Combining Segmentation Graphs And B+ Tree Cloud Data Indexing Mechanism Research

With the rapid development of the Internet and computer technology,e-commerce,Internet,social networking,resource data in the areas of rapid expansion in scientific computing,data age has arrived.Cloud computing as a new form of mass data storage,management,analysis,models,has been widely used and has become base platform and supporting technologiesfor big data.Traditional relational database index in solving unstructured data have a serious bottleneck,unable to get good extensions.In order to improve the efficiency of data management and query,in this paper,data indexing and retrieval algorithms is studied.First,because of the problem of basic bitmap index has big data storage space and low efficiency,this paper presents a cloud data index combination of segmented and b + tree(BBI).Segmented bitmapdivides data into several segments based on a certain number when the index is created,bitmap index by segment,the decision factor of the index data quantity is changed from the range of attribute values to the product of the segments and certain number,which greatly reduces the amount of indexed data.Index using theadvantages of centralized architecture to global sort of segmented index data and build indicated bitmap,records the approximate location of tuples that Sort value corresponded.Index combined with distributed architecture to built b + tree for index data sort value stored on single data node,evading every non-results data ergodicity when data retrieval,which significantly improves the efficiency of data retrieval.Secondly,in order to increase the availability and stability of BBI index,index maintenance strategies for BBI index is designed,when have tuple delete,insert or update operations depending on the property of the tuples to modify the b + tree structure and indicated bitmap,operational processes and algorithms are given.On the other hand,the data retrieval algorithm based on BBI index is presented,which is divided into single condition search and compound condition search.Finally,strict experimental performance of BBI index is designed for testing.In the retrieval algorithm,the response time and the query throughput of the index are tested in two aspects;At the same time,in the index maintenance strategy,the tuple insertion,deletion and data update were tested respectively,and the average value of the response time is taken as the test data.The experiments show that the BBI index is a kind of cloud data indexing mechanism with better performance.