  Domain Name System (DNS) is a hierarchical distributed naming system for
computers, services, or any resource connected to the Internet. A DNS resolves
queries for URLs into IP addresses for the purpose of locating computer
services and devices worldwide. As of now, analytical applications with a vast
amount of DNS data are a challenging problem. Clustering the features of domain
traffic from a DNS data has given necessity to the need for more sophisticated
analytics platforms and tools because of the sensitivity of the data
characterization. In this study, a cloud based big data application, based on
Apache Spark, on DNS data is proposed, as well as a periodic trend pattern
based on traffic to partition numerous domain names and region into separate
groups by the characteristics of their query traffic time series. Preliminary
experimental results on a Turknet DNS data in daily operations are discussed
with business intelligence applications.
