bigDS is a library of scalable big data science algorithms based on spark. The library will cover the fields of linear algebra, statistics, data mining, machine learning, data visualization, as well data science related algorithms. Developers can easily untilize the liabray to build up their high level big data applicaitons.

The bigDS library will be more focused on implementing distributed Spark algorithms instead of Spark itself. It is based on Spark and its corresponding components like MLlib, GraphX, Spark Streaming, etc. Some basic algorithms in bigDS can also be viewed contribution to Spark components like MLlib and GraphX, because we will add new or improved algorithms in Spark when necessary.

The direct user of bigDS would be advanced big data science applications in fields like business intelligence, bioinformatics, gene mining, geology mining, physics, etc.