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Cleanup pass over User's Guide. Key word table updated.

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This commit is contained in:
Peter Eisentraut
2002-11-10 12:45:43 +00:00
parent 188d4d6d73
commit 3590e9fac8
14 changed files with 1722 additions and 1918 deletions
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24
doc/src/sgml/array.sgml
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@ -1,4 +1,4 @@
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/array.sgml,v 1.22 2002/09/21 18:32:52 petere Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/array.sgml,v 1.22.2.1 2002/11/10 12:45:41 petere Exp $ -->
<sect1 id="arrays">
<title>Arrays</title>
@ -21,7 +21,7 @@ CREATE TABLE sal_emp (
</programlisting>
As shown, an array data type is named by appending square brackets
(<literal>[]</>) to the data type name of the array elements.
The above query will create a table named
The above command will create a table named
<structname>sal_emp</structname> with columns including
a <type>text</type> string (<structfield>name</structfield>),
a one-dimensional array of type
@ -68,7 +68,7 @@ SELECT name FROM sal_emp WHERE pay_by_quarter[1] &lt;&gt; pay_by_quarter[2];
The array subscript numbers are written within square brackets.
By default <productname>PostgreSQL</productname> uses the
<quote>one-based</quote> numbering convention for arrays, that is,
one-based numbering convention for arrays, that is,
an array of <replaceable>n</> elements starts with <literal>array[1]</literal> and
ends with <literal>array[<replaceable>n</>]</literal>.
</para>
@ -90,10 +90,9 @@ SELECT pay_by_quarter[3] FROM sal_emp;
<para>
We can also access arbitrary rectangular slices of an array, or
subarrays. An array slice is denoted by writing
<literal><replaceable>lower subscript</replaceable> :
<replaceable>upper subscript</replaceable></literal> for one or more
array dimensions. This query retrieves the first item on Bill's
schedule for the first two days of the week:
<literal><replaceable>lower-bound</replaceable>:<replaceable>upper-bound</replaceable></literal>
for one or more array dimensions. This query retrieves the first
item on Bill's schedule for the first two days of the week:
<programlisting>
SELECT schedule[1:2][1:1] FROM sal_emp WHERE name = 'Bill';
@ -112,9 +111,10 @@ SELECT schedule[1:2][1] FROM sal_emp WHERE name = 'Bill';
with the same result. An array subscripting operation is taken to
represent an array slice if any of the subscripts are written in the
form <replaceable>lower</replaceable> <literal>:</literal>
<replaceable>upper</replaceable>. A lower bound of 1 is assumed for
any subscript where only one value is specified.
form
<literal><replaceable>lower</replaceable>:<replaceable>upper</replaceable></literal>.
A lower bound of 1 is assumed for any subscript where only one value
is specified.
</para>
<para>
@ -308,7 +308,7 @@ SELECT * FROM sal_emp WHERE pay_by_quarter **= 10000;
<tip>
<para>
Remember that what you write in an SQL query will first be interpreted
Remember that what you write in an SQL command will first be interpreted
as a string literal, and then as an array. This doubles the number of
backslashes you need. For example, to insert a <type>text</> array
value containing a backslash and a double quote, you'd need to write
@ -321,7 +321,7 @@ INSERT ... VALUES ('{"\\\\","\\""}');
become <literal>\</> and <literal>"</> respectively. (If we were working
with a data type whose input routine also treated backslashes specially,
<type>bytea</> for example, we might need as many as eight backslashes
in the query to get one backslash into the stored array element.)
in the command to get one backslash into the stored array element.)
</para>
</tip>

795
doc/src/sgml/datatype.sgml
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552
doc/src/sgml/datetime.sgml
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@ -1,5 +1,5 @@
<!--
$Header: /cvsroot/pgsql/doc/src/sgml/datetime.sgml,v 2.28 2002/08/04 06:15:45 thomas Exp $
$Header: /cvsroot/pgsql/doc/src/sgml/datetime.sgml,v 2.28.2.1 2002/11/10 12:45:41 petere Exp $
Date/time details
-->
@ -8,7 +8,7 @@ Date/time details
<para>
<productname>PostgreSQL</productname> uses an internal heuristic
parser for all date/time support. Dates and times are input as
parser for all date/time input support. Dates and times are input as
strings, and are broken up into distinct fields with a preliminary
determination of what kind of information may be in the
field. Each field is interpreted and either assigned a numeric
@ -25,10 +25,203 @@ Date/time details
</para>
<sect1>
<title>Date/Time Keywords</title>
<title>Date/Time Input Interpretation</title>
<para>
<table tocentry="1">
The date/time types are all decoded using a common set of routines.
</para>
<procedure>
<title>Date/Time Input Interpretation</title>
<step>
<para>
Break the input string into tokens and categorize each token as
a string, time, time zone, or number.
</para>
<substeps>
<step>
<para>
If the numeric token contains a colon (<literal>:</>), this is
a time string. Include all subsequent digits and colons.
</para>
</step>
<step>
<para>
If the numeric token contains a dash (<literal>-</>), slash
(<literal>/</>), or two or more dots (<literal>.</>), this is
a date string which may have a text month.
</para>
</step>
<step>
<para>
If the token is numeric only, then it is either a single field
or an ISO 8601 concatenated date (e.g.,
<literal>19990113</literal> for January 13, 1999) or time
(e.g. <literal>141516</literal> for 14:15:16).
</para>
</step>
<step>
<para>
If the token starts with a plus (<literal>+</>) or minus
(<literal>-</>), then it is either a time zone or a special
field.
</para>
</step>
</substeps>
</step>
<step>
<para>
If the token is a text string, match up with possible strings.
</para>
<substeps>
<step>
<para>
Do a binary-search table lookup for the token
as either a special string (e.g., <literal>today</literal>),
day (e.g., <literal>Thursday</literal>),
month (e.g., <literal>January</literal>),
or noise word (e.g., <literal>at</literal>, <literal>on</literal>).
</para>
<para>
Set field values and bit mask for fields.
For example, set year, month, day for <literal>today</literal>,
and additionally hour, minute, second for <literal>now</literal>.
</para>
</step>
<step>
<para>
If not found, do a similar binary-search table lookup to match
the token with a time zone.
</para>
</step>
<step>
<para>
If not found, throw an error.
</para>
</step>
</substeps>
</step>
<step>
<para>
The token is a number or number field.
</para>
<substeps>
<step>
<para>
If there are more than 4 digits,
and if no other date fields have been previously read, then interpret
as a <quote>concatenated date</quote> (e.g., <literal>19990118</literal>). 8
and 6 digits are interpreted as year, month, and day, while 7
and 5 digits are interpreted as year, day of year, respectively.
