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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>63.4. Implementation</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 V1.79.1" /><link rel="prev" href="btree-support-funcs.html" title="63.3. B-Tree Support Functions" /><link rel="next" href="gist.html" title="Chapter 64. GiST Indexes" /></head><body id="docContent" class="container-fluid col-10"><div xmlns="http://www.w3.org/TR/xhtml1/transitional" class="navheader"><table width="100%" summary="Navigation header"><tr><th colspan="5" align="center">63.4. Implementation</th></tr><tr><td width="10%" align="left"><a accesskey="p" href="btree-support-funcs.html" title="63.3. B-Tree Support Functions">Prev</a> </td><td width="10%" align="left"><a accesskey="u" href="btree.html" title="Chapter 63. B-Tree Indexes">Up</a></td><th width="60%" align="center">Chapter 63. B-Tree Indexes</th><td width="10%" align="right"><a accesskey="h" href="index.html" title="PostgreSQL 13.1 Documentation">Home</a></td><td width="10%" align="right"> <a accesskey="n" href="gist.html" title="Chapter 64. GiST Indexes">Next</a></td></tr></table><hr></hr></div><div class="sect1" id="BTREE-IMPLEMENTATION"><div class="titlepage"><div><div><h2 class="title" style="clear: both">63.4. Implementation</h2></div></div></div><div class="toc"><dl class="toc"><dt><span class="sect2"><a href="btree-implementation.html#BTREE-STRUCTURE">63.4.1. B-Tree Structure</a></span></dt><dt><span class="sect2"><a href="btree-implementation.html#BTREE-DEDUPLICATION">63.4.2. Deduplication</a></span></dt></dl></div><p>
  This section covers B-Tree index implementation details that may be
  of use to advanced users.  See
  <code class="filename">src/backend/access/nbtree/README</code> in the source
  distribution for a much more detailed, internals-focused description
  of the B-Tree implementation.
 </p><div class="sect2" id="BTREE-STRUCTURE"><div class="titlepage"><div><div><h3 class="title">63.4.1. B-Tree Structure</h3></div></div></div><p>
   <span class="productname">PostgreSQL</span> B-Tree indexes are
   multi-level tree structures, where each level of the tree can be
   used as a doubly-linked list of pages.  A single metapage is stored
   in a fixed position at the start of the first segment file of the
   index.  All other pages are either leaf pages or internal pages.
   Leaf pages are the pages on the lowest level of the tree.  All
   other levels consist of internal pages.  Each leaf page contains
   tuples that point to table rows.  Each internal page contains
   tuples that point to the next level down in the tree.  Typically,
   over 99% of all pages are leaf pages.  Both internal pages and leaf
   pages use the standard page format described in <a class="xref" href="storage-page-layout.html" title="68.6. Database Page Layout">Section 68.6</a>.
  </p><p>
   New leaf pages are added to a B-Tree index when an existing leaf
   page cannot fit an incoming tuple.  A <em class="firstterm">page
    split</em> operation makes room for items that originally
   belonged on the overflowing page by moving a portion of the items
   to a new page.  Page splits must also insert a new
   <em class="firstterm">downlink</em> to the new page in the parent page,
   which may cause the parent to split in turn.  Page splits
   <span class="quote">“<span class="quote">cascade upwards</span>”</span> in a recursive fashion.  When the
   root page finally cannot fit a new downlink, a <em class="firstterm">root page
    split</em> operation takes place.  This adds a new level to
   the tree structure by creating a new root page that is one level
   above the original root page.
  </p></div><div class="sect2" id="BTREE-DEDUPLICATION"><div class="titlepage"><div><div><h3 class="title">63.4.2. Deduplication</h3></div></div></div><p>
   A duplicate is a leaf page tuple (a tuple that points to a table
   row) where <span class="emphasis"><em>all</em></span> indexed key columns have values
   that match corresponding column values from at least one other leaf
   page tuple in the same index.  Duplicate tuples are quite common in
   practice.  B-Tree indexes can use a special, space-efficient
   representation for duplicates when an optional technique is
   enabled: <em class="firstterm">deduplication</em>.
  </p><p>
   Deduplication works by periodically merging groups of duplicate
   tuples together, forming a single <em class="firstterm">posting list</em> tuple for each
   group.  The column key value(s) only appear once in this
   representation.  This is followed by a sorted array of
   <acronym class="acronym">TID</acronym>s that point to rows in the table.  This
   significantly reduces the storage size of indexes where each value
   (or each distinct combination of column values) appears several
   times on average.  The latency of queries can be reduced
   significantly.  Overall query throughput may increase
   significantly.  The overhead of routine index vacuuming may also be
   reduced significantly.
  </p><div class="note"><h3 class="title">Note</h3><p>
    B-Tree deduplication is just as effective with
    <span class="quote">“<span class="quote">duplicates</span>”</span> that contain a NULL value, even though
    NULL values are never equal to each other according to the
    <code class="literal">=</code> member of any B-Tree operator class.  As far
    as any part of the implementation that understands the on-disk
    B-Tree structure is concerned, NULL is just another value from the
    domain of indexed values.
