Analysis of Techniques to Retrieve Big Database
| dc.contributor.advisor | Jain, Lokesh | |
| dc.contributor.author | Puri, Shivani | |
| dc.date.accessioned | 2019-10-10T04:58:03Z | |
| dc.date.available | 2019-10-10T04:58:03Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | In today’s world there are large amount of data which need to be processed with big databases. From the past years, there is plethora of organisations that has adopted many types of non-relational database. The goal of this research is to implement techniques to retrieve big database for the big datasets and investigate the performance of the big database techniques on CPU utilization and high-performance computing software enabling switching the SQL database with NoSQL database. In this research mainly concerns on the new technology of NoSQL database i.e. MongoDB, HadoopDB. Performance comparison of two big data techniques is carried out. The result found that Aggregation technique consumes less execution time than MapReduce technique and more efficient with MongoDB database where as MapReduce technique has less efficient with HadoopDB. Aggregation technique also produces fine relevant information results with less CPU utilization. The result also shows that MongoDB has capability to switch SQL databases as compare to HadoopDB. | en_US |
| dc.identifier.uri | http://krishikosh.egranth.ac.in/handle/1/5810130583 | |
| dc.keywords | Big Data, MongoDB, HadoopDB, Aggregation, MapReduce | en_US |
| dc.language.iso | en | en_US |
| dc.pages | 58 | en_US |
| dc.publisher | Punjab Agricultural University, Ludhiana | en_US |
| dc.research.problem | Analysis of Techniques to Retrieve Big Database | en_US |
| dc.sub | Information Technology | en_US |
| dc.subject | null | en_US |
| dc.theme | Analysis of Techniques to Retrieve Big Database | en_US |
| dc.these.type | M.Tech. | en_US |
| dc.title | Analysis of Techniques to Retrieve Big Database | en_US |
| dc.type | Thesis | en_US |