</para>
</step>
<step>
<para>
If the token is three digits
and a year has already been decoded, then interpret as day of year.
</para>
</step>
<step>
<para>
If four or six digits and a year has already been read, then
interpret as a time.
</para>
</step>
<step>
<para>
If four or more digits, then interpret as a year.
</para>
</step>
<step>
<para>
If in European date mode, and if the day field has not yet been read,
and if the value is less than or equal to 31, then interpret as a day.
</para>
</step>
<step>
<para>
If the month field has not yet been read,
and if the value is less than or equal to 12, then interpret as a month.
</para>
</step>
<step>
<para>
If the day field has not yet been read,
and if the value is less than or equal to 31, then interpret as a day.
</para>
</step>
<step>
<para>
If two digits or four or more digits, then interpret as a year.
</para>
</step>
<step>
<para>
Otherwise, throw an error.
</para>
</step>
</substeps>
</step>
<step>
<para>
If BC has been specified, negate the year and add one for
internal storage. (There is no year zero in the Gregorian
calendar, so numerically <literal>1BC</literal> becomes year
zero.)
</para>
</step>
<step>
<para>
If BC was not specified, and if the year field was two digits in length, then
adjust the year to 4 digits. If the field was less than 70, then add 2000;
otherwise, add 1900.
<tip>
<para>
Gregorian years AD 1-99 may be entered by using 4 digits with leading
zeros (e.g., <literal>0099</> is AD 99). Previous versions of
<productname>PostgreSQL</productname> accepted years with three
digits and with single digits, but as of version 7.0 the rules have
been tightened up to reduce the possibility of ambiguity.
</para>
</tip>
</para>
</step>
</procedure>
</sect1>
<sect1>
<title>Date/Time Key Words</title>
<para>
<xref linkend="datetime-month-table"> shows the tokens that are
permissible as abbreviations for the names of the month.
</para>
<table id="datetime-month-table">
<title>Month Abbreviations</title>
<tgroup cols="2">
<thead>
@ -88,13 +281,17 @@ Date/time details
<note>
<para>
The month <literal>May</literal> has no explicit abbreviation, for obvious reasons.
The month May has no explicit abbreviation, for obvious reasons.
</para>
</note>
</para>
<para>
<table tocentry="1">
<xref linkend="datetime-dow-table"> shows the tokens that are
permissible as abbreviations for the names of the days of the
week.
</para>
<table id="datetime-dow-table">
<title>Day of the Week Abbreviations</title>
<tgroup cols="2">
<thead>
@ -135,12 +332,14 @@ Date/time details
</tbody>
</tgroup>
</table>
</para>
<para>
<table tocentry="1">
<title><productname>PostgreSQL</productname> Field Modifiers</title>
<titleabbrev>Field Modifiers</titleabbrev>
<xref linkend="datetime-mod-table"> shows the tokens that serve
various modifier purposes.
</para>
<table id="datetime-mod-table">
<title>Date/Time Field Modifiers</title>
<tgroup cols="2">
<thead>
<row>
@ -151,7 +350,7 @@ Date/time details
<tbody>
<row>
<entry><literal>ABSTIME</literal></entry>
<entry>Keyword ignored</entry>
<entry>Key word ignored</entry>
</row>
<row>
<entry><literal>AM</literal></entry>
@ -159,7 +358,7 @@ Date/time details
</row>
<row>
<entry><literal>AT</literal></entry>
<entry>Keyword ignored</entry>
<entry>Key word ignored</entry>
</row>
<row>
<entry><literal>JULIAN</>, <literal>JD</>, <literal>J</></entry>
@ -167,7 +366,7 @@ Date/time details
</row>
<row>
<entry><literal>ON</literal></entry>
<entry>Keyword ignored</entry>
<entry>Key word ignored</entry>
</row>
<row>
<entry><literal>PM</literal></entry>
@ -180,44 +379,40 @@ Date/time details
</tbody>
</tgroup>
</table>
</para>
<para>
The keyword <literal>ABSTIME</literal> is ignored for historical
The key word <literal>ABSTIME</literal> is ignored for historical
reasons; in very old releases of
<productname>PostgreSQL</productname> invalid <type>ABSTIME</type>
fields were emitted as <literal>Invalid Abstime</literal>. This is no
longer the case however and this keyword will likely be dropped in
<productname>PostgreSQL</productname> invalid fields of type <type>abstime</type>
were emitted as <literal>Invalid Abstime</literal>. This is no
longer the case however and this key word will likely be dropped in
a future release.
</para>
</sect1>
<sect1 id="timezones">
<title>Time Zones</title>
<indexterm zone="timezones">
<indexterm>
<primary>time zones</primary>
</indexterm>
<para>
<xref linkend="datetime-timezone-table"> shows the time zone
abbreviations recognized by <productname>PostgreSQL</productname>.
<productname>PostgreSQL</productname> contains internal tabular
information for time zone decoding, since there is no *nix standard
system interface to provide access to general, cross-timezone
information. The underlying OS <emphasis>is</emphasis> used to
provide time zone information for <emphasis>output</emphasis>, however.
information for time zone decoding, since there is no standard
operating system interface to provide access to general,
cross-time zone information. The underlying operating system
<emphasis>is</emphasis> used to provide time zone information for
<emphasis>output</emphasis>, however.
</para>
<para>
The following table of time zones recognized by
<productname>PostgreSQL</productname> is organized by time
zone offset from UTC, rather than alphabetically; this is intended
to facilitate
The table is organized by time zone offset from <acronym>UTC</>,
rather than alphabetically; this is intended to facilitate
matching local usage with recognized abbreviations for cases where
these might differ.
</para>
<table tocentry="1">
<title><productname>PostgreSQL</productname> Recognized Time Zones</title>
<titleabbrev>Time Zones</titleabbrev>
<table id="datetime-timezone-table">
<title>Time Zone Abbreviations</title>
<tgroup cols="3">
<thead>
<row>
@ -749,31 +944,29 @@ Date/time details
</tbody>
</tgroup>
</table>
</para>
<sect2>
<formalpara>
<title>Australian Time Zones</title>
<para>
Australian time zones and their naming variants
account for fully one quarter of all time zones in the
<productname>PostgreSQL</productname> time zone lookup table.
There are two naming conflicts with time zones commonly used
in the United States, <literal>CST</literal> and <literal>EST</literal>.
