Abstract: Cassandra is one of the universal databases,and it’s also specified as the top level project by the Apache.For the Cassandra distributed database system,a large number of write requests will cause excessive and dispersed SStable structures and high data redundancy,causing low efficiency to the user read requests.This problem can be solved by the local data consolidation mechanism triggered automatically by the system or by the overall data consolidation mechanism triggered by the human intervention.However,on one hand,the irrational timing automatical partial merger process will seriously reduce the performance of the read operation requested by the user;on the other hand,the long-time human overall data consolidation process will occupy a large number of system resources,which will severely restrict the overall performance of the corresponding system.To solve this problem,we presented an efficient and dynamic management mechanism.Firstly,appropriate implementation strategies are developed to the time of the merger,the file involved in the merger and the merge process by monitoring system environment and managing the data according to the time and size.Secondly,the impact of the consolidation process on system performance is reduced by reducing the data combination time through specific optimization methods.The final result shows that this data management system optimizes the Cassandra database consolidation process and ultimately enhances the response speed for the read request.

Key words: Cassandra database,Dynamic data management,Consolidation strategy,Response speed for the read request