Methods and systems for database optimization

Abstract

This disclosure relates to increasing performance of database queries. A proxy server receives an input query string and a parameter value for first parameter name in the query string. The proxy server determines a second parameter name based on the parameter value and different to the first parameter name. The proxy server then determines an output query string based on the input query string. The output query string comprises a filter clause with a field name and a second field value, the second field value of the output query string being based on the second parameter name. The proxy serverfinally sends the output query string to a database management system to cause the database management system to execute a database query using an execution plan based on the second parameter name inthe output query string.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to Australian Provisional Application 2016901204, filed 31 March 2016, the contents of which are incorporated herein by reference. [0003] This application also claims priority to Australian full application 2016202911 filed 5 May 2016, the contents of which are incorporated herein by reference. technical field [0004] The present disclosure relates to methods and systems for improving the performance of database queries. Background technique [0005] For most companies, it is very important that data is managed in some way or form. For example, shipping companies track shipments, such as their origin, destination, and current location, as well as their customs clearance status. In the logistics industry, the data generated every day is quite large. [0006] figure 1 A pen 101 and paper 102 approach is shown where the logistics manager manually keeps written records of the differe...

AI Technical Summary

Problems solved by technology

In this way, response time may be affected

[0014] Another disadvantage of using files to store data is that the programs used to query the data are complex and error-prone

Doing so creates the problem of deciding between choosing to store an execution plan to avoid optimization delays, and creating a new execution plan that is optimal for a particular query

Since recreating a plan typically uses a large amount of computing power, plan flushing is often impractical and may result in prolonged response times during recreation

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