Demonstration of kite: A scalable system for microblogs data management

Amr Magdy, Mohamed F Mokbel

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

5 Scopus citations

Abstract

Motivated by its wide availability and richness, there have been a plethora of recent work in querying, analyzing, and visualizing microblogs (see [3] for a brief survey). Examples of microblogs include tweets, online reviews, and comments on news websites. Unfortunately, existing work in microblog lacks data management tools that provide the necessary infrastructure to support efficient storage, indexing, and retrieval of microblogs. Hence, researchers, developers, and practitioners who need to process microblogs for their own purposes would need to either build their own ad-hoc techniques [5] or use any of existing general purpose big data engines, e.g., Spark, as their backbone [4]. Relying on ad-hoc techniques does not scale for large data sizes. Meanwhile, existing general purpose big data engines are built in a generic way to support various query workloads. Thus, they are not equipped to support the characteristics of microblogs [2], and so they are missing necessary infrastructure like supporting the real-Time indexing and promoting temporal, spatial, and ranking queries. This results in sub par performance when supporting microblogs.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017
PublisherIEEE Computer Society
Pages1383-1384
Number of pages2
ISBN (Electronic)9781509065431
DOIs
StatePublished - May 16 2017
Event33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, United States
Duration: Apr 19 2017Apr 22 2017

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other33rd IEEE International Conference on Data Engineering, ICDE 2017
CountryUnited States
CitySan Diego
Period4/19/174/22/17

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