One thing you have to realize is that once you get a little advanced, you have to get to the details of the single SQL implementations, it's not about SQL but about Postgres.
I've found these books really valuable
# SQL Performance Explained Everything Developers Need to Know about SQL Performance
This book fundamentally talks about how to effectively use and leverage the SQL indices. Talks about all the important implementations (Postgres, MySQL, Oracle, SQL Server).
# Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
This book gets mentioned a bunch around here and for a good reason. There aren't too many concrete resources on making your systems "webscale" and this one is really good.
# PostgreSQL 9.0 High Performance
Discusses all the different settings and tweaks you can do in Postgres. It's crazy how much of a perf gain you can get just by twiddling the parameters of the database, i.e. all the tricks you can do when the single instances are bottle necks.
There's a similar book for MySQL https://www.amazon.com/High-Performance-MySQL-Optimization-R...
# PostgreSQL 9 High Availability Cookbook
Discusses how do you go from 1 Postgres instance to 1+ instance. Talks about replication, monitoring, cluster management, avoiding downtime etc i.e. all the tricks you can do to manage multiple instances. Again there's a similar book for MySQL https://www.amazon.com/MySQL-High-Availability-Building-Cent...
Last but not least check out the postgres documentation, people consider it a standard of what good documentation looks like https://www.postgresql.org/docs/9.6/static/index.html
Also last but not least, read up on relational algebra (the foundation of SQL) https://en.wikipedia.org/wiki/Relational_algebra. I've always found SQL to be extremely verbose (the syntax reminds me of idk COBOL or smth) but there's another query language called Datalog, that's for our purposes similar to SQL but the syntax is much more legible.
E.g. check out these snippets from these slides (page 29) (and check out the whole class too)
s(X) <- p(X,Y).
s(X) <- r(Y,X).
t(X,Y,Z) <- p(X,Y), r(Y,Z).
w(X) <- s(X), not q(X).
CREATE VIEW s AS (SELECT a FROM p)
(SELECT b FROM r);
CREATE VIEW t AS
SELECT a, b, c
FROM p, r
WHERE p.b = r.a,
CREATE VIEW w AS
There used to be an issue where users hitting their quota couldn't delete files since for some reason deleting a file meant creating a file somehow. The trick was to find some reasonably large file and `echo 1 > large_file` which truncates the file and frees up enough space that you can begin removing files. Maybe this kind of trick could help you guys.
That said, it's inadvisable to run a database on a btree file system like ZFS or btrfs if you're keeping an eye on the write performance.
cf Postgres 9.0 High Performance by Gregory Smith (https://www.amazon.com/PostgreSQL-High-Performance-Gregory-S...)
Query analysis tool http://explain.depesz.com
The mailing list http://www.postgresql.org/list/pgsql-performance/
Greg Smith's book http://www.amazon.com/PostgreSQL-High-Performance-Gregory-Sm...
#postgresql on freenode.net
I haven't had a chance to finish it. But it does look like the author knows what he's talking about.
The first 2 are bottom-up, structured approaches to benchmarking low-level system performance with an emphasis on *nix, and building up to database performance characterization and investigation. Despite their names, both have a lot of great general, non-product-specific use.
The third I include because it is the only MSSQL-specific book I have on the subject, and it sounds like you're in Windows Land. It has some real gems, but little coverage of the OS or methodology. I cannot over-emphasize how important that methodology is.
Make sure you learn how to use the Resource Monitor, and SQL Profiler.
If you want to chat about it more, I'm justinpitts at google's mail.
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