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Workload Aware Replicated Datapartitioning for Twitter

by Shanty S.R., Aby Abahai T., Eldo P. Elias
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 130 - Number 4
Year of Publication: 2015
Authors: Shanty S.R., Aby Abahai T., Eldo P. Elias

Shanty S.R., Aby Abahai T., Eldo P. Elias . Workload Aware Replicated Datapartitioning for Twitter. International Journal of Computer Applications. 130, 4 ( November 2015), 21-28. DOI=10.5120/ijca2015906845

@article{ 10.5120/ijca2015906845,
author = { Shanty S.R., Aby Abahai T., Eldo P. Elias },
title = { Workload Aware Replicated Datapartitioning for Twitter },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 130 },
number = { 4 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 21-28 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2015906845 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:24:28.418116+05:30
%A Shanty S.R.
%A Aby Abahai T.
%A Eldo P. Elias
%T Workload Aware Replicated Datapartitioning for Twitter
%J International Journal of Computer Applications
%@ 0975-8887
%V 130
%N 4
%P 21-28
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

Most of the queries in twitter include multiuser operations. When a user login to twitter it requests the most recent tweets of whom he follows. These data may be present in different servers. The expense of these queries depends on how the data is partitioned. Existing solution for data partitioning involve hash or graph based partition. In this paper a new method for reducing the interaction between the servers are proposed. For this the data is partitioned such that most of the users that a user interacts are placed on the same partition. In addition to data partition selective replication is also implemented in the proposed approach. The data about the users that are requested most are replicated more than the other users. Experimental analysis indicates that the proposed technique provides significant improvements in the quality of the partitions, especially under low replication ratios.

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Index Terms

Computer Science
Information Sciences


Data partitioning Selective replication Social network Twitter Cassandra.