There are three naming conflicts between Australian time zone
names with time zones commonly used in North and South America:
<literal>ACST</literal>, <literal>CST</literal>, and
<literal>EST</literal>. If the run-time option
<varname>AUSTRALIAN_TIMEZONES</varname> is set to true then
<literal>ACST</literal>, <literal>CST</literal>,
<literal>EST</literal>, and <literal>SAT</literal> are interpreted
as Australian time zone names, as shown in <xref
linkend="datetime-oztz-table">. If it is false (which is the
default), then <literal>ACST</literal>, <literal>CST</literal>,
and <literal>EST</literal> are taken as American time zone names,
and <literal>SAT</literal> is interpreted as a noise word
indicating Saturday.
</para>
</formalpara>
<para>
If the run-time option <literal>AUSTRALIAN_TIMEZONES</literal> is set
then <literal>CST</literal>, <literal>EST</literal>, and
<literal>SAT</literal> will be
interpreted as Australian timezone names. Without this option,
<literal>CST</literal> and <literal>EST</literal> are taken as
American timezone names, while <literal>SAT</literal> is interpreted as a
noise word indicating <literal>Saturday</literal>.
<table tocentry="1">
<title><productname>PostgreSQL</productname> Australian Time Zones</title>
<titleabbrev>Australian Time Zones</titleabbrev>
<table id="datetime-oztz-table">
<title>Australian Time Zone Abbreviations</title>
<tgroup cols="3">
<thead>
<row>
@ -806,196 +999,10 @@ Date/time details
</tbody>
</tgroup>
</table>
</para>
</sect2>
<sect2>
<title>Date/Time Input Interpretation</title>
</sect1>
<para>
The date/time types are all decoded using a common set of routines.
</para>
<procedure>
<title>Date/Time Input Interpretation</title>
<step>
<para>
Break the input string into tokens and categorize each token as
a string, time, time zone, or number.
</para>
<substeps>
<step>
<para>
If the numeric token contains a colon (":"), this is a time
string. Include all subsequent digits and colons.
</para>
</step>
<step>
<para>
If the numeric token contains a dash ("-"), slash ("/"), or
two or more dots ("."),
this is a date string which may have a text month.
</para>
</step>
<step>
<para>
If the token is numeric only, then it is either a single field
or an ISO-8601 concatenated date
(e.g. <literal>19990113</literal> for January 13, 1999)
or time (e.g. 141516 for 14:15:16).
</para>
</step>
<step>
<para>
If the token starts with a plus ("+") or minus ("-"),
then it is either a time zone or a special field.
</para>
</step>
</substeps>
</step>
<step>
<para>
If the token is a text string, match up with possible strings.
</para>
<substeps>
<step>
<para>
Do a binary-search table lookup for the token
as either a special string (e.g. <literal>today</literal>),
day (e.g. <literal>Thursday</literal>),
month (e.g. <literal>January</literal>),
or noise word (e.g. <literal>at</literal>, <literal>on</literal>).
</para>
<para>
Set field values and bit mask for fields.
For example, set year, month, day for <literal>today</literal>,
and additionally hour, minute, second for <literal>now</literal>.
</para>
</step>
<step>
<para>
If not found, do a similar binary-search table lookup to match
the token with a time zone.
</para>
</step>
<step>
<para>
If not found, throw an error.
</para>
</step>
</substeps>
</step>
<step>
<para>
The token is a number or number field.
</para>
<substeps>
<step>
<para>
If there are more than 4 digits,
and if no other date fields have been previously read, then interpret
as a <quote>concatenated date</quote> (e.g. <literal>19990118</literal>). 8
and 6 digits are interpreted as year, month, and day, while 7
and 5 digits are interpreted as year, day of year, respectively.
</para>
</step>
<step>
<para>
If the token is three digits
and a year has already been decoded, then interpret as day of year.
</para>
</step>
<step>
<para>
If four or six digits and a year has already been read, then
interpret as a time.
</para>
</step>
<step>
<para>
If four or more digits, then interpret as a year.
</para>
</step>
<step>
<para>
If in European date mode, and if the day field has not yet been read,
and if the value is less than or equal to 31, then interpret as a day.
</para>
</step>
<step>
<para>
If the month field has not yet been read,
and if the value is less than or equal to 12, then interpret as a month.
</para>
</step>
<step>
<para>
If the day field has not yet been read,
and if the value is less than or equal to 31, then interpret as a day.
</para>
</step>
<step>
<para>
If two digits or four or more digits, then interpret as a year.
</para>
</step>
<step>
<para>
Otherwise, throw an error.
</para>
</step>
</substeps>
</step>
<step>
<para>
If BC has been specified, negate the year and add one for
internal storage
(there is no year zero in the Gregorian calendar, so numerically
<literal>1BC</literal> becomes year zero).
</para>
</step>
<step>
<para>
If BC was not specified, and if the year field was two digits in length, then
adjust the year to 4 digits. If the field was less than 70, then add 2000;
otherwise, add 1900.
<tip>
<para>
Gregorian years 1-99AD may be entered by using 4 digits with leading
zeros (e.g. 0099 is 99AD). Previous versions of
<productname>PostgreSQL</productname> accepted years with three
digits and with single digits, but as of version 7.0 the rules have
been tightened up to reduce the possibility of ambiguity.
</para>
</tip>
</para>
</step>
</procedure>
</sect2>
</sect1>
<sect1 id="units-history">
<sect1 id="units-history">
<title>History of Units</title>
<note>
@ -1015,22 +1022,20 @@ Date/time details
to noon UTC on 2 January 4713 BC.
</para>
<para>
<quote>Julian Day</quote> is different from <quote>Julian Date</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 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.
The accumulating calendar error prompted Pope Gregory XIII
to reform the calendar in accordance with instructions
from the Council of Trent.
<para>
The <quote>Julian Day</quote> is different from the <quote>Julian
Date</quote>. The Julian date refers to the Julian calendar, which
was introduced by Julius Caesar in 45 BC. It was in common use
until the 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.
</para>
<para>
The accumulating calendar error prompted
Pope Gregory XIII to reform the calendar in accordance with
instructions from the Council of Trent.
In the Gregorian calendar, the tropical year is approximated as
365 + 97 / 400 days = 365.2425 days. Thus it takes approximately 3300
years for the tropical year to shift one day with respect to the
@ -1066,37 +1071,36 @@ Date/time details
This was observed in Italy, Poland, Portugal, and Spain. Other Catholic
countries followed shortly after, but Protestant countries were
reluctant to change, and the Greek orthodox countries didn't change
until the start of this century.
until the start of the 20th century.
The reform was observed by Great Britain and Dominions (including what is
now the USA) in 1752.
Thus 2 Sep 1752 was followed by 14 Sep 1752.
Thus 2 September 1752 was followed by 14 September 1752.
