A correlation-aware data placement strategy for key-value stores

Citation:
Vilaça R, Oliveira R, Pereira JO.  2011.  A correlation-aware data placement strategy for key-value stores. Proceeedings of the 11th IFIP Distributed Applications and Interoperable Systems (DAIS).

Tertiary Title:

LNCS

Date Presented:

June

Abstract:

Key-value stores hold the unprecedented bulk of the data produced by applications such as social networks. Their scalability and availability requirements often outweigh sacrificing richer data and pro- cessing models, and even elementary data consistency. Moreover, existing key-value stores have only random or order based placement strategies. In this paper we exploit arbitrary data relations easily expressed by the application to foster data locality and improve the performance of com- plex queries common in social network read-intensive workloads. We present a novel data placement strategy, supporting dynamic tags, based on multidimensional locality-preserving mappings. We compare our data placement strategy with the ones used in existing key-value stores under the workload of a typical social network appli- cation and show that the proposed correlation-aware data placement strategy offers a major improvement on the system's overall response time and network requirements.

Citation Key:

vop11

DOI:

10.1007/978-3-642-21387-8_17

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