@title Performance: N+1 Query Problem
@group developer

How to avoid a common performance pitfall.

= Overview =

The N+1 query problem is a common performance antipattern. It looks like this:

  COUNTEREXAMPLE
  $cats = load_cats();
  foreach ($cats as $cat) {
    $cats_hats = load_hats_for_cat($cat);
    // ...
  }

Assuming `load_cats()` has an implementation that boils down to:

  SELECT * FROM cat WHERE ...

..and `load_hats_for_cat($cat)` has an implementation something like this:

  SELECT * FROM hat WHERE catID = ...

..you will issue "N+1" queries when the code executes, where N is the number of
cats:

  SELECT * FROM cat WHERE ...
  SELECT * FROM hat WHERE catID = 1
  SELECT * FROM hat WHERE catID = 2
  SELECT * FROM hat WHERE catID = 3
  SELECT * FROM hat WHERE catID = 4
  SELECT * FROM hat WHERE catID = 5
  ...

The problem with this is that each query has quite a bit of overhead. **It is
//much faster// to issue 1 query which returns 100 results than to issue 100
queries which each return 1 result.** This is particularly true if your database
is on a different machine which is, say, 1-2ms away on the network. In this
case, issuing 100 queries serially has a minimum cost of 100-200ms, even if they
can be satisfied instantly by MySQL. This is far higher than the entire
server-side generation cost for most Phabricator pages should be.

= Batching Queries =

Fix the N+1 query problem by batching queries. Load all your data before
iterating through it (this is oversimplified and omits error checking):

  $cats = load_cats();
  $hats = load_all_hats_for_these_cats($cats);
  foreach ($cats as $cat) {
    $cats_hats = $hats[$cat->getID()];
  }

That is, issue these queries:

  SELECT * FROM cat WHERE ...
  SELECT * FROM hat WHERE catID IN (1, 2, 3, 4, 5, ...)

In this case, the total number of queries issued is always 2, no matter how many
objects there are. You've removed the "N" part from the page's query plan, and
are no longer paying the overhead of issuing hundreds of extra queries. This
will perform much better (although, as with all performance changes, you should
verify this claim by measuring it).

See also @{method:LiskDAO::loadRelatives} method which provides an abstraction
to prevent this problem.

= Detecting the Problem =

Beyond reasoning about it while figuring out how to load the data you need, the
easiest way to detect this issue is to check the "Services" tab in DarkConsole
(see @{article:Using DarkConsole}), which lists all the service calls made on a
page. If you see a bunch of similar queries, this often indicates an N+1 query
issue (or a similar kind of query batching problem). Restructuring code so you
can run a single query to fetch all the data at once will always improve the
performance of the page.