hypopg VS pev2

It works particularly well with pg_stat_statements[0] which tracks execution statistics of all SQL statements executed on your Postgres database.

It leans heavily on HypoPG[1], an excellent extension to determine if PostgreSQL will use a given index without spending resources to create them.

[0] pg_stat_statements: https://www.postgresql.org/docs/current/pgstatstatements.htm...

[1] https://github.com/HypoPG/hypopg

This is an introduction to the hypopg PostgreSQL extension for YugabyteDB 2.15.3.0. Hypopg allows the creation of hypothetical indexes, so indexes that do not really exist. This means this allows you to see what an index would do if it were created, without it actually being created, and therefore not influencing anything on the database. YugabyteDB 2.15.3.0 is a preview version of the YugabyteDB database.

There's a lot of good ecosystem stuff around this:

https://github.com/HypoPG/hypopg

HypoPG is a PostgreSQL extension adding support for hypothetical indexes.

An hypothetical -- or virtual -- index is an index that doesn't really exists, and thus doesn't cost CPU, disk or any resource to create. They're useful to know if specific indexes can increase performance for problematic queries, since you can know if PostgreSQL will use these indexes or not without having to spend resources to create them.

With one approach to using it here: https://www.percona.com/blog/2019/07/22/automatic-index-reco...

This runs in about 250ms. Let's have a look at the explain plan to understand it better. To visualise it, I am using the excellent visualisation tool from Dalibo.

The PEV2 is open source and give you a good visualization. I never used this pgmustard to compare.

https://explain.dalibo.com/

Visualize Your Plan: Visit explain.dalibo.com and paste the generated plan text and query. Then, hit Submit. The tool will generate a visualization of your query plan. Here's an example of the visualization for the fifth attempt version of the query from this post. It shows the different types of scans that were used and how the data gets combined. The duration of each operation is also shown:

You can download the whole analyzer as a simple html file and use it this way. No need to obfuscate or sanitize anything at all.

https://github.com/dalibo/pev2

You might be interested in sites like https://explain.dalibo.com/ which make the output a bit nicer to read. I use these quite often to quickly identify bottlenecks.

PostgreSQL Query Plan Analyzer and Visualizer

I didn’t know about pev2, interesting, checking it now. Did you integrate the component yourself or are you using this hosted page by them: https://explain.dalibo.com/?

IMO it‘s important to get started with indexing. Grab your most frequently used queries and run an EXPLAIN ANALYZE to identify the problems. This tool might help you to understand your execution plans. Once you identified your problems, you can build indexes and check again. Then you should regularly check if your indexes are used.