This is why Unix systems have <application>cal</application>
This is why Unix systems have the <command>cal</command> program
produce the following:
<programlisting>
% cal 9 1752
<screen>
$ <userinput>cal 9 1752</userinput>
September 1752
S M Tu W Th F S
1 2 14 15 16
17 18 19 20 21 22 23
24 25 26 27 28 29 30
</programlisting>
</screen>
</para>
<note>
<para>
SQL92 states that
<quote>Within the definition of a <quote>datetime literal</quote>,
the <quote>datetime value</quote>s are constrained by the
natural rules for dates and times
according to the Gregorian calendar</quote>.
Dates between 1752-09-03 and 1752-09-13, although eliminated in
some countries by Papal fiat, conform to
<quote>natural rules</quote> and are hence valid dates.
</para>
</note>
<note>
<para>
The SQL standard states that <quote>Within the definition of a
<quote>datetime literal</quote>, the <quote>datetime
value</quote>s are constrained by the natural rules for dates and
times according to the Gregorian calendar</quote>. Dates between
1752-09-03 and 1752-09-13, although eliminated in some countries
by Papal fiat, conform to <quote>natural rules</quote> and are
hence valid dates.
</para>
</note>
<para>
Different calendars have been developed in various parts of the
@ -1108,7 +1112,7 @@ Date/time details
calendar in 2637 BC.
The People's Republic of China uses the Gregorian calendar
for civil purposes. Chinese calendar is used for determining
for civil purposes. The Chinese calendar is used for determining
festivals.
</para>
</sect1>

16
doc/src/sgml/ddl.sgml
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@ -1,4 +1,4 @@
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/ddl.sgml,v 1.8 2002/10/24 21:10:58 tgl Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/ddl.sgml,v 1.8.2.1 2002/11/10 12:45:42 petere Exp $ -->
<chapter id="ddl">
<title>Data Definition</title>
@ -222,7 +222,7 @@ DROP TABLE products;
<para>
The identity (transaction ID) of the deleting transaction, or
zero for an undeleted tuple. It is possible for this field to
be nonzero in a visible tuple: that usually indicates that the
be nonzero in a visible tuple: That usually indicates that the
deleting transaction hasn't committed yet, or that an attempted
deletion was rolled back.
</para>
@ -353,7 +353,7 @@ CREATE TABLE products (
price numeric <emphasis>CONSTRAINT positive_price</emphasis> CHECK (price > 0)
);
</programlisting>
To specify a named constraint, use the key word
So, to specify a named constraint, use the key word
<literal>CONSTRAINT</literal> followed by an identifier followed
by the constraint definition.
</para>
@ -382,7 +382,7 @@ CREATE TABLE products (
</para>
<para>
We say that the first two are column constraints, whereas the
We say that the first two constraints are column constraints, whereas the
third one is a table constraint because it is written separately
from the column definitions. Column constraints can also be
written as table constraints, while the reverse is not necessarily
@ -931,7 +931,7 @@ WHERE c.altitude &gt; 500 and c.tableoid = p.oid;
<para>
In previous versions of <productname>PostgreSQL</productname>, the
default was not to get access to child tables. This was found to
be error prone and is also in violation of SQL99. Under the old
be error prone and is also in violation of the SQL standard. Under the old
syntax, to get the sub-tables you append <literal>*</literal> to the table name.
For example
<programlisting>
@ -1609,7 +1609,7 @@ REVOKE CREATE ON public FROM PUBLIC;
standard. Therefore, many users consider qualified names to
really consist of
<literal><replaceable>username</>.<replaceable>tablename</></literal>.
This is also supported by PostgreSQL if you create a per-user
This is how PostgreSQL will effectively behave if you create a per-user
schema for every user.
</para>
@ -1693,8 +1693,8 @@ DROP TABLE products CASCADE;
</screen>
and all the dependent objects will be removed. In this case, it
doesn't remove the orders table, it only removes the foreign key
constraint. (If you want to check what DROP ... CASCADE will do,
run DROP without CASCADE and read the NOTICEs.)
constraint. (If you want to check what <literal>DROP ... CASCADE</> will do,
run <command>DROP</> without <literal>CASCADE</> and read the <literal>NOTICE</> messages.)
</para>
<para>

19
doc/src/sgml/dml.sgml
View File

@ -1,4 +1,4 @@
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/dml.sgml,v 1.2 2002/10/20 05:05:46 tgl Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/dml.sgml,v 1.2.2.1 2002/11/10 12:45:42 petere Exp $ -->
<chapter id="dml">
<title>Data Manipulation</title>
@ -23,10 +23,10 @@
<para>
When a table is created, it contains no data. The first thing to
do before a database can be of much use is to insert data. Data is
inserted one row at a time. This does not mean that there are no
means to <quote>bulk load</quote> many rows efficiently. But there
is no way to insert less than one row at a time. Even if you know
only some column values, a complete row must be created.
conceptually inserted one row at a time. Of course you can also
insert more than one row, but there is no way to insert less than
one row at a time. Even if you know only some column values, a
complete row must be created.
</para>
<para>
@ -84,6 +84,15 @@ INSERT INTO products (product_no, name, price) VALUES (1, 'Cheese', DEFAULT);
INSERT INTO products DEFAULT VALUES;
</programlisting>
</para>
<tip>
<para>
To do <quote>bulk loads</quote>, that is, inserting a lot of data,
take a look at the <command>COPY</command> command (see
&cite-reference;). It is not as flexible as the
<command>INSERT</command> command, but more efficient.
</para>
</tip>
</sect1>
<sect1 id="dml-update">

1390
doc/src/sgml/func.sgml
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176
doc/src/sgml/indices.sgml
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@ -1,4 +1,4 @@
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/indices.sgml,v 1.37 2002/09/21 18:32:53 petere Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/indices.sgml,v 1.37.2.1 2002/11/10 12:45:42 petere Exp $ -->
<chapter id="indexes">
<title id="indexes-title">Indexes</title>
@ -432,172 +432,6 @@ SELECT am.amname AS acc_method,
</sect1>
<sect1 id="keys">
<title id="keys-title">Keys</title>
<para>
<note>
<title>Author</title>
<para>
Written by Herouth Maoz (<email>herouth@oumail.openu.ac.il</email>).
This originally appeared on the User's Mailing List on 1998-03-02
in response to the question:
"What is the difference between PRIMARY KEY and UNIQUE constraints?".
</para>
</note>
</para>
<para>
<literallayout>
Subject: Re: [QUESTIONS] PRIMARY KEY | UNIQUE
What's the difference between:
PRIMARY KEY(fields,...) and
UNIQUE (fields,...)
- Is this an alias?
- If PRIMARY KEY is already unique, then why
is there another kind of key named UNIQUE?
</literallayout>
</para>
<para>
A primary key is the field(s) used to identify a specific row. For example,
Social Security numbers identifying a person.
</para>
<para>
A simply UNIQUE combination of fields has nothing to do with identifying
the row. It's simply an integrity constraint. For example, I have
collections of links. Each collection is identified by a unique number,
which is the primary key. This key is used in relations.
</para>
<para>
However, my application requires that each collection will also have a
unique name. Why? So that a human being who wants to modify a collection
will be able to identify it. It's much harder to know, if you have two
collections named <quote>Life Science</quote>, the one tagged 24433 is the one you
need, and the one tagged 29882 is not.
</para>
<para>
So, the user selects the collection by its name. We therefore make sure,
within the database, that names are unique. However, no other table in the
database relates to the collections table by the collection Name. That
would be very inefficient.
</para>
<para>
Moreover, despite being unique, the collection name does not actually
define the collection! For example, if somebody decided to change the name
of the collection from <quote>Life Science</quote> to <quote>Biology</quote>, it will still be the
same collection, only with a different name. As long as the name is unique,
that's OK.
</para>
<para>
So:
<itemizedlist>
<listitem>
<para>
Primary key:
<itemizedlist spacing="compact" mark="bullet">
<listitem>
<para>
Is used for identifying the row and relating to it.
</para>
</listitem>
<listitem>
<para>
Is impossible (or hard) to update.
</para>
</listitem>
<listitem>
<para>
Should not allow null values.
</para>
</listitem>
</itemizedlist>
</para>
</listitem>
<listitem>
<para>
Unique field(s):
<itemizedlist spacing="compact" mark="bullet">
<listitem>
<para>
Are used as an alternative access to the row.
</para>
</listitem>
<listitem>
<para>
Are updatable, so long as they are kept unique.
</para>
</listitem>
<listitem>
<para>
Null values are acceptable.
</para>
</listitem>
</itemizedlist>
</para>
</listitem>
</itemizedlist>
</para>
<para>
As for why no non-unique keys are defined explicitly in standard
<acronym>SQL</acronym> syntax? Well, you
must understand that indexes are implementation-dependent.
<acronym>SQL</acronym> does not
define the implementation, merely the relations between data in the
database. <productname>PostgreSQL</productname> does allow
non-unique indexes, but indexes
used to enforce <acronym>SQL</acronym> keys are always unique.
</para>
<para>
Thus, you may query a table by any combination of its columns, despite the
fact that you don't have an index on these columns. The indexes are merely
an implementation aid that each <acronym>RDBMS</acronym> offers
you, in order to cause
commonly used queries to be done more efficiently.
Some <acronym>RDBMS</acronym> may give you
additional measures, such as keeping a key stored in main memory. They will
have a special command, for example
<synopsis>
CREATE MEMSTORE ON <replaceable>table</replaceable> COLUMNS <replaceable>cols</replaceable>
</synopsis>
(This is not an existing command, just an example.)
</para>
<para>
In fact, when you create a primary key or a unique combination of fields,
nowhere in the <acronym>SQL</acronym> specification does it say
that an index is created, nor that
the retrieval of data by the key is going to be more efficient than a
sequential scan!
</para>
<para>
So, if you want to use a combination of fields that is not unique as a
secondary key, you really don't have to specify anything - just start
retrieving by that combination! However, if you want to make the retrieval
efficient, you'll have to resort to the means your
<acronym>RDBMS</acronym> provider gives you
- be it an index, my imaginary <literal>MEMSTORE</literal> command, or an intelligent
<acronym>RDBMS</acronym>
that creates indexes without your knowledge based on the fact that you have
sent it many queries based on a specific combination of keys... (It learns
from experience).
</para>
</sect1>
<sect1 id="indexes-partial">
<title>Partial Indexes</title>
@ -876,8 +710,8 @@ CREATE UNIQUE INDEX tests_success_constraint ON tests (subject, target)
<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
various plan types (described in the &cite-admin;).
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
@ -906,8 +740,8 @@ CREATE UNIQUE INDEX tests_success_constraint ON tests (subject, target)
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
run-time parameters (described in the &cite-admin;).
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).

132
doc/src/sgml/keywords.sgml
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@ -1,4 +1,4 @@
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/keywords.sgml,v 2.7 2002/11/02 18:41:21 tgl Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/keywords.sgml,v 2.7.2.1 2002/11/10 12:45:42 petere Exp $ -->
<appendix id="sql-keywords-appendix">
<title><acronym>SQL</acronym> Key Words</title>
@ -232,13 +232,13 @@
</row>
<row>
<entry><token>ASSERTION</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
<row>
<entry><token>ASSIGNMENT</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
@ -262,7 +262,7 @@
</row>
<row>
<entry><token>AUTHORIZATION</token></entry>
<entry>non-reserved</entry>
<entry>reserved (can be function)</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -296,6 +296,12 @@
<entry>non-reserved</entry>
<entry>reserved</entry>
</row>
<row>
<entry><token>BIGINT</token></entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>BINARY</token></entry>
<entry>reserved (can be function)</entry>
@ -328,7 +334,7 @@
</row>
<row>
<entry><token>BOOLEAN</token></entry>
<entry></entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry>reserved</entry>
<entry></entry>
</row>
@ -370,7 +376,7 @@
</row>
<row>
<entry><token>CALLED</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
@ -490,7 +496,7 @@
</row>
<row>
<entry><token>CLASS</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry></entry>
</row>
@ -680,6 +686,12 @@
<entry>reserved</entry>
<entry>reserved</entry>
</row>
<row>
<entry><token>CONVERSION</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>CONVERT</token></entry>
<entry>non-reserved (cannot be function or type)</entry>
@ -706,7 +718,7 @@
</row>
<row>
<entry><token>CREATE</token></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -832,7 +844,7 @@
</row>
<row>
<entry><token>DEALLOCATE</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -880,7 +892,7 @@
</row>
<row>
<entry><token>DEFINER</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
@ -988,7 +1000,7 @@
</row>
<row>
<entry><token>DOMAIN</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -1126,7 +1138,7 @@
</row>
<row>
<entry><token>EXTERNAL</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -1252,7 +1264,7 @@
</row>
<row>
<entry><token>GET</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -1276,7 +1288,7 @@
</row>
<row>
<entry><token>GRANT</token></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -1358,12 +1370,24 @@
<entry>reserved</entry>
<entry>reserved</entry>
</row>
<row>
<entry><token>IMMUTABLE</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>IMPLEMENTATION</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
<row>
