An application-aware fragmented database analysis and optimization method

Abstract

The present invention provides an application-insensitive fragmented database analysis and optimization method, which includes the following steps: S1: when the application program executes the query operation of the fragmented database, the statement is sent to the query analyzer and optimized by the client fragmentation driver. S2: The query analyzer and optimizer check and analyze the syntax of the query statement, and judge whether the query is a distributed query or a centralized query according to whether the query content or query conditions contain centralized processing keywords; S3: The query analyzer and optimizer will analyze which data fragments of the fragmented database the query needs to be executed on based on the query conditions and combined with the data fragmentation information stored in the fragmentation manager; S4: The query analyzer and the optimizer notify the fragmentation The query mode of this query of the slice driver; S5: The slice driver operates the slice database through the distributed query executor or the centralized query executor, and then returns the query result to the client.

Description

technical field [0001] The present invention relates to a method for processing a fragmented database, in particular to a method for parsing and optimizing a fragmented database with no application perception. Background technique [0002] As the amount of data increases, the data in a single database table of a relational database will become very large. As the amount of data increases, on the one hand, the performance of accessing the data will be reduced, and on the other hand, the data will be concentrated in one database table. There will also be problems with concurrency support. The sharded database can solve the above problems by sharding the data in the database table according to the hash value or range value of the primary key. But the sharded database brings another problem, that is, the original access operation to a table has now become an access operation to multiple tables in multiple databases, and the ACID characteristics of the database require a new mech...

AI Technical Summary

Problems solved by technology

[0004] Middleware technology: This technology requires fewer changes on the client side and is more versatile, but it also has two disadvantages: First, the access function to the database is subject to the functions of the middleware itself, and various middleware technologies themselves realize The functions are quite different, especially the database function of the middleware itself is very weak, and the support for some operations that require secondary processing, such as combined queries across tables, subqueries, and aggregation functions (such as SUM, AVG), is not optimized enough. Some do not even support it; secondly, every operation on the sharded database needs to go through the middleware, which affects the efficiency on the one hand, and on the other hand, the middleware itself is easily called a bottleneck

Images