Recruit Technologies deployed Apache™ Hadoop® in order to reduce the processing time for analyzing ever-increasing data volumes using native distributed data processing capabilities. In the past, data was analyzed and processed separately for each business department. However, in order to provide information according to user needs, the decision was made to consolidate group data and analyze it as a whole. As a result, the data volume increased significantly to an extent that it could not be handled by normal batch processing. It was then that the company decided to deploy Hadoop for distributed processing. Consequently, data was stored in Apache HBase and powered with useful functions, such as enabling a web API from the front-end, estimating segments from user attributes, and sending information according to segments.
With different departments in the Group analyzing data concurrently for their businesses, data volume, data types, and frequency of usage increased. This took its toll on performance, which gradually deteriorated.