<entry><token>IMPLICIT</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>IN</token></entry>
<entry>reserved (can be function)</entry>
@ -1426,7 +1450,7 @@
</row>
<row>
<entry><token>INPUT</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -1462,13 +1486,13 @@
</row>
<row>
<entry><token>INT</token></entry>
<entry></entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
<row>
<entry><token>INTEGER</token></entry>
<entry></entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -1492,7 +1516,7 @@
</row>
<row>
<entry><token>INVOKER</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
@ -1642,13 +1666,13 @@
</row>
<row>
<entry><token>LOCALTIME</token></entry>
<entry></entry>
<entry>reserved</entry>
<entry>reserved</entry>
<entry></entry>
</row>
<row>
<entry><token>LOCALTIMESTAMP</token></entry>
<entry></entry>
<entry>reserved</entry>
<entry>reserved</entry>
<entry></entry>
</row>
@ -2056,7 +2080,7 @@
</row>
<row>
<entry><token>OVERLAY</token></entry>
<entry></entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
@ -2156,6 +2180,12 @@
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>PLACING</token></entry>
<entry>reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>PLI</token></entry>
<entry></entry>
@ -2194,7 +2224,7 @@
</row>
<row>
<entry><token>PREPARE</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -2236,7 +2266,7 @@
</row>
<row>
<entry><token>PUBLIC</token></entry>
<entry>reserved (can be function)</entry>
<entry></entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -2254,9 +2284,15 @@
</row>
<row>
<entry><token>REAL</token></entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
<row>
<entry><token>RECHECK</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
<row>
<entry><token>RECURSIVE</token></entry>
@ -2416,7 +2452,7 @@
</row>
<row>
<entry><token>ROW</token></entry>
<entry>non-reserved</entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry>reserved</entry>
<entry></entry>
</row>
@ -2494,7 +2530,7 @@
</row>
<row>
<entry><token>SECURITY</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
@ -2578,13 +2614,13 @@
</row>
<row>
<entry><token>SIMILAR</token></entry>
<entry></entry>
<entry>reserved (can be function)</entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
<row>
<entry><token>SIMPLE</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>non-reserved</entry>
<entry></entry>
</row>
@ -2596,7 +2632,7 @@
</row>
<row>
<entry><token>SMALLINT</token></entry>
<entry></entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -2672,6 +2708,12 @@
<entry>reserved</entry>
<entry></entry>
</row>
<row>
<entry><token>STABLE</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>START</token></entry>
<entry>non-reserved</entry>
@ -2714,6 +2756,18 @@
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>STORAGE</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>STRICT</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>STRUCTURE</token></entry>
<entry></entry>
@ -2914,7 +2968,7 @@
</row>
<row>
<entry><token>TREAT</token></entry>
<entry></entry>
<entry>non-reserved (cannot be function or type)</entry>
<entry>reserved</entry>
<entry></entry>
</row>
@ -3046,7 +3100,7 @@
</row>
<row>
<entry><token>USAGE</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>
@ -3092,6 +3146,12 @@
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>VALIDATOR</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>VALUE</token></entry>
<entry></entry>
@ -3140,6 +3200,12 @@
<entry>reserved</entry>
<entry>reserved</entry>
</row>
<row>
<entry><token>VOLATILE</token></entry>
<entry>non-reserved</entry>
<entry></entry>
<entry></entry>
</row>
<row>
<entry><token>WHEN</token></entry>
<entry>reserved</entry>
@ -3178,7 +3244,7 @@
</row>
<row>
<entry><token>WRITE</token></entry>
<entry></entry>
<entry>non-reserved</entry>
<entry>reserved</entry>
<entry>reserved</entry>
</row>

131
doc/src/sgml/mvcc.sgml
View File

@ -1,5 +1,5 @@
<!--
$Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere Exp $
$Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28.2.1 2002/11/10 12:45:42 petere Exp $
-->
<chapter id="mvcc">
@ -9,24 +9,23 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
<primary>concurrency</primary>
</indexterm>
<abstract>
<para>
Multiversion Concurrency Control
(MVCC)
is an advanced technique for improving database performance in a
multiuser environment.
Vadim Mikheev (<email>vadim@krs.ru</email>) provided
the implementation for <productname>PostgreSQL</productname>.
</para>
</abstract>
<para>
This chapter describes the behavior of the PostgreSQL database
system when two or more sessions try to access the same data at the
same time. The goals in that situation are to allow efficient
access for all sessions while maintaining strict data integrity.
Every developer of database applications should be familiar with
the topics covered in this chapter.
</para>
<sect1 id="mvcc-intro">
<title>Introduction</title>
<para>
Unlike most other database systems which use locks for concurrency control,
Unlike traditional database systems which use locks for concurrency control,
<productname>PostgreSQL</productname>
maintains data consistency by using a multiversion model.
maintains data consistency by using a multiversion model
(Multiversion Concurrency Control, <acronym>MVCC</acronym>).
This means that while querying a database each transaction sees
a snapshot of data (a <firstterm>database version</firstterm>)
as it was some
@ -56,7 +55,7 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
<title>Transaction Isolation</title>
<para>
The <acronym>ANSI</acronym>/<acronym>ISO</acronym> <acronym>SQL</acronym>
The <acronym>SQL</acronym>
standard defines four levels of transaction
isolation in terms of three phenomena that must be prevented
between concurrent transactions.
@ -65,8 +64,8 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
<variablelist>
<varlistentry>
<term>
dirty reads
<indexterm><primary>dirty reads</primary></indexterm>
dirty read
<indexterm><primary>dirty read</primary></indexterm>
</term>
<listitem>
<para>
@ -77,8 +76,8 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
<varlistentry>
<term>
non-repeatable reads
<indexterm><primary>non-repeatable reads</primary></indexterm>
nonrepeatable read
<indexterm><primary>nonrepeatable read</primary></indexterm>
</term>
<listitem>
<para>
@ -92,7 +91,7 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
<varlistentry>
<term>
phantom read
<indexterm><primary>phantom reads</primary></indexterm>
<indexterm><primary>phantom read</primary></indexterm>
</term>
<listitem>
<para>
@ -111,6 +110,7 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
</indexterm>
The four transaction isolation levels and the corresponding
behaviors are described in <xref linkend="mvcc-isolevel-table">.
</para>
<table tocentry="1" id="mvcc-isolevel-table">
<title><acronym>SQL</acronym> Transaction Isolation Levels</title>
@ -125,7 +125,7 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
Dirty Read
</entry>
<entry>
Non-Repeatable Read
Nonrepeatable Read
</entry>
<entry>
Phantom Read
@ -195,15 +195,13 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
</tbody>
</tgroup>
</table>
</para>
<para>
<productname>PostgreSQL</productname>
offers the read committed and serializable isolation levels.
</para>
</sect1>
<sect1 id="xact-read-committed">
<sect2 id="xact-read-committed">
<title>Read Committed Isolation Level</title>
<indexterm>
@ -229,7 +227,7 @@ $Header: /cvsroot/pgsql/doc/src/sgml/mvcc.sgml,v 2.28 2002/09/21 18:32:53 petere
</para>
<para>
<command>UPDATE</command>, <command>DELETE</command> and <command>SELECT
<command>UPDATE</command>, <command>DELETE</command>, and <command>SELECT
FOR UPDATE</command> commands behave the same as <command>SELECT</command>
in terms of searching for target rows: they will only find target rows
that were committed as of the query start time. However, such a target
@ -287,9 +285,9 @@ COMMIT;
be necessary to guarantee a more rigorously consistent view of the
database than the Read Committed mode provides.
</para>
</sect1>
</sect2>
<sect1 id="xact-serializable">
<sect2 id="xact-serializable">
<title>Serializable Isolation Level</title>
<indexterm>
@ -316,13 +314,13 @@ COMMIT;
committed.) This is different from Read Committed in that the
<command>SELECT</command>
sees a snapshot as of the start of the transaction, not as of the start
of the current query within the transaction. Successive
of the current query within the transaction. Thus, successive
<command>SELECT</command>s within a single transaction always see the same
data.
</para>
<para>
<command>UPDATE</command>, <command>DELETE</command> and <command>SELECT
<command>UPDATE</command>, <command>DELETE</command>, and <command>SELECT
FOR UPDATE</command> commands behave the same as <command>SELECT</command>
in terms of searching for target rows: they will only find target rows
that were committed as of the transaction start time. However, such a
@ -370,7 +368,8 @@ ERROR: Can't serialize access due to concurrent update
a transaction performs several successive queries that must see
identical views of the database.
</para>
</sect1>
</sect2>
</sect1>
<sect1 id="explicit-locking">
<title>Explicit Locking</title>
@ -421,8 +420,7 @@ ERROR: Can't serialize access due to concurrent update
To examine a list of the currently outstanding locks in a
database server, use the <literal>pg_locks</literal> system
view. For more information on monitoring the status of the lock
manager subsystem, refer to the <citetitle>Administrator's
Guide</citetitle>.
manager subsystem, refer to the &cite-admin;.
</para>
<variablelist>
@ -647,14 +645,14 @@ ERROR: Can't serialize access due to concurrent update
<para>
Use of explicit locking can cause <firstterm>deadlocks</>, wherein
two (or more) transactions each hold locks that the other wants.
For example, if transaction 1 acquires exclusive lock on table A
and then tries to acquire exclusive lock on table B, while transaction
2 has already exclusive-locked table B and now wants exclusive lock
For example, if transaction 1 acquires an exclusive lock on table A
and then tries to acquire an exclusive lock on table B, while transaction
2 has already exclusive-locked table B and now wants an exclusive lock
on table A, then neither one can proceed.
<productname>PostgreSQL</productname> automatically detects deadlock
situations and resolves them by aborting one of the transactions
involved, allowing the other(s) to complete. (Exactly which transaction
will be aborted is difficult to predict, and should not be relied on.)
will be aborted is difficult to predict and should not be relied on.)
</para>
<para>
@ -678,7 +676,7 @@ ERROR: Can't serialize access due to concurrent update
</sect1>
<sect1 id="applevel-consistency">
<title>Data consistency checks at the application level</title>
<title>Data Consistency Checks at the Application Level</title>
<para>
Because readers in <productname>PostgreSQL</productname>
@ -718,11 +716,10 @@ ERROR: Can't serialize access due to concurrent update
<note>
<para>
Before version 6.5 <productname>PostgreSQL</productname>
used read-locks and so the
above consideration is also the case
when upgrading to 6.5 (or higher) from previous
<productname>PostgreSQL</productname> versions.
Before version 6.5 <productname>PostgreSQL</productname> used
read locks, and so the above consideration is also the case when
upgrading from <productname>PostgreSQL</productname> versions
prior to 6.5.
</para>
</note>
</para>
@ -732,7 +729,7 @@ ERROR: Can't serialize access due to concurrent update
example, a banking application might wish to check that the sum of
all credits in one table equals the sum of debits in another table,
when both tables are being actively updated. Comparing the results of two
successive SELECT SUM(...) commands will not work reliably under
successive <literal>SELECT SUM(...)</literal> commands will not work reliably under
Read Committed mode, since the second query will likely include the results
of transactions not counted by the first. Doing the two sums in a
single serializable transaction will give an accurate picture of the
@ -758,7 +755,8 @@ ERROR: Can't serialize access due to concurrent update
the table are still running --- but if the snapshot seen by the
transaction predates obtaining the lock, it may predate some now-committed
changes in the table. A serializable transaction's snapshot is actually
frozen at the start of its first query (SELECT/INSERT/UPDATE/DELETE), so
frozen at the start of its first query (<literal>SELECT</>, <literal>INSERT</>,
<literal>UPDATE</>, or <literal>DELETE</>), so
it's possible to obtain explicit locks before the snapshot is
frozen.
</para>
@ -781,12 +779,26 @@ ERROR: Can't serialize access due to concurrent update
<variablelist>
<varlistentry>
<term>
<acronym>GiST</acronym> and R-Tree indexes
B-tree indexes
</term>
<listitem>
<para>
Short-term share/exclusive page-level locks are used for
read/write access. Locks are released immediately after each
index tuple is fetched or inserted. B-tree indexes provide
the highest concurrency without deadlock conditions.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>
<acronym>GiST</acronym> and R-tree indexes
</term>
<listitem>
<para>
Share/exclusive index-level locks are used for read/write access.
Locks are released after statement is done.
Locks are released after the statement (command) is done.
</para>
</listitem>
</varlistentry>
@ -797,31 +809,10 @@ ERROR: Can't serialize access due to concurrent update
</term>
<listitem>
<para>
Share/exclusive page-level locks are used for read/write access.
Locks are released after page is processed.
</para>
<para>
Page-level locks provide better concurrency than index-level ones
but are subject to deadlocks.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>
B-tree indexes
</term>
<listitem>
<para>
Short-term share/exclusive page-level locks are used for
read/write access. Locks are released immediately after each index
tuple is fetched/inserted.
</para>
<para>
B-tree indexes provide the highest concurrency without deadlock
conditions.
Share/exclusive page-level locks are used for read/write
access. Locks are released after the page is processed.
Page-level locks provide better concurrency than index-level
ones but are liable to deadlocks.
