问题
Every day I delete hundreds of thousands of records from a large table, then I do some calculations (with new data) and replace every one of the records that I previously deleted. I thought doing regular vacuum tbl would do the trick. I know it doesn't return disk space to the server, but (because of the pg docs) I thought because I was inserting about as many records as I was deleting, I wouldn't loose any/much disk space. However, after moving the table to a different namespace (for an unrelated reason) the table went from 117GB to 44GB! So...
Is there a better strategy than this so my table does bloat:
delete from tbl where ...etc... -- hundreds of thousands of rows removed
insert into tbl (...etc...) values (...etc...) -- hundreds of thousands of rows added back (fresh calcs)
.. repeat the above about 10 times a day ...
vacuum tbl
https://www.postgresql.org/docs/9.6/static/sql-vacuum.html
PostgreSQL 9.6
What I actually did to reduce the table size is in my answer here: integer out of range and remaining disk space too small to convert id to bigint and other solutions
Edit 1:
The drawbacks to vacuum full are too restricting for me. I am processing stuff 24/7 so i can't have locks like that and my available disk space is pretty limited at any point in time. Trying to go about this in a better way.
回答1:
What you are looking for is "dead space equilibrium" as I like to call it. If you've got say 1M rows and you want to delete and replace 100k rows, then you can do it in different ways. Let's suppose you delete 100k, and insert 100k right away. The db won't have time to vacuum up those old dead rows, so now your 1M row table has 100k dead rows in it. Over the next 24 hours vacuum will kick in and mark them dead, and the next time you delete / insert, you'll create 100k more dead rows, then reuse (most of) the previous 100k dead rows. Your 1M row table now has ~100k dead rows again, which will get reused next time and so on.
You want to reach a point where your deletes/inserts (or updates) and vacuum are creating / reclaiming dead tuples at an even rate.
来源：https://stackoverflow.com/questions/46674520/best-disk-saving-strategy-for-replacement-inserts