tables.
  </para>

  <para>
   To force the planner to follow the join order laid out by explicit
   <literal>JOIN</literal>s,
   set the <xref linkend="guc-join-collapse-limit"/> run-time parameter to 1.
   (Other possible values are discussed below.)
  </para>

  <para>
   You do not need to constrain the join order completely in order to
   cut search time, because it's OK to use <literal>JOIN</literal> operators
   within items of a plain <literal>FROM</literal> list.  For example, consider:
<programlisting>
SELECT * FROM a CROSS JOIN b, c, d, e WHERE ...;
</programlisting>
   With <varname>join_collapse_limit</varname> = 1, this
   forces the planner to join A to B before joining them to other tables,
   but doesn't constrain its choices otherwise.  In this example, the
   number of possible join orders is reduced by a factor of 5.
  </para>

  <para>
   Constraining the planner's search in this way is a useful technique
   both for reducing planning time and for directing the planner to a
   good query plan.  If the planner chooses a bad join order by default,
   you can force it to choose a better order via <literal>JOIN</literal> syntax
   &mdash; assuming that you know of a better order, that is.  Experimentation
   is recommended.
  </para>

  <para>
   A closely related issue that affects planning time is collapsing of
   subqueries into their parent query.  For example, consider:
<programlisting>
SELECT *
FROM x, y,
    (SELECT * FROM a, b, c WHERE something) AS ss
WHERE somethingelse;
</programlisting>
   This situation might arise from use of a view that contains a join;
   the view's <literal>SELECT</literal> rule will be inserted in place of the view
   reference, yielding a query much like the above.  Normally, the planner
   will try to collapse the subquery into the parent, yielding:
<programlisting>
SELECT * FROM x, y, a, b, c WHERE something AND somethingelse;
</programlisting>
   This usually results in a better plan than planning the subquery
   separately.  (For example, the outer <literal>WHERE</literal> conditions might be such that
   joining X to A first eliminates many rows of A, thus avoiding the need to
   form the full logical output of the subquery.)  But at the same time,
   we have increased the planning time; here, we have a five-way join
   problem replacing two separate three-way join problems.  Because of the
   exponential growth of the number of possibilities, this makes a big
   difference.  The planner tries to avoid getting stuck in huge join search
   problems by not collapsing a subquery if more than <varname>from_collapse_limit</varname>
   <literal>FROM</literal> items would result in the parent
   query.  You can trade off planning time against quality of plan by
   adjusting this run-time parameter up or down.
  </para>

  <para>
   <xref linkend="guc-from-collapse-limit"/> and <xref
   linkend="guc-join-collapse-limit"/>
   are similarly named because they do almost the same thing: one controls
   when the planner will <quote>flatten out</quote> subqueries, and the
   other controls when it will flatten out explicit joins.  Typically
   you would either set <varname>join_collapse_limit</varname> equal to
   <varname>from_collapse_limit</varname> (so that explicit joins and subqueries
   act similarly) or set <varname>join_collapse_limit</varname> to 1 (if you want
   to control join order with explicit joins).  But you might set them
   differently if you are trying to fine-tune the trade-off between planning
   time and run time.
  </para>
 </sect1>

 <sect1 id="populate">
  <title>Populating a Database</title>

  <para>
   One might need to insert a large amount of data when first populating
   a database. This section contains some suggestions on how to make
   this process as efficient as possible.
  </para>

  <sect2 id="disable-autocommit">
   <title>Disable Autocommit</title>

   <indexterm>
    <primary>autocommit</primary>
    <secondary>bulk-loading data</secondary>