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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8" /><title>11.1. Introduction</title><link rel="stylesheet" type="text/css" href="stylesheet.css" /><link rev="made" href="pgsql-docs@lists.postgresql.org" /><meta name="generator" content="DocBook XSL Stylesheets Vsnapshot" /><link rel="prev" href="indexes.html" title="Chapter 11. Indexes" /><link rel="next" href="indexes-types.html" title="11.2. Index Types" /></head><body id="docContent" class="container-fluid col-10"><div class="navheader"><table width="100%" summary="Navigation header"><tr><th colspan="5" align="center">11.1. Introduction</th></tr><tr><td width="10%" align="left"><a accesskey="p" href="indexes.html" title="Chapter 11. Indexes">Prev</a> </td><td width="10%" align="left"><a accesskey="u" href="indexes.html" title="Chapter 11. Indexes">Up</a></td><th width="60%" align="center">Chapter 11. Indexes</th><td width="10%" align="right"><a accesskey="h" href="index.html" title="PostgreSQL 15.7 Documentation">Home</a></td><td width="10%" align="right"> <a accesskey="n" href="indexes-types.html" title="11.2. Index Types">Next</a></td></tr></table><hr /></div><div class="sect1" id="INDEXES-INTRO"><div class="titlepage"><div><div><h2 class="title" style="clear: both">11.1. Introduction</h2></div></div></div><p>
Suppose we have a table similar to this:
</p><pre class="programlisting">
CREATE TABLE test1 (
id integer,
content varchar
);
</pre><p>
and the application issues many queries of the form:
</p><pre class="programlisting">
SELECT content FROM test1 WHERE id = <em class="replaceable"><code>constant</code></em>;
</pre><p>
With no advance preparation, the system would have to scan the entire
<code class="structname">test1</code> table, row by row, to find all
matching entries. If there are many rows in
<code class="structname">test1</code> and only a few rows (perhaps zero
or one) that would be returned by such a query, this is clearly an
inefficient method. But if the system has been instructed to maintain an
index on the <code class="structfield">id</code> column, it can use a more
efficient method for locating matching rows. For instance, it
might only have to walk a few levels deep into a search tree.
</p><p>
A similar approach is used in most non-fiction books: terms and
concepts that are frequently looked up by readers are collected in
an alphabetic index at the end of the book. The interested reader
can scan the index relatively quickly and flip to the appropriate
page(s), rather than having to read the entire book to find the
material of interest. Just as it is the task of the author to
anticipate the items that readers are likely to look up,
it is the task of the database programmer to foresee which indexes
will be useful.
</p><p>
The following command can be used to create an index on the
<code class="structfield">id</code> column, as discussed:
</p><pre class="programlisting">
CREATE INDEX test1_id_index ON test1 (id);
</pre><p>
The name <code class="structname">test1_id_index</code> can be chosen
freely, but you should pick something that enables you to remember
later what the index was for.
</p><p>
To remove an index, use the <code class="command">DROP INDEX</code> command.
Indexes can be added to and removed from tables at any time.
</p><p>
Once an index is created, no further intervention is required: the
system will update the index when the table is modified, and it will
use the index in queries when it thinks doing so would be more efficient
than a sequential table scan. But you might have to run the
<code class="command">ANALYZE</code> command regularly to update
statistics to allow the query planner to make educated decisions.
See <a class="xref" href="performance-tips.html" title="Chapter 14. Performance Tips">Chapter 14</a> for information about
how to find out whether an index is used and when and why the
planner might choose <span class="emphasis"><em>not</em></span> to use an index.
</p><p>
Indexes can also benefit <code class="command">UPDATE</code> and
<code class="command">DELETE</code> commands with search conditions.
Indexes can moreover be used in join searches. Thus,
an index defined on a column that is part of a join condition can
also significantly speed up queries with joins.
</p><p>
In general, <span class="productname">PostgreSQL</span> indexes can be used
to optimize queries that contain one or more <code class="literal">WHERE</code>
or <code class="literal">JOIN</code> clauses of the form
</p><pre class="synopsis">
<em class="replaceable"><code>indexed-column</code></em> <em class="replaceable"><code>indexable-operator</code></em> <em class="replaceable"><code>comparison-value</code></em>
</pre><p>
Here, the <em class="replaceable"><code>indexed-column</code></em> is whatever
column or expression the index has been defined on.
The <em class="replaceable"><code>indexable-operator</code></em> is an operator that
is a member of the index's <em class="firstterm">operator class</em> for
the indexed column. (More details about that appear below.)
And the <em class="replaceable"><code>comparison-value</code></em> can be any
expression that is not volatile and does not reference the index's
table.
</p><p>
In some cases the query planner can extract an indexable clause of
this form from another SQL construct. A simple example is that if
the original clause was
</p><pre class="synopsis">
<em class="replaceable"><code>comparison-value</code></em> <em class="replaceable"><code>operator</code></em> <em class="replaceable"><code>indexed-column</code></em>
</pre><p>
then it can be flipped around into indexable form if the
original <em class="replaceable"><code>operator</code></em> has a commutator
operator that is a member of the index's operator class.
</p><p>
Creating an index on a large table can take a long time. By default,
<span class="productname">PostgreSQL</span> allows reads (<code class="command">SELECT</code> statements) to occur
on the table in parallel with index creation, but writes (<code class="command">INSERT</code>,
<code class="command">UPDATE</code>, <code class="command">DELETE</code>) are blocked until the index build is finished.
In production environments this is often unacceptable.
It is possible to allow writes to occur in parallel with index
creation, but there are several caveats to be aware of —
for more information see <a class="xref" href="sql-createindex.html#SQL-CREATEINDEX-CONCURRENTLY" title="Building Indexes Concurrently">Building Indexes Concurrently</a>.
</p><p>
After an index is created, the system has to keep it synchronized with the
table. This adds overhead to data manipulation operations. Indexes can
also prevent the creation of <a class="link" href="storage-hot.html" title="73.7. Heap-Only Tuples (HOT)">heap-only
tuples</a>.
Therefore indexes that are seldom or never used in queries
should be removed.
</p></div><div class="navfooter"><hr /><table width="100%" summary="Navigation footer"><tr><td width="40%" align="left"><a accesskey="p" href="indexes.html" title="Chapter 11. Indexes">Prev</a> </td><td width="20%" align="center"><a accesskey="u" href="indexes.html" title="Chapter 11. Indexes">Up</a></td><td width="40%" align="right"> <a accesskey="n" href="indexes-types.html" title="11.2. Index Types">Next</a></td></tr><tr><td width="40%" align="left" valign="top">Chapter 11. Indexes </td><td width="20%" align="center"><a accesskey="h" href="index.html" title="PostgreSQL 15.7 Documentation">Home</a></td><td width="40%" align="right" valign="top"> 11.2. Index Types</td></tr></table></div></body></html>
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