Data allocation of large-scale key-value store system using kinetic drives

Xiang Cao, Manas Minglani, David Hung Chang Du

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Nowadays, NoSQL databases become more and more prevalent. As an important category of NoSQL databases, key-value store (KVS) is widely used in many Big Data applications by providing flexible and efficient performance. In a KVS, a key-value pair can be easily accessed by giving a key. Recently, a new Ethernet accessed disk drive called 'Kinetic Drive' was developed by Seagate. This drive can be directly accessed by applications via IP addresses without going through a dedicated storage server. Given the keys from a user, Kinetic Drive can perform key-value pair operations by itself. It can reduce the management complexity, especially in large-scale deployment. Given a set of Kinetic Drives in a data center, it is important to manage the key-value pairs and store them in an organized way. In this paper, we investigate how to allocate data on a large-scale key-value store system using Kinetic Drives. We show the tradeoff among various design factors. We investigate key indexing schemes and allocate data on drives accordingly. We propose efficient approaches to migrate data among drives. We carry out performance evaluation that shows our approaches can handle various key distributions well.

Original languageEnglish (US)
Title of host publicationProceedings - 3rd IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages60-69
Number of pages10
ISBN (Electronic)9781509063185
DOIs
StatePublished - Jun 8 2017
Event3rd IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2017 - San Francisco, United States
Duration: Apr 6 2017Apr 10 2017

Publication series

NameProceedings - 3rd IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2017

Other

Other3rd IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2017
Country/TerritoryUnited States
CitySan Francisco
Period4/6/174/10/17

Bibliographical note

Funding Information:
This work has been supported by NSF I/UCRC Center for Research in Intelligent Storage (CRIS) and the National Science Foundation (NSF) under awards 1305237, 1421913, 1439622, and 1525617.

Publisher Copyright:
© 2017 IEEE.

Keywords

  • Data Management
  • Key-Value Store
  • Kinetic Drive

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