eprintid: 11129
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/11/29
datestamp: 2023-11-10 03:25:40
lastmod: 2023-11-10 03:25:40
status_changed: 2023-11-10 01:14:32
type: conference_item
metadata_visibility: show
creators_name: Ahmad, R.
creators_name: Zakaria, M.N.
creators_name: Abdullahi, A.U.
title: Hadoop MapReduce's InputSplit based Indexing for Join Query Processing
ispublished: pub
keywords: Control systems; Database systems; Indexing (of information); Query processing, Hadoop MapReduce; Indexing approaches; Indexing techniques; Processing approach; Runtimes, Indexing (materials working)
note: cited By 1; Conference of 9th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2019 ; Conference Date: 29 November 2019 Through 1 December 2019; Conference Code:159323
abstract: Join queries are amongst the most used form of queries, where records from two or more tables or files are retrieved in order to have a comprehensive, comparable and contrasted view of certain data. However, the processing of the join queries come with higher overhead since all the tables or files involved in the process have to be considered. It can easily be imagined how much the overhead could become when data contained in such tables/files is big data. The use of indexing on Hadoop and its abstractions have resulted in improved performance when processing queries. However, even with the use of some of the indexing approaches, the processing of join query indicates higher overhead, except when the amount of data to processed is reduced by the indexing techniques before the query processing even get started. One indexing technique that ensures this, is the InputSplit based index. This paper showcases how InputSplit based indexing can be implemented in Hadoop MapReduce as well the experimental results of running a join query using such index. The results show at least 50 reduction in runtime when compared to both normal Hadoop MapReduce and Clustered Index based on blockIds query processing approaches. © 2019 IEEE.
date: 2019
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084312161&doi=10.1109%2fICCSCE47578.2019.9068559&partnerID=40&md5=3d99a4359ec8de94a0728a053c23d1ee
id_number: 10.1109/ICCSCE47578.2019.9068559
full_text_status: none
publication: Proceedings - 9th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2019
pagerange: 131-135
refereed: TRUE
isbn: 9781728135007
citation:   Ahmad, R. and Zakaria, M.N. and Abdullahi, A.U.  (2019) Hadoop MapReduce's InputSplit based Indexing for Join Query Processing.  In: UNSPECIFIED.