database/postgres
1
0
Fork 0
mirror of https://github.com/postgres/postgres.git synced 2025-09-02 04:21:28 +03:00
Code Activity

Doc: Describe CREATE INDEX deduplication strategy.

Browse Source 
The B-Tree index deduplication strategy used during CREATE INDEX and
REINDEX differs from the lazy strategy used by retail inserts.  Make
that clear by adding a new paragraph to the B-Tree implementation
section of the documentation.

In passing, do some copy-editing of nearby deduplication documentation.
This commit is contained in:
Peter Geoghegan
2020-05-21 13:36:45 -07:00
parent 3350fb5d1f
commit 449e14a561
1 changed files with 37 additions and 17 deletions
Download Patch File Download Diff File Expand all files Collapse all files

54
doc/src/sgml/btree.sgml
View File

@@ -622,12 +622,13 @@ equalimage(<replaceable>opcintype</replaceable> <type>oid</type>) returns bool
</para>
<note>
<para>
While NULL is generally not considered to be equal to any other
value, including NULL, NULL is nevertheless treated as just
another value from the domain of indexed values by the B-Tree
implementation (except when enforcing uniqueness in a unique
index). B-Tree deduplication is therefore just as effective with
<quote>duplicates</quote> that contain a NULL value.
B-Tree deduplication is just as effective with
<quote>duplicates</quote> that contain a NULL value, even though
NULL values are never equal to each other according to the
<literal>=</literal> 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.
</para>
</note>
<para>
@@ -642,6 +643,20 @@ equalimage(<replaceable>opcintype</replaceable> <type>oid</type>) returns bool
see a moderate performance benefit from using deduplication.
Deduplication is enabled by default.
</para>
<para>
<command>CREATE INDEX</command> and <command>REINDEX</command>
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
<emphasis>before</emphasis> being added to the current pending leaf
page. Individual posting list tuples are packed with as many
<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 <command>CREATE INDEX</command> and
<command>REINDEX</command> because they are once-off batch
operations.
</para>
<para>
Write-heavy workloads that don't benefit from deduplication due to
having few or no duplicate values in indexes will incur a small,
@@ -657,17 +672,22 @@ equalimage(<replaceable>opcintype</replaceable> <type>oid</type>) returns bool
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. Thus, an update of a row always creates all-new index
entries for the row, even if the key values did not change. Some
workloads suffer from index bloat caused by these
implementation-level version duplicates (this is typically a
problem for <command>UPDATE</command>-heavy workloads that cannot
apply the <acronym>HOT</acronym> optimization due to modifying at
least one indexed column). B-Tree deduplication does not
distinguish between these implementation-level version duplicates
and conventional duplicates. Deduplication can nevertheless help
with controlling index bloat caused by implementation-level version
churn.
entry. <quote>Version duplicates</quote> may sometimes accumulate
and adversely affect query latency and throughput. This typically
occurs with <command>UPDATE</command>-heavy workloads where most
individual updates cannot apply the <acronym>HOT</acronym>
optimization (often because at least one indexed column gets
modified, necessitating a new set of index tuple versions &mdash;
one new tuple for <emphasis>each and every</emphasis> 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 <emphasis>physically</emphasis> 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 <command>VACUUM</command> more time to run before an
<quote>unnecessary</quote> page split caused by version churn can
take place.
</para>
<tip>
<para>