In my previous blog post, I explained how to optimize EXPLAIN ANALYZE. I demonstrated how to reduce its overhead from 29.82[%] to 5.33[%] in just three steps.

While the analysis at the end of that post was brief and a bit superficial, in this blog, I will perform a deeper analysis to gain insights for further improvements.

1-Line Abstract: Cut the overhead of EXPLAIN ANALYZE by roughly 82.1[%].

I show a tip of autovacuum management.

As frequently mentioned, the table bloat problem is one of the most annoying things in managing PostgreSQL. Several things can cause that problem, and Autovacuum is one of them.

On March 8th, Datadog totally paralyzed around the world and it continued a few days.

I was interested in the caurses of that failure from the point of view of my pure engineering interest. However, Datadog have not disclosed anything yet.

I list up three kinds of technologies I am interested in except computing. If I were young, I would try to dive into these fields.

I’ve just released pg_plan_inspector that is a framework to monitor and improve the performance of PostgreSQL using Machine Learning methods.

One movie is worth a thousand words. Watch this movie.

I made a PostgreSQL’s module called shutdown_db using weekend time.

This module emulates the Oracle’s shutdown commands by controlling access for each DB.

pgindent maintains the uniform layout style of postgresql related source code.

My first Chinese book has been published on 1st June.

I made a program to calculate ‘A * B mod N’, where A, B and N are 64 bit integers.

Main problem is to avoid overflow when calculate ‘A * B’.

I searched a while and finally decided to use the interleaved modular multiplication method, which is used in the feild of electric circuit design.

I found some bugs when I tested corner cases, so I have to fix them [2018.9.2]. I think I’ve fixed them [2018.9.3]. I’ve just improved it! [2018.9.5]

The program is shown below: