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Tom Lane 2003-11-06 22:21:47 +00:00
parent 96889392e9
commit e1b47c2dbd
5 changed files with 62 additions and 60 deletions
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6
doc/src/sgml/datatype.sgml
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@ -1,5 +1,5 @@
<!--
$Header: /cvsroot/pgsql/doc/src/sgml/datatype.sgml,v 1.129 2003/11/04 09:55:38 petere Exp $
$Header: /cvsroot/pgsql/doc/src/sgml/datatype.sgml,v 1.130 2003/11/06 22:21:47 tgl Exp $
-->
<chapter id="datatype">
@ -250,8 +250,8 @@ $Header: /cvsroot/pgsql/doc/src/sgml/datatype.sgml,v 1.129 2003/11/04 09:55:38 p
<type>varchar</type>, <type>date</type>, <type>double
precision</type>, <type>integer</type>, <type>interval</type>,
<type>numeric</type>, <type>decimal</type>, <type>real</type>,
<type>smallint</type>, <type>time</type>, <type>timestamp</type>
(both with or without time zone).
<type>smallint</type>, <type>time</type> (with or without time zone),
<type>timestamp</type> (with or without time zone).
</para>
</note>

9
doc/src/sgml/datetime.sgml
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@ -1,5 +1,5 @@
<!--
$Header: /cvsroot/pgsql/doc/src/sgml/datetime.sgml,v 2.36 2003/09/20 20:12:04 tgl Exp $
$Header: /cvsroot/pgsql/doc/src/sgml/datetime.sgml,v 2.37 2003/11/06 22:21:47 tgl Exp $
-->
<appendix id="datetime-appendix">
@ -995,7 +995,7 @@ $Header: /cvsroot/pgsql/doc/src/sgml/datetime.sgml,v 2.36 2003/09/20 20:12:04 tg
<para>
The Julian Date was invented by the French scholar
Joseph Justus Scaliger (1540-1609)
and probably takes its name from the Scaliger's father,
and probably takes its name from Scaliger's father,
the Italian scholar Julius Caesar Scaliger (1484-1558).
Astronomers have used the Julian period to assign a unique number to
every day since 1 January 4713 BC. This is the so-called Julian Date
@ -1007,7 +1007,7 @@ $Header: /cvsroot/pgsql/doc/src/sgml/datetime.sgml,v 2.36 2003/09/20 20:12:04 tg
The <quote>Julian Date</quote> is different from the <quote>Julian
Calendar</quote>. The Julian calendar
was introduced by Julius Caesar in 45 BC. It was in common use
until the 1582, when countries started changing to the Gregorian
until the year 1582, when countries started changing to the Gregorian
calendar. In the Julian calendar, the tropical year is
approximated as 365 1/4 days = 365.25 days. This gives an error of
about 1 day in 128 years.
@ -1042,7 +1042,8 @@ $Header: /cvsroot/pgsql/doc/src/sgml/datetime.sgml,v 2.36 2003/09/20 20:12:04 tg
So, 1700, 1800, 1900, 2100, and 2200 are not leap years. But 1600,
2000, and 2400 are leap years.
By contrast, in the older Julian calendar only years divisible by 4 are leap years.
By contrast, in the older Julian calendar all years divisible by 4 are leap
years.
</para>
<para>

87
doc/src/sgml/indices.sgml
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@ -1,4 +1,4 @@
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/indices.sgml,v 1.45 2003/09/30 03:22:33 tgl Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/indices.sgml,v 1.46 2003/11/06 22:21:47 tgl Exp $ -->
<chapter id="indexes">
<title id="indexes-title">Indexes</title>
@ -77,7 +77,7 @@ CREATE INDEX test1_id_index ON test1 (id);
than a sequential table scan. But you may have to run the
<command>ANALYZE</command> command regularly to update
statistics to allow the query planner to make educated decisions.
Also read <xref linkend="performance-tips"> for information about
See <xref linkend="performance-tips"> for information about
how to find out whether an index is used and when and why the
planner may choose <emphasis>not</emphasis> to use an index.
</para>
@ -106,8 +106,8 @@ CREATE INDEX test1_id_index ON test1 (id);
<para>
<productname>PostgreSQL</productname> provides several index types:
B-tree, R-tree, GiST, and Hash. Each index type is more appropriate for
a particular query type because of the algorithm it uses.
B-tree, R-tree, GiST, and Hash. Each index type uses a different
algorithm that is best suited to different types of queries.
<indexterm>
<primary>index</primary>
<secondary>B-tree</secondary>
@ -116,9 +116,10 @@ CREATE INDEX test1_id_index ON test1 (id);
<primary>B-tree</primary>
<see>index</see>
</indexterm>
By
default, the <command>CREATE INDEX</command> command will create a
B-tree index, which fits the most common situations. In
By default, the <command>CREATE INDEX</command> command will create a
B-tree index, which fits the most common situations. B-trees can
handle equality and range queries on data that can be sorted into
some ordering. In
particular, the <productname>PostgreSQL</productname> query planner
will consider using a B-tree index whenever an indexed column is
involved in a comparison using one of these operators:
@ -154,7 +155,7 @@ CREATE INDEX test1_id_index ON test1 (id);
<primary>R-tree</primary>
<see>index</see>
</indexterm>
R-tree indexes are especially suited for spatial data. To create
R-tree indexes are suited for queries on spatial data. To create
an R-tree index, use a command of the form
<synopsis>
CREATE INDEX <replaceable>name</replaceable> ON <replaceable>table</replaceable> USING RTREE (<replaceable>column</replaceable>);
@ -185,6 +186,7 @@ CREATE INDEX <replaceable>name</replaceable> ON <replaceable>table</replaceable>
<primary>hash</primary>
<see>index</see>
</indexterm>
Hash indexes can only handle simple equality comparisons.
The query planner will consider using a hash index whenever an
indexed column is involved in a comparison using the
<literal>=</literal> operator. The following command is used to
@ -195,19 +197,18 @@ CREATE INDEX <replaceable>name</replaceable> ON <replaceable>table</replaceable>
<note>
<para>
Testing has shown <productname>PostgreSQL</productname>'s hash
indexes to be similar or slower than B-tree indexes, and the
index size and build time for hash indexes is much worse. Hash
indexes also suffer poor performance under high concurrency. For
indexes to perform no better than B-tree indexes, and the
index size and build time for hash indexes is much worse. For
these reasons, hash index use is presently discouraged.
</para>
</note>
</para>
<para>
The B-tree index is an implementation of Lehman-Yao
The B-tree index method is an implementation of Lehman-Yao
high-concurrency B-trees. The R-tree index method implements
standard R-trees using Guttman's quadratic split algorithm. The
hash index is an implementation of Litwin's linear hashing. We
hash index method is an implementation of Litwin's linear hashing. We
mention the algorithms used solely to indicate that all of these
index methods are fully dynamic and do not have to be optimized
periodically (as is the case with, for example, static hash methods).
@ -233,7 +234,7 @@ CREATE TABLE test2 (
name varchar
);
</programlisting>
(Say, you keep your <filename class="directory">/dev</filename>
(say, you keep your <filename class="directory">/dev</filename>
directory in a database...) and you frequently make queries like
<programlisting>
SELECT name FROM test2 WHERE major = <replaceable>constant</replaceable> AND minor = <replaceable>constant</replaceable>;
@ -263,8 +264,8 @@ CREATE INDEX test2_mm_idx ON test2 (major, minor);
<literal>a</literal> and <literal>b</literal>, or in queries
involving only <literal>a</literal>, but not in other combinations.
(In a query involving <literal>a</literal> and <literal>c</literal>
the planner might choose to use the index for
<literal>a</literal> only and treat <literal>c</literal> like an
the planner could choose to use the index for
<literal>a</literal>, while treating <literal>c</literal> like an
ordinary unindexed column.) Of course, each column must be used with
operators appropriate to the index type; clauses that involve other
operators will not be considered.
@ -310,16 +311,16 @@ CREATE UNIQUE INDEX <replaceable>name</replaceable> ON <replaceable>table</repla
<para>
When an index is declared unique, multiple table rows with equal
indexed values will not be allowed. Null values are not considered
equal.
equal. A multicolumn unique index will only reject cases where all
of the indexed columns are equal in two rows.
</para>
<para>
<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 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.
<productname>PostgreSQL</productname> automatically creates a unique
index when a unique constraint or a primary key is defined for a table.
The index covers the columns that make up the primary key or unique
columns (a multicolumn index, if appropriate), and is the mechanism
that enforces the constraint.
</para>
<note>
@ -328,6 +329,9 @@ CREATE UNIQUE INDEX <replaceable>name</replaceable> ON <replaceable>table</repla
<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.
One should, however, be aware that there's no need to manually
create indexes on unique columns; doing so would just duplicate
the automatically-created index.
</para>
</note>
</sect1>
@ -362,6 +366,14 @@ CREATE INDEX test1_lower_col1_idx ON test1 (lower(col1));
</programlisting>
</para>
<para>
If we were to declare this index <literal>UNIQUE</>, it would prevent
creation of rows whose <literal>col1</> values differ only in case,
as well as rows whose <literal>col1</> values are actually identical.
Thus, indexes on expressions can be used to enforce constraints that
are not definable as simple unique constraints.
</para>
<para>
As another example, if one often does queries like this:
<programlisting>
@ -409,7 +421,7 @@ CREATE INDEX <replaceable>name</replaceable> ON <replaceable>table</replaceable>
In practice the default operator class for the column's data type is
usually sufficient. The main point of having operator classes is
that for some data types, there could be more than one meaningful
ordering. For example, we might want to sort a complex-number data
index behavior. For example, we might want to sort a complex-number data
type either by absolute value or by real part. We could do this by
defining two operator classes for the data type and then selecting
the proper class when making an index.
