的概率。我们使用合成基准以及现实基准(TPC-C和RUBIS)评估STR的表现最多可达九个地理分布式Amazon EC2数据中心。我们的评估表明,STR在由低间数据中心争用特征的工作负载中实现高达11倍和延迟减少的吞吐量增加11倍和延迟降低的延迟减少10倍。此外,由于动态和透明地启用和禁用猜测的自调谐机制,即使面对遭受高误操作率的不利工作负载,STR也会提供强大的性能。

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