The invention discloses a big-data 
parallel computing method and 
system based on distributed columnar storage. Data which is most often accessed currently is stored by using the 
NoSQL columnar storage based on a memory, the cache optimizing function is achieved, and quick 
data query is achieved; a distributed cluster architecture, 
big data storing demands are met, and the dynamic 
scalability of the data storage capacity is achieved; combined with a 
parallel computing framework based on Spark, the 
data analysis and the parallel operation of a business layer are achieved, and the computing speed is increased; the real-
time data visual experience of the large-screen rolling analysis is achieved by using a graph and diagram engine. In the big-data 
parallel computing method and 
system, the 
memory processing performance and the parallel computing advantages of a distributed 
cloud server are given full play, the bottlenecks of a 
single server and serial computing performance are overcome, the redundant 
data transmission between data nodes is avoided, the real-
time response speed of the 
system is increased, and quick big-
data analysis is achieved.