[GSoC] Summery of pg performance farm

From: Hongyuan Ma <mahongyuan1997(at)gmail(dot)com>
To: Mark Wong <mark(at)2ndquadrant(dot)com>, sfrost(at)snowman(dot)net
Cc: pgsql-hackers(at)postgresql(dot)org, pgsql-hackers(at)lists(dot)postgresql(dot)org
Subject: [GSoC] Summery of pg performance farm
Date: 2018-08-19 07:53:55
Message-ID: CAJSVFNCqT2CwOdZaXyXWa9_9+7UP2LdWA4Bi3uj3B3X00fpZXw@mail.gmail.com
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Hello monters and hackers,

This is a late summary of pg performance farm in gsoc. Although it is not
yet perfect, but it has began to take shape.

1. The implementation of the basic test results upload interface to ensure
that the upload operation for the atomic level (including different client
numbers in different modes (rw, ro) corresponding to the results of the
value).

2. Implementation of the data report related to the list page. Compare each
metrics whith the previous results. If any of the metrics are a 5%
improvement( or regression), there is one aspect that is progressive (or
regressive). This means there may be aspects of "improvement", "regression"
and "status quo" in one test result.This is the report List page for an
example: http://140.211.168.111/#/machineInfo/pmJEjJjSk3WREM3Q

3.The details page of the test report is implemented. The test results in
the "read only" and "read & write" mode of this report are detailed in this
page, as well as the link of previous report and other details.
Here is an example:
http://140.211.168.111/#/detailInfo/KScN58FCUWRD2fuC2R7VeY

4. A simple user center was implemented to allow users to browse the owning
machine and apply for a new machine (I originally planned to access the
community's user information interface at logon verification, but this
seems to require some waiting...So this part is temporarily not present.)
5. Implement the action of approvaling machine and sending notification
email in django admin.

We plan to add some useful features and write test cases to pg performance
farm in the future. If anyone has any good ideas or opinions. Please feel
free to email my mentors and me. And You are also welcome to leave a
message on this issue page: https://github.com/PGPerfFarm/pgperffarm/issues

Best Regards,
Hongyuan Ma

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