Hadoop empowers us to solve problems that require intense processing and storage on commodity hardware harnessing the power of distributed computing, while ensuring reliability. When it comes to applicability beyond experimental purposes, the industry welcomes Hadoop with warm heart, as it can query their databases in realistic time regardless of the volume of data. In this post, we will try to run some experiments to see how this can be done. Before you start, make sure you have set up a Hadoop cluster . We will use Hive , a data warehouse to query large data sets and a adequate-sized sample data set, along with an imaginary database of a travelling agency on MySQL; the DB consisting of details about their clients, including Flight bookings, details of bookings and hotel reservations. Their data model is as below: The number of records in the database tables are as: - booking: 2.1M - booking_detail: 2.1M - booking_hotel: 1.48M - city: 2.2K We will write a query t...