I think it will be fast, because the "IN set", which is the result of
"SELECT processorid FROM users_processors WHERE userid=4040", is limited
to a maximum of ~500 processors which is not very big. Increasing
Postgres' RAM would be difficult for me, because I am only running a
very small server with 256MB RAM and the webserver also likes to use
Does Postgre cache the HASH-Table for later use? For example when the
user reloads the website.
Rusty Conover wrote:
> This is what I've found with tables ranging in the millions of rows.
> Using IN is better when you've got lots of rows to check against the
> IN set and the IN set may be large and possibly complicated to
> retrieve (i.e. lots of joins, or expensive functions).
> Postgres will normally build a hash table of the IN set and just
> search that hash table. It's especially fast if the entire hash table
> that is built can fit into RAM. The cpu/io cost of building the IN
> set can be quite large because it needs to fetch every tuple to hash
> it, but this can be faster then searching tuple by tuple through
> possibly many indexes and tables like EXISTS does. I like to increase
> work_mem a lot (512mb and up) if I know I'm going to be doing a lot of
> matches against a large IN set of rows because I'd prefer for that
> hash table to never to be written to disk.
> EXISTS is better when you're doing fewer matches because it will pull
> the rows out one at a time from its query possibly using indexes, its
> main advantage is that it doesn't pull all of the tuples before it
> starts processing matches.
> So in summary both are good to know how to use, but choosing which one
> to use can really depend on your data set and resources.
> Rusty Conover
> InfoGears Inc.
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|Subject: Re: Planner should use index on a LIKE 'foo%' query|