@ -419,20 +431,6 @@ CREATE INDEX <replaceable>name</replaceable> ON <replaceable>table</replaceable>
There are also some built-in operator classes besides the default ones:
<itemizedlist>
<listitem>
<para>
The operator classes <literal>box_ops</literal> and
<literal>bigbox_ops</literal> both support R-tree indexes on the
<type>box</type> data type. The difference between them is
that <literal>bigbox_ops</literal> scales box coordinates down,
to avoid floating-point exceptions from doing multiplication,
addition, and subtraction on very large floating-point
coordinates. If the field on which your rectangles lie is about
20 000 square units or larger, you should use
<literal>bigbox_ops</literal>.
</para>
</listitem>
<listitem>
<para>
The operator classes <literal>text_pattern_ops</literal>,
@ -644,7 +642,8 @@ SELECT * FROM orders WHERE order_nr = 3501;
create, it would probably be too slow to be of any real use.)
The system can recognize simple inequality implications, for example
<quote>x &lt; 1</quote> implies <quote>x &lt; 2</quote>; otherwise
the predicate condition must exactly match the query's <literal>WHERE</> condition
the predicate condition must exactly match part of the query's
<literal>WHERE</> condition
or the index will not be recognized to be usable.
</para>
@ -723,7 +722,8 @@ CREATE UNIQUE INDEX tests_success_constraint ON tests (subject, target)
maintenance and tuning, it is still important to check
which indexes are actually used by the real-life query workload.
Examining index usage for an individual query is done with the
<command>EXPLAIN</> command; its application for this purpose is
<xref linkend="sql-explain" endterm="sql-explain-title">
command; its application for this purpose is
illustrated in <xref linkend="using-explain">.
It is also possible to gather overall statistics about index usage
in a running server, as described in <xref linkend="monitoring-stats">.
@ -740,7 +740,8 @@ CREATE UNIQUE INDEX tests_success_constraint ON tests (subject, target)
<itemizedlist>
<listitem>
<para>
Always run <command>ANALYZE</command> first. This command
Always run <xref linkend="sql-analyze" endterm="sql-analyze-title">
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
@ -813,8 +814,8 @@ CREATE UNIQUE INDEX tests_success_constraint ON tests (subject, target)
run-time parameters (described in <xref linkend="runtime-config">).
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).
tuning the statistics-gathering parameters (see
<xref linkend="sql-altertable" endterm="sql-altertable-title">).
</para>
<para>

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doc/src/sgml/queries.sgml
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@ -1,4 +1,4 @@
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/queries.sgml,v 1.26 2003/11/04 09:55:38 petere Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/queries.sgml,v 1.27 2003/11/06 22:21:47 tgl Exp $ -->
<chapter id="queries">
<title>Queries</title>
@ -44,7 +44,7 @@ SELECT * FROM table1;
client application. For example, the
<application>psql</application> program will display an ASCII-art
table on the screen, while client libraries will offer functions to
retrieve individual rows and columns.) The select list
extract individual values from the query result.) The select list
specification <literal>*</literal> means all columns that the table
expression happens to provide. A select list can also select a
subset of the available columns or make calculations using the

16
doc/src/sgml/syntax.sgml
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@ -1,5 +1,5 @@
<!--
$Header: /cvsroot/pgsql/doc/src/sgml/syntax.sgml,v 1.87 2003/11/04 19:18:15 tgl Exp $
$Header: /cvsroot/pgsql/doc/src/sgml/syntax.sgml,v 1.88 2003/11/06 22:21:47 tgl Exp $
-->
<chapter id="sql-syntax">
@ -205,7 +205,7 @@ UPDATE "my_table" SET "a" = 5;
should be equivalent to <literal>"FOO"</literal> not
<literal>"foo"</literal> according to the standard. If you want
to write portable applications you are advised to always quote a
particular name or never quote it.
particular name or never quote it.)
</para>
</sect2>
@ -241,13 +241,13 @@ UPDATE "my_table" SET "a" = 5;
<secondary>escaping</secondary>
</indexterm>
A string constant in SQL is an arbitrary sequence of characters
bounded by single quotes (<quote>'</quote>), e.g., <literal>'This
bounded by single quotes (<literal>'</literal>), e.g., <literal>'This
is a string'</literal>. SQL allows single quotes to be embedded
in strings by typing two adjacent single quotes (e.g.,
<literal>'Dianne''s horse'</literal>). In
in strings by typing two adjacent single quotes, e.g.,
<literal>'Dianne''s horse'</literal>. In
<productname>PostgreSQL</productname> single quotes may
alternatively be escaped with a backslash (<quote>\</quote>,
e.g., <literal>'Dianne\'s horse'</literal>).
alternatively be escaped with a backslash (<literal>\</literal>),
e.g., <literal>'Dianne\'s horse'</literal>.
</para>
<para>
@ -838,7 +838,7 @@ SELECT 3 OPERATOR(pg_catalog.+) 4;
<itemizedlist>
<listitem>
<para>
A constant or literal value; see <xref linkend="sql-syntax-constants">.
A constant or literal value.
</para>
</listitem>