News Data Analysis from Facebook Through MongoDB and Hive

摘要

The research aims at doing a comparative study for news data analysis through MongoDB and Hive. The news posts or feeds are gathered from the official Facebook page of The Times of India with the help of Facebook Graph API. The data is stored in a NoSQL database, MongoDB and the Hive data warehouse of Hadoop ecosystem. For better data handling and quick query processing, the data is sharded (partitioned) in MongoDB as well as partitioned in Hive using the date field as the sharding key and the partitioning key in the respective databases. A comparative study is done between the two platforms by running various queries on the data and comparing the execution time. The queries aim to search the news posts on the basis of date ranges, particular keywords in the heading or through any other field like maximum laugh reactions. The study was done on a single machine system for both MongoDB and Hive. The results indicate less execution time for all queries with MongoDB as compared to Hive.