Spatiotemporal Aspects of Big Data

Saadia Karim; Tariq Rahim Soomro; S. M. Aqil Burney

doi:10.2478/acss-2018-0012

What is it about?

Many frameworks are available for big data analysis. Spatial and temporal data is very important in analysis. In many researches, different frameworks are separately used, but we done a comparison of all available frameworks. Frameworks have been compared on the basis of architectural characteristics and feature attributes.

Why is it important?

We provide a comparison of all available frameworks at one place in our work and Apache Spark and Flink are more efficient frameworks for spatiotemporal big data.

Perspectives

The work is all about frameworks for Spatiotemporal big data. That helps us to understand the efficiency and performance of framework with processes utilization.
Mrs Saadia Karim
Institute of Business Management (IoBM), Karachi Pakistan

This page is a summary of: Spatiotemporal Aspects of Big Data, Applied Computer Systems, December 2018, De Gruyter,
DOI: 10.2478/acss-2018-0012.
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Open Access version
Spatiotemporal Aspects of Big Data
Applied Computer Systems, The Journal of Riga Technical University give me opportunity to publish my work with them and De Gruyter are the publisher of the work. Thanks to all support.

Contributors

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Which frameworks give an efficient result while working with Spatiotemporal big data.

What is it about?

Why is it important?

Perspectives

Resources