   </p></div><p>
   The deduplication process occurs lazily, when a new item is
   inserted that cannot fit on an existing leaf page.  This prevents
   (or at least delays) leaf page splits.  Unlike GIN posting list
   tuples, B-Tree posting list tuples do not need to expand every time
   a new duplicate is inserted; they are merely an alternative
   physical representation of the original logical contents of the
   leaf page.  This design prioritizes consistent performance with
   mixed read-write workloads.  Most client applications will at least
   see a moderate performance benefit from using deduplication.
   Deduplication is enabled by default.
  </p><p>
   <code class="command">CREATE INDEX</code> and <code class="command">REINDEX</code>
   apply deduplication to create posting list tuples, though the
   strategy they use is slightly different.  Each group of duplicate
   ordinary tuples encountered in the sorted input taken from the
   table is merged into a posting list tuple
   <span class="emphasis"><em>before</em></span> being added to the current pending leaf
   page.  Individual posting list tuples are packed with as many
   <acronym class="acronym">TID</acronym>s as possible.  Leaf pages are written out in
   the usual way, without any separate deduplication pass.  This
   strategy is well-suited to <code class="command">CREATE INDEX</code> and
   <code class="command">REINDEX</code> because they are once-off batch
   operations.
  </p><p>
   Write-heavy workloads that don't benefit from deduplication due to
   having few or no duplicate values in indexes will incur a small,
   fixed performance penalty (unless deduplication is explicitly
   disabled).  The <code class="literal">deduplicate_items</code> storage
   parameter can be used to disable deduplication within individual
   indexes.  There is never any performance penalty with read-only
   workloads, since reading posting list tuples is at least as
   efficient as reading the standard tuple representation.  Disabling
   deduplication isn't usually helpful.
  </p><p>
   B-Tree indexes are not directly aware that under MVCC, there might
   be multiple extant versions of the same logical table row; to an
   index, each tuple is an independent object that needs its own index
   entry.  <span class="quote">“<span class="quote">Version duplicates</span>”</span> may sometimes accumulate
   and adversely affect query latency and throughput.  This typically
   occurs with <code class="command">UPDATE</code>-heavy workloads where most
   individual updates cannot apply the <acronym class="acronym">HOT</acronym>
   optimization (often because at least one indexed column gets
   modified, necessitating a new set of index tuple versions —
   one new tuple for <span class="emphasis"><em>each and every</em></span> index).  In
   effect, B-Tree deduplication ameliorates index bloat caused by
   version churn.  Note that even the tuples from a unique index are
   not necessarily <span class="emphasis"><em>physically</em></span> unique when stored
   on disk due to version churn.  The deduplication optimization is
   selectively applied within unique indexes.  It targets those pages
   that appear to have version duplicates.  The high level goal is to
   give <code class="command">VACUUM</code> more time to run before an
   <span class="quote">“<span class="quote">unnecessary</span>”</span> page split caused by version churn can
   take place.
  </p><div class="tip"><h3 class="title">Tip</h3><p>
    A special heuristic is applied to determine whether a
    deduplication pass in a unique index should take place.  It can
    often skip straight to splitting a leaf page, avoiding a
    performance penalty from wasting cycles on unhelpful deduplication
    passes.  If you're concerned about the overhead of deduplication,
    consider setting <code class="literal">deduplicate_items = off</code>
    selectively.  Leaving deduplication enabled in unique indexes has
    little downside.
   </p></div><p>
   Deduplication cannot be used in all cases due to
   implementation-level restrictions.  Deduplication safety is
   determined when <code class="command">CREATE INDEX</code> or
   <code class="command">REINDEX</code> is run.
  </p><p>
   Note that deduplication is deemed unsafe and cannot be used in the
   following cases involving semantically significant differences
   among equal datums:
  </p><p>
   </p><div class="itemizedlist"><ul class="itemizedlist" style="list-style-type: disc; "><li class="listitem"><p>
      <code class="type">text</code>, <code class="type">varchar</code>, and <code class="type">char</code>
      cannot use deduplication when a
      <span class="emphasis"><em>nondeterministic</em></span> collation is used.  Case
      and accent differences must be preserved among equal datums.
     </p></li><li class="listitem"><p>
      <code class="type">numeric</code> cannot use deduplication.  Numeric display
      scale must be preserved among equal datums.
     </p></li><li class="listitem"><p>
      <code class="type">jsonb</code> cannot use deduplication, since the
      <code class="type">jsonb</code> B-Tree operator class uses
      <code class="type">numeric</code> internally.
     </p></li><li class="listitem"><p>
      <code class="type">float4</code> and <code class="type">float8</code> cannot use
      deduplication.  These types have distinct representations for
      <code class="literal">-0</code> and <code class="literal">0</code>, which are
      nevertheless considered equal.  This difference must be
      preserved.
     </p></li></ul></div><p>
  </p><p>
   There is one further implementation-level restriction that may be
   lifted in a future version of
   <span class="productname">PostgreSQL</span>:
  </p><p>
   </p><div class="itemizedlist"><ul class="itemizedlist" style="list-style-type: disc; "><li class="listitem"><p>
      Container types (such as composite types, arrays, or range
      types) cannot use deduplication.
     </p></li></ul></div><p>
  </p><p>
   There is one further implementation-level restriction that applies
   regardless of the operator class or collation used:
  </p><p>
   </p><div class="itemizedlist"><ul class="itemizedlist" style="list-style-type: disc; "><li class="listitem"><p>
      <code class="literal">INCLUDE</code> indexes can never use deduplication.
     </p></li></ul></div><p>
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