Databases
StackOverflow2013
Postsdbo
POOptimise PostgreSQL for fast testing
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POOptimise PostgreSQL for fast testing
    primarykey
    data
    text
    <p>I am switching to PostgreSQL from SQLite for a typical Rails application.</p> <p>The problem is that running specs became slow with PG.<br> On SQLite it took ~34 seconds, on PG it's ~76 seconds which is <strong>more than 2x slower</strong>.</p> <p>So now I want to apply some techniques to <strong>bring the performance of the specs on par with SQLite</strong> with no code modifications (ideally just by setting the connection options, which is probably not possible).</p> <p>Couple of obvious things from top of my head are:</p> <ul> <li>RAM Disk (good setup with RSpec on OSX would be good to see)</li> <li>Unlogged tables (can it be applied on the whole database so I don't have change all the scripts?)</li> </ul> <p>As you may have understood I don't care about reliability and the rest (the DB is just a throwaway thingy here).<br> I need to get the most out of the PG and make it <strong>as fast as it can possibly be</strong>.</p> <p><strong>Best answer</strong> would ideally describe the <em>tricks</em> for doing just that, setup and the drawbacks of those tricks.</p> <p><strong>UPDATE:</strong> <code>fsync = off</code> + <code>full_page_writes = off</code> only decreased time to ~65 seconds (~-16 secs). Good start, but far from the target of 34.</p> <p><strong>UPDATE 2:</strong> I <a href="https://gist.github.com/1573414" rel="noreferrer">tried to use RAM disk</a> but the performance gain was within an error margin. So doesn't seem to be worth it.</p> <p><strong>UPDATE 3:*</strong> I found the biggest bottleneck and now my specs run as fast as the SQLite ones.</p> <p>The issue was the database cleanup that did the <strong>truncation</strong>. Apparently SQLite is way too fast there.</p> <p>To "fix" it I open a <strong>transaction</strong> before each test and roll it back at the end.</p> <p>Some numbers for ~700 tests.</p> <ul> <li>Truncation: SQLite - 34s, PG - 76s.</li> <li>Transaction: SQLite - 17s, PG - 18s.</li> </ul> <p>2x speed increase for SQLite. 4x speed increase for PG.</p>
    singulars
    1. PO
      singulars
      1. PTAnswer
    1. This table or related slice is empty.
    1. PTQuestion
    1. USthe_drow
    1. USDmytrii Nagirniak
    plurals
    1. PL
      singulars
      1. LTLinked
    1. PL
      singulars
      1. LTLinked
    2. PL
      singulars
      1. LTLinked
    3. PL
      singulars
      1. LTLinked
    1. This table or related slice is empty.
    1. PO
      singulars
      1. PTAnswer
    2. PO
      singulars
      1. PTAnswer
    1. VO
      singulars
      1. POOptimise PostgreSQL for fast testing
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. POOptimise PostgreSQL for fast testing
      1. This table or related slice is empty.
      1. VTUpMod
    3. VO
      singulars
      1. POOptimise PostgreSQL for fast testing
      1. This table or related slice is empty.
      1. VTUpMod
    1. COI really doubt you'll get it to go as fast as SQLite. SQLite with a single user is *insanely* fast. SQLite's design is very fast with low user counts and scales poorly; Pg's design scales well but isn't as fast for simple bulk work with just one user.
      singulars
      1. POOptimise PostgreSQL for fast testing
      1. USCraig Ringer
    2. COI realise that, but there's a particular case that I hope to optimise PG for (test runs) so it is as fast as it can possibly be. I don't mind it to be *slightly* slower there, but 2.2x is a bit too slow. See what I mean?
      singulars
      1. POOptimise PostgreSQL for fast testing
      1. USDmytrii Nagirniak
    3. CO+1 I'd be very interested in updates on the RAM disk approach if you've got any results concerning that.
      singulars
      1. POOptimise PostgreSQL for fast testing
      1. UStscho
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload