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<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<!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>67.4. 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 Vsnapshot" /><link rel="prev" href="btree-support-funcs.html" title="67.3. B-Tree Support Functions" /><link rel="next" href="gist.html" title="Chapter 68. GiST Indexes" /></head><body id="docContent" class="container-fluid col-10"><div class="navheader"><table width="100%" summary="Navigation header"><tr><th colspan="5" align="center">67.4. Implementation</th></tr><tr><td width="10%" align="left"><a accesskey="p" href="btree-support-funcs.html" title="67.3. B-Tree Support Functions">Prev</a> </td><td width="10%" align="left"><a accesskey="u" href="btree.html" title="Chapter 67. B-Tree Indexes">Up</a></td><th width="60%" align="center">Chapter 67. B-Tree Indexes</th><td width="10%" align="right"><a accesskey="h" href="index.html" title="PostgreSQL 15.6 Documentation">Home</a></td><td width="10%" align="right"> <a accesskey="n" href="gist.html" title="Chapter 68. GiST Indexes">Next</a></td></tr></table><hr /></div><div class="sect1" id="BTREE-IMPLEMENTATION"><div class="titlepage"><div><div><h2 class="title" style="clear: both">67.4. Implementation</h2></div></div></div><div class="toc"><dl class="toc"><dt><span class="sect2"><a href="btree-implementation.html#BTREE-STRUCTURE">67.4.1. B-Tree Structure</a></span></dt><dt><span class="sect2"><a href="btree-implementation.html#BTREE-DELETION">67.4.2. Bottom-up Index Deletion</a></span></dt><dt><span class="sect2"><a href="btree-implementation.html#BTREE-DEDUPLICATION">67.4.3. 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">67.4.1. 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="73.6. Database Page Layout">Section 73.6</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-DELETION"><div class="titlepage"><div><div><h3 class="title">67.4.2. Bottom-up Index Deletion</h3></div></div></div><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 churn</span>”</span> tuples 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
<a class="link" href="storage-hot.html" title="73.7. Heap-Only Tuples (HOT)"><acronym class="acronym">HOT</acronym> optimization.</a>
Changing the value of only
one column covered by one index during an <code class="command">UPDATE</code>
<span class="emphasis"><em>always</em></span> necessitates a new set of index tuples
— one for <span class="emphasis"><em>each and every</em></span> index on the
table. Note in particular that this includes indexes that were not
<span class="quote">“<span class="quote">logically modified</span>”</span> by the <code class="command">UPDATE</code>.
All indexes will need a successor physical index tuple that points
to the latest version in the table. Each new tuple within each
index will generally need to coexist with the original
<span class="quote">“<span class="quote">updated</span>”</span> tuple for a short period of time (typically
until shortly after the <code class="command">UPDATE</code> transaction
commits).
</p><p>
B-Tree indexes incrementally delete version churn index tuples by
performing <em class="firstterm">bottom-up index deletion</em> passes.
Each deletion pass is triggered in reaction to an anticipated
<span class="quote">“<span class="quote">version churn page split</span>”</span>. This only happens with
indexes that are not logically modified by
<code class="command">UPDATE</code> statements, where concentrated build up
of obsolete versions in particular pages would occur otherwise. A
page split will usually be avoided, though it's possible that
certain implementation-level heuristics will fail to identify and
delete even one garbage index tuple (in which case a page split or
deduplication pass resolves the issue of an incoming new tuple not
fitting on a leaf page). The worst-case number of versions that
any index scan must traverse (for any single logical row) is an
important contributor to overall system responsiveness and
throughput. A bottom-up index deletion pass targets suspected
garbage tuples in a single leaf page based on
<span class="emphasis"><em>qualitative</em></span> distinctions involving logical
rows and versions. This contrasts with the <span class="quote">“<span class="quote">top-down</span>”</span>
index cleanup performed by autovacuum workers, which is triggered
when certain <span class="emphasis"><em>quantitative</em></span> table-level
thresholds are exceeded (see <a class="xref" href="routine-vacuuming.html#AUTOVACUUM" title="25.1.6. The Autovacuum Daemon">Section 25.1.6</a>).
