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提交 8e144b09 编写于 作者: P Peter Eisentraut
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More information about partial indexes, and some tips about examining 

index usage.
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doc/src/sgml/indices.sgml
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<!-- $Header: /cvsroot/pgsql/doc/src/sgml/indices.sgml,v 1.23 2001/09/09 17:21:59 petere Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/indices.sgml,v 1.24 2001/10/31 20:38:26 petere Exp $ -->
<chapter id="indexes">
<title id="indexes-title">Indexes</title>
......@@ -68,7 +68,7 @@ CREATE INDEX test1_id_index ON test1 (id);
<para>
To remove an index, use the <command>DROP INDEX</command> command.
Indexes can be added and removed from tables at any time.
Indexes can be added to and removed from tables at any time.
</para>
<para>
......@@ -204,11 +204,11 @@ CREATE INDEX <replaceable>name</replaceable> ON <replaceable>table</replaceable>
<sect1 id="indexes-multicolumn">
<title>Multi-Column Indexes</title>
<title>Multicolumn Indexes</title>
<indexterm zone="indexes-multicolumn">
<primary>indexes</primary>
<secondary>multi-column</secondary>
<secondary>multicolumn</secondary>
</indexterm>
<para>
......@@ -235,14 +235,14 @@ CREATE INDEX test2_mm_idx ON test2 (major, minor);
</para>
<para>
Currently, only the B-tree implementation supports multi-column
Currently, only the B-tree implementation supports multicolumn
indexes. Up to 16 columns may be specified. (This limit can be
altered when building <productname>Postgres</productname>; see the
file <filename>pg_config.h</filename>.)
</para>
<para>
The query optimizer can use a multi-column index for queries that
The query optimizer can use a multicolumn index for queries that
involve the first <parameter>n</parameter> consecutive columns in
the index (when used with appropriate operators), up to the total
number of columns specified in the index definition. For example,
......@@ -258,7 +258,7 @@ CREATE INDEX test2_mm_idx ON test2 (major, minor);
</para>
<para>
Multi-column indexes can only be used if the clauses involving the
Multicolumn indexes can only be used if the clauses involving the
indexed columns are joined with <literal>AND</literal>. For instance,
<programlisting>
SELECT name FROM test2 WHERE major = <replaceable>constant</replaceable> OR minor = <replaceable>constant</replaceable>;
......@@ -269,7 +269,7 @@ SELECT name FROM test2 WHERE major = <replaceable>constant</replaceable> OR mino
</para>
<para>
Multi-column indexes should be used sparingly. Most of the time,
Multicolumn indexes should be used sparingly. Most of the time,
an index on a single column is sufficient and saves space and time.
Indexes with more than three columns are almost certainly
inappropriate.
......@@ -304,11 +304,19 @@ CREATE UNIQUE INDEX <replaceable>name</replaceable> ON <replaceable>table</repla
<productname>PostgreSQL</productname> automatically creates unique
indexes when a table is declared with a unique constraint or a
primary key, on the columns that make up the primary key or unique
columns (a multi-column index, if appropriate), to enforce that
columns (a multicolumn index, if appropriate), to enforce that
constraint. A unique index can be added to a table at any later
time, to add a unique constraint. (But a primary key cannot be
added after table creation.)
time, to add a unique constraint.
</para>
<note>
<para>
The preferred way to add a unique constraint to a table is
<literal>ALTER TABLE ... ADD CONSTRAINT</literal>. The use of
indexes to enforce unique constraints could be considered an
implementation detail that should not be accessed directly.
</para>
</note>
</sect1>
......@@ -346,7 +354,7 @@ CREATE INDEX test1_lower_col1_idx ON test1 (lower(col1));
argument, but they must be table columns, not constants.
Functional indexes are always single-column (namely, the function
result) even if the function uses more than one input field; there
cannot be multi-column indexes that contain function calls.
cannot be multicolumn indexes that contain function calls.
</para>
<tip>
......@@ -580,71 +588,290 @@ CREATE MEMSTORE ON <replaceable>table</replaceable> COLUMNS <replaceable>cols</r
</sect1>
<sect1 id="partial-index">
<title id="partial-index-title">Partial Indexes</title>
<sect1 id="indexes-partial">
<title>Partial Indexes</title>
<indexterm zone="partial-index">
<indexterm zone="indexes-partial">
<primary>indexes</primary>
<secondary>partial</secondary>
</indexterm>
<note>
<title>Author</title>
<para>
This is from a reply to a question on the email list
by Paul M. Aoki (<email>aoki@CS.Berkeley.EDU</email>)
on 1998-08-11.
<!--
Paul M. Aoki | University of California at Berkeley
aoki@CS.Berkeley.EDU | Dept. of EECS, Computer Science Division #1776
| Berkeley, CA 94720-1776
-->
</para>
</note>
<para>
A <firstterm>partial index</firstterm> is an index built over a
subset of a table; the subset is defined by a conditional
expression (called the <firstterm>predicate</firstterm> of the
partial index).
</para>
<para>
A major motivation for partial indexes is to avoid indexing common
values. Since a query conditionalized on a common value will not
use the index anyway, there is no point in keeping those rows in the
index at all. This reduces the size of the index, which will speed
up queries that do use the index. It will also speed up many data
manipulation operations because the index does not need to be
updated in all cases. <xref linkend="indexes-partial-ex1"> shows a
possible application of this idea.
</para>
<example id="indexes-partial-ex1">
<title>Setting up a Partial Index to Exclude Common Values</title>
<para>
Suppose you are storing web server access logs in a database.
Most accesses originate from the IP range of your organization but
some are from elsewhere (say, employees on dial-up connections).
So you do not want to index the IP range that corresponds to your
organization's subnet.
</para>
<para>
Assume a table like this:
<programlisting>
CREATE TABLE access_log (
url varchar,
client_ip inet,
...
);
</programlisting>
</para>
<para>
To create a partial index that suits our example, use a command
such as this:
<programlisting>
CREATE INDEX access_log_client_ip_ix ON access_log (client_ip)
WHERE NOT (client_ip > inet '192.168.100.0' AND client_ip < inet '192.168.100.255');
</programlisting>
</para>
<para>
A <firstterm>partial index</firstterm>
is an index built over a subset of a table; the subset is defined by
a predicate. <productname>Postgres</productname>
supports partial indexes with arbitrary
predicates. I believe IBM's <productname>DB2</productname>
for AS/400 supports partial indexes
using single-clause predicates.
A typical query that can use this index would be:
<programlisting>
SELECT * FROM access_log WHERE url = '/index.html' AND client_ip = inet '212.78.10.32';
</programlisting>
A query that cannot use this index is:
<programlisting>
SELECT * FROM access_log WHERE client_ip = inet '192.168.100.23';
</programlisting>
</para>
<para>
The main motivation for partial indexes is this:
if all of the queries you ask that can
profitably use an index fall into a certain range, why build an index
over the whole table and suffer the associated space/time costs?
Observe that this kind of partial index requires that the common
values be actively tracked. If the distribution of values is
inherent (due to the nature of the application) and static (does
not change), this is not difficult, but if the common values are
merely due to the coincidental data load this can require a lot of
maintenance work.
</para>
</example>
<para>
Another possibility is to exclude values from the index that the
typical query workload is not interested in; this is shown in <xref
linkend="indexes-partial-ex2">. This results in the same
advantages as listed above, but it prevents the
<quote>uninteresting</quote> values from being accessed via an
index at all, even if an index scan might be profitable in that
case. Obviously, setting up partial indexes for this kind of
scenario will require a lot of care and experimentation.
</para>
(There are other reasons too; see
<xref endterm="STON89b" linkend="STON89b-full"> for details.)
<example id="indexes-partial-ex2">
<title>Setting up a Partial Index to Exclude Uninteresting Values</title>
<para>
If you have a table that contains both billed and unbilled orders
where the unbilled orders take up a small fraction of the total
table and yet that is an often used section, you can improve
performance by creating an index on just that portion. The
command the create the index would look like this:
<programlisting>
CREATE INDEX orders_unbilled_index ON orders (order_nr)
WHERE billed is not true;
</programlisting>
</para>
<para>
The machinery to build, update and query partial indexes isn't too
bad. The hairy parts are index selection (which indexes do I build?)
and query optimization (which indexes do I use?); i.e., the parts
that involve deciding what predicate(s) match the workload/query in
some useful way. For those who are into database theory, the problems
are basically analogous to the corresponding materialized view
problems, albeit with different cost parameters and formulas. These
are, in the general case, hard problems for the standard ordinal
<acronym>SQL</acronym>
types; they're super-hard problems with black-box extension types,
because the selectivity estimation technology is so crude.
A possible query to use this index would be
<programlisting>
SELECT * FROM orders WHERE billed is not true AND order_nr < 10000;
</programlisting>
However, the index can also be used in queries that do not involve
<structfield>order_nr</> at all, e.g.,
<programlisting>
SELECT * FROM orders WHERE billed is not true AND amount > 5000.00;
</programlisting>
This is not as efficient as a partial index on the
<structfield>amount</> column would be, since the system has to
scan the entire index in any case.
</para>
<para>
Check <xref endterm="STON89b" linkend="STON89b-full">,
<xref endterm="OLSON93" linkend="OLSON93-full">,
and
<xref endterm="SESHADRI95" linkend="SESHADRI95-full">
for more information.
Note that this query cannot use this index:
<programlisting>
SELECT * FROM orders WHERE order_nr = 3501;
</programlisting>
The order 3501 may be among the billed or among the unbilled
orders.
</para>
</sect1>
</chapter>
</example>
<para>
<xref linkend="indexes-partial-ex2"> also illustrates that the
indexed column and the column used in the predicate do not need to
match. <productname>PostgreSQL</productname> supports partial
indexes with arbitrary predicates, as long as only columns of the
table being indexed are involved. However, keep in mind that the
predicate must actually match the condition used in the query that
is supposed to benefit from the index.
<productname>PostgreSQL</productname> does not have a sophisticated
theorem prover that can recognize mathematically equivalent
predicates that are written in different forms. (Not
only is such a general theorem prover extremely difficult to
create, it would probably be too slow to be of any real use.)
</para>
<para>
Finally, a partial index can also be used to override the system's
query plan choices. It may occur that data sets with peculiar
distributions will cause the system to use an index when it really
should not. In that case the index can be set up so that it is not
available for the offending query. Normally,
<productname>PostgreSQL</> makes reasonable choices about index
usage (e.g., it avoids them when retrieving common values, so the
earlier example really only saves index size, it is not required to
avoid index usage), and grossly incorrect plan choices are cause
for a bug report.
</para>
<para>
Keep in mind that setting up a partial index indicates that you
know at least as much as the query planner knows, in particular you
know when an index might be profitable. Forming this knowledge
requires experience and understanding of how indexes in
<productname>PostgreSQL</> work. In most cases, the advantage of a
partial index over a regular index will not be much.
</para>
<para>
More information about partial indexes can be found in <xref
endterm="STON89b" linkend="STON89b-full">, <xref endterm="OLSON93"
linkend="OLSON93-full">, and <xref endterm="SESHADRI95"
linkend="SESHADRI95-full">.
</para>
</sect1>
<sect1 id="indexes-examine">
<title>Examining Index Usage</title>
<para>
Although indexes in <productname>PostgreSQL</> do not need
maintenance and tuning, it is still important that it is checked
which indexes are actually used by the real-life query workload.
Examining index usage is done with the <command>EXPLAIN</> command;
its application for this purpose is illustrated in <xref
linkend="using-explain">.
</para>
<para>
It is difficult to formulate a general procedure for determining
which indexes to set up. There are a number of typical cases that
have been shown in the examples throughout the previous sections.
A good deal of experimentation will be necessary in most cases.
The rest of this section gives some tips for that.
</para>
<itemizedlist>
<listitem>
<para>
Always run <command>ANALYZE</command> first. This command
collects statistics about the distribution of the values in the
table. This information is required to guess the number of rows
returned by a query, which is needed by the planner to assign
realistic costs to each possible query plan. In absence of any
real statistics, some default values are assumed, which are
almost certain to be inaccurate. Examining an application's
index usage without having run <command>ANALYZE</command> is
therefore a lost cause.
</para>
</listitem>
<listitem>
<para>
Use real data for experimentation. Using test data for setting
up indexes will tell you what indexes you need for the test data,
but that is all.
</para>
<para>
It is especially fatal to use proportionally reduced data sets.
While selecting 1000 out of 100000 rows could be a candidate for
an index, selecting 1 out of 100 rows will hardly be, because the
100 rows will probably fit within a single disk page, and there
is no plan that can beat sequentially fetching 1 disk page.
</para>
<para>
Also be careful when making up test data, which is often
unavoidable when the application is not in production use yet.
Values that are very similar, completely random, or inserted in
sorted order will skew the statistics away from the distribution
that real data would have.
</para>
</listitem>
<listitem>
<para>
When indexes are not used, it can be useful for testing to force
their use. There are run-time parameters that can turn off
various plan types (described in the <citetitle>Administrator's
Guide</citetitle>). For instance, turning off sequential scans
(<varname>enable_seqscan</>) and nested-loop joins
(<varname>enable_nestloop</>), which are the most basic plans,
will force the system to use a different plan. If the system
still chooses a sequential scan or nested-loop join then there is
probably a more fundamental problem for why the index is not
used, for example, the query condition does not match the index.
(What kind of query can use what kind of index is explained in
the previous sections.)
</para>
</listitem>
<listitem>
<para>
If forcing index usage does use the index, then there are two
possibilities: Either the system is right and using the index is
indeed not appropriate, or the cost estimates of the query plans
are not reflecting reality. So you should time your query with
and without indexes. The <command>EXPLAIN ANALYZE</command>
command can be useful here.
</para>
</listitem>
<listitem>
<para>
If it turns out that the cost estimates are wrong, there are,
again, two possibilities. The total cost is computed from the
per-row costs of each plan node times the selectivity estimate of
the plan node. The costs of the plan nodes can be tuned with
run-time parameters (described in the <citetitle>Administrator's
Guide</citetitle>). An inaccurate selectivity estimate is due to
insufficient statistics. It may be possible to help this by
tuning the statistics-gathering parameters (see <command>ALTER
TABLE</command> reference).
</para>
<para>
If you do not succeed in adjusting the costs to be more
appropriate, then you may have to do with forcing index usage
explicitly. You may also want to contact the
<productname>PostgreSQL</> developers to examine the issue.
</para>
</listitem>
</itemizedlist>
</sect1>
</chapter>
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