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.