Internals of PostgreSQL
interdb.jp
interdb.jp
http://www.interdb.jp/blog/pgsql/pg_pacemaker_01/
Which in turn lead me to
https://github.com/gocardless/our-postgresql-setup
And in turn to a fifteen minute talk titled “Zero-downtime Postgres upgrades”
https://www.youtube.com/watch?v=SAkNBiZzEX8
Which was interesting and informative IMO.
After watching that one I was lead further via the YouTube suggested videos to a 45 minute talk titled “Tuning PostgreSQL for High Write Loads”
https://www.youtube.com/watch?v=xrMbzHdPLKM
Which I liked a lot as well.
I think anyone who came here because they are interested in the subject of the OP link might be interested in watching these videos.
Though disclaimer of course: These videos told me things I didn’t know about scaling PostgreSQL, because there is a lot I don’t know about that. But if you already know a lot about that then of course these videos might not be so interesting to you.
http://www.dba-oracle.com/art_so_undoc_parms_p2.htm
PostgreSQL, however, has none of these limitations.
Jonathan Lewis, Guy Harrison and Craig “the Hammer” Shallahammer are infinitely more experienced and insightful.
Christophe Pettus: PostgreSQL Proficiency for Python People - PyCon 2014. https://www.youtube.com/watch?v=0uCxLCmzaG4
[1] https://www.sqlserverinternals.com/publications/
[2] https://www.amazon.com/gp/product/0735658560/ref=as_li_tl?ie...
But if some query takes 5 minutes to run and you can’t speed it up, you need to do something.
I cache a very few select queries that don’t need to be 100% accurate as scan a ton of rows.
1. Needing a consistent (meaning reading off replicas is not fresh enough) data source for reads and writes that happens every request to very high-request site. Think sessions, api rate limiting.
2. Needing a fast store for denormalized data.
Or you have some complex ranking/relationship/aggregation calculations - it might computationally be infeasible for the database, as hard as people worked on its efficiency, to calculate such a query on each request...
wget http://www.interdb.jp/pg/pgsql{01..11}.html http://www.interdb.jp/pg/img/fig-{1..11}-{01..34}.png http://www.interdb.jp/pg/img/fig-4-fdw-{1..7}.png http://www.interdb.jp/pg/img/udc1.jpg
mkdir img
mv *.jpg *.png img/
pandoc -s pgsql{01..11}.html -o internals_pgsql.epub
From there, you should be able to convert it to mobi with Calibre or a similar tool.