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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Automated Data Partitioning for Highly Scalable and Strongly Consistent Transactions
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Automated Data Partitioning for Highly Scalable and Strongly Consistent Transactions

机译:自动数据分区,实现高度可扩展和高度一致的交易

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摘要

Modern transactional processing systems need to be fast and scalable, but this means many such systems settled for weak consistency models. It is however possible to achieve all of strong consistency, high scalability and high performance, by using fine-grained partitions and light-weight concurrency control that avoids superfluous synchronization and other overheads such as lock management. Independent transactions are one such mechanism, that rely on good partitions and appropriately defined transactions. On the downside, it is not usually straightforward to determine optimal partitioning schemes, especially when dealing with non-trivial amounts of data. Our work attempts to solve this problem by automating the partitioning process, choosing the correct transactional primitive, and routing transactions appropriately.
机译:现代的事务处理系统需要快速且可扩展,但这意味着许多此类系统已为弱一致性模型做好了准备。但是,通过使用细粒度的分区和轻量级的并发控制,可以避免多余的同步和其他开销(如锁管理),从而实现所有强大的一致性,高可伸缩性和高性能。独立事务就是这样一种机制,它依赖于良好的分区和适当定义的事务。不利的一面是,确定最佳的分区方案通常并不容易,尤其是在处理大量数据时。我们的工作试图通过自动化分区过程,选择正确的事务基元并适当地路由事务来解决此问题。

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