实践经验报告:Cassandra+:在Cassandra中权衡一致性、延迟和容错性

Guo-Shu Gao, K. Konwar, Juan Mantica, Haochen Pan, D. Kish, Lewis Tseng, Zezhi Wang, Yingjian Wu
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引用次数: 1

摘要

数据的指数级增长将行业推向了新型的数据管理系统,如NoSQL数据库。我们的目标是扩展NoSQL,重点关注它作为分布式键值存储(KV-store)的应用程序。现有的生产就绪系统通常只提供一致性和容错的概率保证,如果集群有严重的时钟漂移,可能会违反它们的正确性属性。我们的系统Cassandra+通过提供更多的一致性和容错选择来解决这些问题。我们通过在Cassandra(业界最流行的nosql之一)中实现理论上的分布式共享内存(DSM)来构建Cassandra+。在本文中,我们分享了在现实世界系统中适应和实现DSM算法的经验。我们希望我们的经验和结果能让人们更好地理解DSM和所涉及的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical Experience Report: Cassandra+: Trading-Off Consistency, Latency, and Fault-tolerance in Cassandra
The exponential growth of data has pushed the industry towards new types of data management systems such as NoSQL database. Our goal is to augment NoSQL, with the focus on its application as a distributed key-value store (KV-store). Existing production-ready systems often provide only probabilistic guarantees on consistency and fault-tolerance, and may violate their correctness properties if a cluster has severe clock drift. Our system Cassandra+ addresses these issues by providing more choices for consistency and fault-tolerance. We build Cassandra+ by implementing theoretical distributed shared memory (DSM) in Cassandra, one of the most popular NoSQLs in the industry. In this paper, we share our experience in adapting and implementing DSM algorithms into a real-world system. We hope our experience and results allow a better understanding of the DSM and the tradeoffs involved.
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