Application-awareness-free fragmentation database analysis and optimization method

Abstract

The invention provides an application-awareness-free fragmented database analysis and optimization method, which comprises the following steps that S1, when an application program executes query operation of a fragmented database, statements are sent to a query analyzer and an optimizer through a client fragmentation driver; S2, a query analyzer and an optimizer perform grammar check and analysison the query statement, and whether the query is a distributed query or a centralized query is judged according to whether the query content or the query condition contains a centralized processing keyword or not; S3, the query analyzer and the optimizer analyze which data fragments of the fragment database the query needs to be executed according to the query condition in combination with the data fragment information stored in the fragment manager; S4, the query analyzer and the optimizer notify the fragmentation driver of the query mode of this time; and S5, the fragmentation driver operates the fragmentation database through the distributed query executor or the centralized query executor, and returns a query result to the client.

Description

technical field [0001] The invention relates to a method for processing a fragmented database, in particular to an application-insensitive method for analyzing and optimizing a fragmented database. 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 decrease, and on the other hand, the data will be concentrated in one database table. It will also bring about the problem of concurrency support. Fragmented databases 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, and can store the data in one database table into multiple fragmented tables in multiple databases. However, the sharded database brings another problem, that is, the original access operation to one table has now become the access operation to m...

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

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