Spatiotemporal Aspects of Big Data
Data has evolved into a large-scale data as big data in the recent era. The analysis of big data involves determined attempts on previous data. As new era of data has spatiotemporal facts that involve the time and space factors, which make them distinct from traditional data. The big data with spati...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2018-12-01
|
| Series: | Applied Computer Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/acss-2018-0012 |
| _version_ | 1818587099553595392 |
|---|---|
| author | Karim Saadia Soomro Tariq Rahim Aqil Burney S. M. |
| author_facet | Karim Saadia Soomro Tariq Rahim Aqil Burney S. M. |
| author_sort | Karim Saadia |
| collection | DOAJ |
| description | Data has evolved into a large-scale data as big data in the recent era. The analysis of big data involves determined attempts on previous data. As new era of data has spatiotemporal facts that involve the time and space factors, which make them distinct from traditional data. The big data with spatiotemporal aspects helps achieve more efficient results and, therefore, many different types of frameworks have been introduced in cooperate world. In the present research, a qualitative approach is used to present the framework classification in two categories: architecture and features. Frameworks have been compared on the basis of architectural characteristics and feature attributes as well. These two categories project a significant effect on the execution of spatiotemporal data in big data. Frameworks are able to solve the real-time problems in less time of cycle. This study presents spatiotemporal aspects in big data with reference to several dissimilar environments and frameworks. |
| first_indexed | 2024-12-16T09:03:28Z |
| format | Article |
| id | doaj.art-7621db1eb4d34ab6b35a63c9f216a7c7 |
| institution | Directory Open Access Journal |
| issn | 2255-8691 |
| language | English |
| last_indexed | 2024-12-16T09:03:28Z |
| publishDate | 2018-12-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Computer Systems |
| spelling | doaj.art-7621db1eb4d34ab6b35a63c9f216a7c72022-12-21T22:37:07ZengSciendoApplied Computer Systems2255-86912018-12-012329010010.2478/acss-2018-0012acss-2018-0012Spatiotemporal Aspects of Big DataKarim Saadia0Soomro Tariq Rahim1Aqil Burney S. M.2CCSIS, Institute of Business Management, Karachi, Sindh, PakistanCCSIS, Institute of Business Management, Karachi, Sindh, PakistanCCSIS, Institute of Business Management, Karachi, Sindh, PakistanData has evolved into a large-scale data as big data in the recent era. The analysis of big data involves determined attempts on previous data. As new era of data has spatiotemporal facts that involve the time and space factors, which make them distinct from traditional data. The big data with spatiotemporal aspects helps achieve more efficient results and, therefore, many different types of frameworks have been introduced in cooperate world. In the present research, a qualitative approach is used to present the framework classification in two categories: architecture and features. Frameworks have been compared on the basis of architectural characteristics and feature attributes as well. These two categories project a significant effect on the execution of spatiotemporal data in big data. Frameworks are able to solve the real-time problems in less time of cycle. This study presents spatiotemporal aspects in big data with reference to several dissimilar environments and frameworks.https://doi.org/10.2478/acss-2018-0012apache hadoopbig data analyticsspatiotemporalsamzastormsparkflink |
| spellingShingle | Karim Saadia Soomro Tariq Rahim Aqil Burney S. M. Spatiotemporal Aspects of Big Data Applied Computer Systems apache hadoop big data analytics spatiotemporal samza storm spark flink |
| title | Spatiotemporal Aspects of Big Data |
| title_full | Spatiotemporal Aspects of Big Data |
| title_fullStr | Spatiotemporal Aspects of Big Data |
| title_full_unstemmed | Spatiotemporal Aspects of Big Data |
| title_short | Spatiotemporal Aspects of Big Data |
| title_sort | spatiotemporal aspects of big data |
| topic | apache hadoop big data analytics spatiotemporal samza storm spark flink |
| url | https://doi.org/10.2478/acss-2018-0012 |
| work_keys_str_mv | AT karimsaadia spatiotemporalaspectsofbigdata AT soomrotariqrahim spatiotemporalaspectsofbigdata AT aqilburneysm spatiotemporalaspectsofbigdata |