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<chapter id="GiST">
<title>GiST Indexes</title>

   <indexterm>
    <primary>index</primary>
    <secondary>GiST</secondary>
   </indexterm>

<sect1 id="gist-intro">
 <title>Introduction</title>

 <para>
   <acronym>GiST</acronym> stands for Generalized Search Tree.  It is a
   balanced, tree-structured access method, that acts as a base template in
   which to implement arbitrary indexing schemes. B-trees, R-trees and many
   other indexing schemes can be implemented in <acronym>GiST</acronym>.
 </para>

 <para>
  One advantage of <acronym>GiST</acronym> is that it allows the development
  of custom data types with the appropriate access methods, by
  an expert in the domain of the data type, rather than a database expert.
 </para>

  <para>
    Some of the information here is derived from the University of California at
    Berkeley's GiST Indexing Project
    <ulink url="http://gist.cs.berkeley.edu/">web site</ulink> and 
    <ulink url="http://www.sai.msu.su/~megera/postgres/gist/papers/concurrency/access-methods-for-next-generation.pdf.gz">
    Marcel Kornacker's thesis, Access Methods for Next-Generation Database Systems</ulink>.
    The <acronym>GiST</acronym>
    implementation in <productname>PostgreSQL</productname> is primarily
    maintained by Teodor Sigaev and Oleg Bartunov, and there is more
    information on their
    <ulink url="http://www.sai.msu.su/~megera/postgres/gist/">website</ulink>.
  </para>

</sect1>

<sect1 id="gist-extensibility">
 <title>Extensibility</title>

 <para>
   Traditionally, implementing a new index access method meant a lot of
   difficult work.  It was necessary to understand the inner workings of the
   database, such as the lock manager and Write-Ahead Log.  The
   <acronym>GiST</acronym> interface has a high level of abstraction,
   requiring the access method implementer to only implement the semantics of
   the data type being accessed.  The <acronym>GiST</acronym> layer itself
   takes care of concurrency, logging and searching the tree structure.
 </para>
 
 <para>
   This extensibility should not be confused with the extensibility of the
   other standard search trees in terms of the data they can handle.  For
   example, <productname>PostgreSQL</productname> supports extensible B-trees
   and hash indexes. That means that you can use
   <productname>PostgreSQL</productname> to build a B-tree or hash over any
   data type you want. But B-trees only support range predicates
   (<literal>&lt;</literal>, <literal>=</literal>, <literal>&gt;</literal>),
   and hash indexes only support equality queries.
 </para>
 
 <para>
   So if you index, say, an image collection with a
   <productname>PostgreSQL</productname> B-tree, you can only issue queries
   such as <quote>is imagex equal to imagey</quote>, <quote>is imagex less
   than imagey</quote> and <quote>is imagex greater than imagey</quote>?
   Depending on how you define <quote>equals</quote>, <quote>less than</quote>
   and <quote>greater than</quote> in this context, this could be useful.
   However, by using a <acronym>GiST</acronym> based index, you could create
   ways to ask domain-specific questions, perhaps <quote>find all images of
   horses</quote> or <quote>find all over-exposed images</quote>.
 </para>

 <para>
   All it takes to get a <acronym>GiST</acronym> access method up and running
   is to implement seven user-defined methods, which define the behavior of
   keys in the tree. Of course these methods have to be pretty fancy to
   support fancy queries, but for all the standard queries (B-trees,
   R-trees, etc.) they're relatively straightforward. In short,
   <acronym>GiST</acronym> combines extensibility along with generality, code
   reuse, and a clean interface.
  </para>

</sect1>

<sect1 id="gist-implementation">
 <title>Implementation</title>
 
 <para>
   There are seven methods that an index operator class for
   <acronym>GiST</acronym> must provide:
 </para>

 <variablelist>
    <varlistentry>
     <term>consistent</term>
     <listitem>
      <para>
       Given a predicate <literal>p</literal> on a tree page, and a user
       query, <literal>q</literal>, this method will return false if it is
       certain that both <literal>p</literal> and <literal>q</literal> cannot
       be true for a given data item.  For a true result, a
       <literal>recheck</> flag must also be returned; this indicates whether
       the predicate implies the query (<literal>recheck</> = false) or
       not (<literal>recheck</> = true).
      </para>
     </listitem>
    </varlistentry>

