Efficient Product Inventory Maintenance for Black Friday Sale via Spark Big Data System
| dc.contributor.author | Kulkarni, Chhaya | |
| dc.contributor.author | Rajan, Kavitha Loganathan Sundara | |
| dc.contributor.author | Wang, Xin | |
| dc.date.accessioned | 2020-03-10T14:54:24Z | |
| dc.date.available | 2020-03-10T14:54:24Z | |
| dc.description.abstract | Black Friday fever attracts customers from far and wide. Excitement also leads to frantic chaos for e-commerce websites. To help ease the burden on the e-commerce companies managing the traffic as well as inventory is of utmost importance. An environment that emulates the Black Friday sale can be created well using Spark Streaming component. Spark SQL and Dataframes can be used to carry out operations and store data. We have attempted to see how we can effectively handle the inventory using Spark components. | en_US |
| dc.description.sponsorship | The hardware in the UMBC High Performance Computing Facility (HPCF) is supported by the U.S. National Science Foundation through the MRI program (grant nos. CNS–0821258, CNS–1228778, and OAC–1726023) and the SCREMS program (grant no. DMS–0821311), with additional substantial support from the University of Maryland, Baltimore County (UMBC). We would like to extend special thanks to our instructor Dr. Jianwu Wang for supporting us. | en_US |
| dc.description.uri | http://hpcf-files.umbc.edu/research/papers/IS789_Project_Report-HPCF-2019-30.pdf | en_US |
| dc.format.extent | 11 pages | en_US |
| dc.genre | reports | en_US |
| dc.identifier | doi:10.13016/m2qem2-aomr | |
| dc.identifier.citation | Chhaya Kulkarni, Kavitha Loganathan Sundara Rajan, Xin Wang, Efficient Product Inventory Maintenance for Black Friday Sale via Spark Big Data System ,http://hpcf-files.umbc.edu/research/papers/IS789_Project_Report-HPCF-2019-30.pdf | en_US |
| dc.identifier.uri | http://hdl.handle.net/11603/17517 | |
| dc.language.iso | en_US | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Information Systems Department Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.subject | UMBC IS 789 (Big Data Fundamentals and Techniques) | en_US |
| dc.subject | UMBC High Performance Computing Facility (HPCF) | |
| dc.title | Efficient Product Inventory Maintenance for Black Friday Sale via Spark Big Data System | en_US |
| dc.type | Text | en_US |