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Distributed Data Persistency

Apostolos Kokolis, Antonis Psistakis, Benjamin Reidys, Jian Huang, Josep Torrellas

2021Year
7Citations
4Top-tier citations

Abstract

Distributed applications such as key-value stores and databases avoid frequent writes to secondary storage devices to minimize performance degradation. They provide fault tolerance by replicating variables in the memories of different nodes, and using data consistency protocols to ensure consistency across replicas. Unfortunately, the reduced data durability guarantees provided can cause data loss or slow data recovery. In this environment, non-volatile memory (NVM) offers the ability to attain both high performance and data durability in distributed applications. However, it is unclear how to tie NVM memory persistency models to the existing data consistency frameworks, and what are the durability guarantees that the combination will offer to distributed applications.

In this paper, we propose the concept of Distributed Data Persistency (DDP) model, which is the binding of the memory persistency model with the data consistency model in a distributed system. We reason about the interaction between consistency and persistency by using the concepts of Visibility Point and Durability Point. We design low-latency distributed protocols for DDP models that combine five consistency models with five persistency models. For the resulting DDP models, we investigate the trade-offs between performance, durability, and intuition provided to the programmer.

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