创建具有基于其他表列值生成的布尔列的表？

Question

I have tables A, B, C with millions of rows each. Tables B and C reference table A. The tables are mainly used for one query with multiple filters but only one of those filters vary between queries. since the constant parameters are adding significant time to the query execution time, I was wondering if there is a way to precompute these params into a new table. I was looking at materialized views but the issue is that the computed type I want will be different from the original column type. To explain I will give an example.

lets say these tables represent a book store database. Table A contains general information and table B contain multiple codes for each book to indicate what categories they fall under such as 406, 678, 252.. . I'm building a query to search for books that only fall under 3 of those categories. The variable here is the keyword search in the discreption of the book. I will always need books under those 3 categories (codes) so these are constants.

What I want to do is create a table where it will have a column that tells me whether a given serial falls under those 3 codes or not. this can be done with a boolean type. I don't want to have to join these table and filter for these 3 codes (and more in the real scenario) for every query.. As I understand materialized views can't have generated fields?

What do you think is a good solution here?

Answer 1

You have multiple options.

Partial Index

PostgreSQL allows you to create an index with a where clause like so:

create index tableb_category on tableb (category)
where category in (406, 678, 252);

Create a view for those categories:

create view v_books_of_interest
as
select tablea.*, tableb.*
from tablea
inner join table b
   on tableb.bookid = tablea.bookid
   and tableb.category in (406, 678, 252);

Now, your queries can use this book_of_interest rather than books. Frankly, I would start with this first. Query optimization with the right indexes goes a long way. Millions of rows in multiple table are manageable.

Materialized view

create materialized view mv_books_of_interest
as
select tablea.*, tableb.*
from tablea
inner join table b
   on tableb.bookid = tablea.bookid
   and tableb.category in (406, 678, 252);
with no data;

Periodically, run a cron job (or the like) to refresh it:

refresh materialized view mv_books_of_interest;

Partitioning data

https://www.postgresql.org/docs/9.3/ddl-partitioning.html will get you started. If your team is on-board with table inheritance, great. Give it a shot and see how that works for your use case.

Trigger

Create a field is_interesting in tableA (or tableB, depending on how you want to access data). Create a trigger that checks for a certain criteria when data is inserted in dependencies and then turns the book's flag true/false. That will allow your queries to run faster but could slow down your inserts and updates.