Research And Application Of Row Column Data Storage Access

In the traditional dynamic random access memory(DRAM)and the memory constructed by nonvolatile memory,there is only row data access mode.However,in the case of special type of access patterns,the number of row accesses becomes excessive,which is not ideal in the efficiency of data acquisition.Just as it happens,the columnar access of memory can effectively solve the problem in this scenario.By building two kinds of accesses into two terminal memory,we can effectively deal with different those two scenarios.Combined with the effectiveness of two terminal memory access,aiming at some shortcomings in the calculation and judgment of row and column access,an effective calculation model is proposed in this thesis.According to the physical structure of two terminal storage on the hardware level and the lack of effective row and column discrimination on the software level,a recognition algorithm is proposed.The main work of this thesis is as follows1.This paper analyzes different ways of data storage and access,models the different ways of data accesses,and thesis the corresponding access calculation model.The corresponding results are obtained through different calculation formulas,and the double end access efficiency is the best through the comparative analysis of the results.Finally,the validity of the method is verified by our experimental data.2.Design the recognition algorithm of SQL statement for different database application types.According to the different application types of database,online transaction processing application corresponds to the row oriented storage access of database.At the same time,the application of OLAP corresponds to the columnar storage access of database.According to the characteristics of SQL statements,different keyword categories are divided,and the recognition algorithm is designed.The access mode and application type of SQL statements are recognized by the algorithm.Finally,the effectiveness of the algorithm is measured and analyzed.3.Design fuzzy search application.In the application of massive data,fuzzy search is also an important application scenario.Columnar storage can save the same type of data,which is conducive to the fuzzy query of massive data.By crawling the data of Jingdong Mall as the data source,applying effective query keywords through fuzzy query,and highlighting the search keywords to display all relevant data information,the fast search is completed.