</p><div class="note"><h3 class="title">Note</h3><p>
Not all deletion operations that are performed within B-Tree
indexes are bottom-up deletion operations. There is a distinct
category of index tuple deletion: <em class="firstterm">simple index tuple
deletion</em>. This is a deferred maintenance operation
that deletes index tuples that are known to be safe to delete
(those whose item identifier's <code class="literal">LP_DEAD</code> bit is
already set). Like bottom-up index deletion, simple index
deletion takes place at the point that a page split is anticipated
as a way of avoiding the split.
</p><p>
Simple deletion is opportunistic in the sense that it can only
take place when recent index scans set the
<code class="literal">LP_DEAD</code> bits of affected items in passing.
Prior to <span class="productname">PostgreSQL</span> 14, the only
category of B-Tree deletion was simple deletion. The main
differences between it and bottom-up deletion are that only the
former is opportunistically driven by the activity of passing
index scans, while only the latter specifically targets version
churn from <code class="command">UPDATE</code>s that do not logically modify
indexed columns.
</p></div><p>
Bottom-up index deletion performs the vast majority of all garbage
index tuple cleanup for particular indexes with certain workloads.
This is expected with any B-Tree index that is subject to
significant version churn from <code class="command">UPDATE</code>s that
rarely or never logically modify the columns that the index covers.
The average and worst-case number of versions per logical row can
be kept low purely through targeted incremental deletion passes.
It's quite possible that the on-disk size of certain indexes will
never increase by even one single page/block despite
<span class="emphasis"><em>constant</em></span> version churn from
<code class="command">UPDATE</code>s. Even then, an exhaustive <span class="quote">“<span class="quote">clean
sweep</span>”</span> by a <code class="command">VACUUM</code> operation (typically
run in an autovacuum worker process) will eventually be required as
a part of <span class="emphasis"><em>collective</em></span> cleanup of the table and
each of its indexes.
</p><p>
Unlike <code class="command">VACUUM</code>, bottom-up index deletion does not
provide any strong guarantees about how old the oldest garbage
index tuple may be. No index can be permitted to retain
<span class="quote">“<span class="quote">floating garbage</span>”</span> index tuples that became dead prior
to a conservative cutoff point shared by the table and all of its
indexes collectively. This fundamental table-level invariant makes
it safe to recycle table <acronym class="acronym">TID</acronym>s. This is how it
is possible for distinct logical rows to reuse the same table
<acronym class="acronym">TID</acronym> over time (though this can never happen with
two logical rows whose lifetimes span the same
<code class="command">VACUUM</code> cycle).
</p></div><div class="sect2" id="BTREE-DEDUPLICATION"><div class="titlepage"><div><div><h3 class="title">67.4.3. 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, though only when
index tuple deletion could not free sufficient space for the new
item (typically deletion is briefly considered and then skipped
over). 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>
It is sometimes possible for unique indexes (as well as unique
constraints) to use deduplication. This allows leaf pages to
temporarily <span class="quote">“<span class="quote">absorb</span>”</span> extra version churn duplicates.
Deduplication in unique indexes augments bottom-up index deletion,
especially in cases where a long-running transaction holds a
snapshot that blocks garbage collection. The goal is to buy time
for the bottom-up index deletion strategy to become effective
again. Delaying page splits until a single long-running
transaction naturally goes away can allow a bottom-up deletion pass
to succeed where an earlier deletion pass failed.
</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>
</p></div></div><div class="navfooter"><hr /><table width="100%" summary="Navigation footer"><tr><td width="40%" align="left"><a accesskey="p" href="btree-support-funcs.html" title="67.3. B-Tree Support Functions">Prev</a> </td><td width="20%" align="center"><a accesskey="u" href="btree.html" title="Chapter 67. B-Tree Indexes">Up</a></td><td width="40%" align="right"> <a accesskey="n" href="gist.html" title="Chapter 68. GiST Indexes">Next</a></td></tr><tr><td width="40%" align="left" valign="top">67.3. B-Tree Support Functions </td><td width="20%" align="center"><a accesskey="h" href="index.html" title="PostgreSQL 15.6 Documentation">Home</a></td><td width="40%" align="right" valign="top"> Chapter 68. GiST Indexes</td></tr></table></div></body></html>
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