    <varlistentry>
     <term>union</term>
     <listitem>
      <para>
       This method consolidates information in the tree.  Given a set of
       entries, this function generates a new predicate that is true for all
       the entries.
      </para>
     </listitem>
    </varlistentry>

    <varlistentry>
     <term>compress</term>
     <listitem>
      <para>
       Converts the data item into a format suitable for physical storage in
       an index page.
      </para>
     </listitem>
    </varlistentry>

    <varlistentry>
     <term>decompress</term>
     <listitem>
      <para>
       The reverse of the <function>compress</function> method.  Converts the
       index representation of the data item into a format that can be
       manipulated by the database.
      </para>
     </listitem>
    </varlistentry>

    <varlistentry>
     <term>penalty</term>
     <listitem>
      <para>
       Returns a value indicating the <quote>cost</quote> of inserting the new
       entry into a particular branch of the tree.  items will be inserted
       down the path of least <function>penalty</function> in the tree.
      </para>
     </listitem>
    </varlistentry>

    <varlistentry>
     <term>picksplit</term>
     <listitem>
      <para>
       When a page split is necessary, this function decides which entries on
       the page are to stay on the old page, and which are to move to the new
       page.
      </para>
     </listitem>
    </varlistentry>

    <varlistentry>
     <term>same</term>
     <listitem>
      <para>
       Returns true if two entries are identical, false otherwise.
      </para>
     </listitem>
    </varlistentry>

  </variablelist>

</sect1>

<sect1 id="gist-examples">
 <title>Examples</title>

 <para>
  The <productname>PostgreSQL</productname> source distribution includes
  several examples of index methods implemented using
  <acronym>GiST</acronym>.  The core system currently provides text search
  support (indexing for <type>tsvector</> and <type>tsquery</>) as well as
  R-Tree equivalent functionality for some of the built-in geometric data types
  (see <filename>src/backend/access/gist/gistproc.c</>).  The following
  <filename>contrib</> modules also contain <acronym>GiST</acronym>
  operator classes: 
 </para>
 
 <variablelist>
  <varlistentry>
   <term>btree_gist</term>
   <listitem>
    <para>B-Tree equivalent functionality for several data types</para>
   </listitem>
  </varlistentry>

  <varlistentry>
   <term>cube</term>
   <listitem>
    <para>Indexing for multidimensional cubes</para>
   </listitem>
  </varlistentry>

  <varlistentry>
   <term>hstore</term>
   <listitem>
    <para>Module for storing (key, value) pairs</para>
   </listitem>
  </varlistentry>

  <varlistentry>
   <term>intarray</term>
   <listitem>
    <para>RD-Tree for one-dimensional array of int4 values</para>
   </listitem>
  </varlistentry>

  <varlistentry>
   <term>ltree</term>
   <listitem>
    <para>Indexing for tree-like structures</para>
   </listitem>
  </varlistentry>

  <varlistentry>
   <term>pg_trgm</term>
   <listitem>
    <para>Text similarity using trigram matching</para>
   </listitem>
  </varlistentry>

  <varlistentry>
   <term>seg</term>
   <listitem>
    <para>Indexing for <quote>float ranges</quote></para>
   </listitem>
  </varlistentry>
 </variablelist>

</sect1>

<sect1 id="gist-recovery">
 <title>Crash Recovery</title>

 <para>
  Usually, replay of the WAL log is sufficient to restore the integrity
  of a GiST index following a database crash.  However, there are some
  corner cases in which the index state is not fully rebuilt.  The index
  will still be functionally correct, but there might be some performance
  degradation.  When this occurs, the index can be repaired by
  <command>VACUUM</>ing its table, or by rebuilding the index using
  <command>REINDEX</>.  In some cases a plain <command>VACUUM</> is
  not sufficient, and either <command>VACUUM FULL</> or <command>REINDEX</>
  is needed.  The need for one of these procedures is indicated by occurrence
  of this log message during crash recovery:
<programlisting>
LOG:  index NNN/NNN/NNN needs VACUUM or REINDEX to finish crash recovery
</programlisting>
  or this log message during routine index insertions:
<programlisting>
LOG:  index "FOO" needs VACUUM or REINDEX to finish crash recovery
</programlisting>
  If a plain <command>VACUUM</> finds itself unable to complete recovery
  fully, it will return a notice:
<programlisting>
NOTICE:  index "FOO" needs VACUUM FULL or REINDEX to finish crash recovery
</programlisting>
 </para>
</sect1>

</chapter>