</para>
</listitem>
</varlistentry>

240
doc/src/sgml/perform.sgml
View File

@ -1,5 +1,5 @@
<!--
$Header: /cvsroot/pgsql/doc/src/sgml/perform.sgml,v 1.21 2002/09/21 18:32:53 petere Exp $
$Header: /cvsroot/pgsql/doc/src/sgml/perform.sgml,v 1.21.2.1 2002/11/10 12:45:42 petere Exp $
-->
<chapter id="performance-tips">
@ -32,30 +32,30 @@ $Header: /cvsroot/pgsql/doc/src/sgml/perform.sgml,v 1.21 2002/09/21 18:32:53 pet
<itemizedlist>
<listitem>
<para>
Estimated start-up cost (time expended before output scan can start,
e.g., time to do the sorting in a SORT node).
Estimated start-up cost (Time expended before output scan can start,
e.g., time to do the sorting in a sort node.)
</para>
</listitem>
<listitem>
<para>
Estimated total cost (if all tuples are retrieved, which they may not
be --- a query with a LIMIT will stop short of paying the total cost,
for example).
Estimated total cost (If all rows are retrieved, which they may not
be --- a query with a <literal>LIMIT</> clause will stop short of paying the total cost,
for example.)
</para>
</listitem>
<listitem>
<para>
Estimated number of rows output by this plan node (again, only if
executed to completion).
Estimated number of rows output by this plan node (Again, only if
executed to completion.)
</para>
</listitem>
<listitem>
<para>
Estimated average width (in bytes) of rows output by this plan
node.
node
</para>
</listitem>
</itemizedlist>
@ -64,9 +64,9 @@ $Header: /cvsroot/pgsql/doc/src/sgml/perform.sgml,v 1.21 2002/09/21 18:32:53 pet
<para>
The costs are measured in units of disk page fetches. (CPU effort
estimates are converted into disk-page units using some
fairly arbitrary fudge-factors. If you want to experiment with these
fairly arbitrary fudge factors. If you want to experiment with these
factors, see the list of run-time configuration parameters in the
<citetitle>Administrator's Guide</citetitle>.)
&cite-admin;.)
</para>
<para>
@ -74,17 +74,17 @@ $Header: /cvsroot/pgsql/doc/src/sgml/perform.sgml,v 1.21 2002/09/21 18:32:53 pet
the cost of all its child nodes. It's also important to realize that
the cost only reflects things that the planner/optimizer cares about.
In particular, the cost does not consider the time spent transmitting
result tuples to the frontend --- which could be a pretty dominant
result rows to the frontend --- which could be a pretty dominant
factor in the true elapsed time, but the planner ignores it because
it cannot change it by altering the plan. (Every correct plan will
output the same tuple set, we trust.)
output the same row set, we trust.)
</para>
<para>
Rows output is a little tricky because it is <emphasis>not</emphasis> the
number of rows
processed/scanned by the query --- it is usually less, reflecting the
estimated selectivity of any WHERE-clause constraints that are being
estimated selectivity of any <literal>WHERE</>-clause constraints that are being
applied at this node. Ideally the top-level rows estimate will
approximate the number of rows actually returned, updated, or deleted
by the query.
@ -92,44 +92,44 @@ $Header: /cvsroot/pgsql/doc/src/sgml/perform.sgml,v 1.21 2002/09/21 18:32:53 pet
<para>
Here are some examples (using the regress test database after a
vacuum analyze, and 7.3 development sources):
<literal>VACUUM ANALYZE</>, and 7.3 development sources):
<programlisting>
<programlisting>
regression=# EXPLAIN SELECT * FROM tenk1;
QUERY PLAN
-------------------------------------------------------------
Seq Scan on tenk1 (cost=0.00..333.00 rows=10000 width=148)
</programlisting>
</programlisting>
</para>
<para>
This is about as straightforward as it gets. If you do
<programlisting>
<programlisting>
SELECT * FROM pg_class WHERE relname = 'tenk1';
</programlisting>
</programlisting>
you will find out that <classname>tenk1</classname> has 233 disk
pages and 10000 tuples. So the cost is estimated at 233 page
reads, defined as 1.0 apiece, plus 10000 * <varname>cpu_tuple_cost</varname> which is
currently 0.01 (try <command>show cpu_tuple_cost</command>).
pages and 10000 rows. So the cost is estimated at 233 page
reads, defined as costing 1.0 apiece, plus 10000 * <varname>cpu_tuple_cost</varname> which is
currently 0.01 (try <command>SHOW cpu_tuple_cost</command>).
</para>
<para>
Now let's modify the query to add a WHERE condition:
Now let's modify the query to add a <literal>WHERE</> condition:
<programlisting>
<programlisting>
regression=# EXPLAIN SELECT * FROM tenk1 WHERE unique1 &lt; 1000;
QUERY PLAN
------------------------------------------------------------
Seq Scan on tenk1 (cost=0.00..358.00 rows=1033 width=148)
Filter: (unique1 &lt; 1000)
</programlisting>
</programlisting>
The estimate of output rows has gone down because of the WHERE clause.
The estimate of output rows has gone down because of the <literal>WHERE</> clause.
However, the scan will still have to visit all 10000 rows, so the cost
hasn't decreased; in fact it has gone up a bit to reflect the extra CPU
time spent checking the WHERE condition.
time spent checking the <literal>WHERE</> condition.
</para>
<para>
@ -144,26 +144,26 @@ regression=# EXPLAIN SELECT * FROM tenk1 WHERE unique1 &lt; 1000;
<para>
Modify the query to restrict the condition even more:
<programlisting>
<programlisting>
regression=# EXPLAIN SELECT * FROM tenk1 WHERE unique1 &lt; 50;
QUERY PLAN
-------------------------------------------------------------------------------
Index Scan using tenk1_unique1 on tenk1 (cost=0.00..179.33 rows=49 width=148)
Index Cond: (unique1 &lt; 50)
</programlisting>
</programlisting>
and you will see that if we make the WHERE condition selective
and you will see that if we make the <literal>WHERE</> condition selective
enough, the planner will
eventually decide that an index scan is cheaper than a sequential scan.
This plan will only have to visit 50 tuples because of the index,
This plan will only have to visit 50 rows because of the index,
so it wins despite the fact that each individual fetch is more expensive
than reading a whole disk page sequentially.
</para>
<para>
Add another clause to the WHERE condition:
Add another clause to the <literal>WHERE</> condition:
<programlisting>
<programlisting>
regression=# EXPLAIN SELECT * FROM tenk1 WHERE unique1 &lt; 50 AND
regression-# stringu1 = 'xxx';
QUERY PLAN
@ -171,11 +171,11 @@ regression-# stringu1 = 'xxx';
Index Scan using tenk1_unique1 on tenk1 (cost=0.00..179.45 rows=1 width=148)
Index Cond: (unique1 &lt; 50)
Filter: (stringu1 = 'xxx'::name)
</programlisting>
</programlisting>
The added clause <literal>stringu1 = 'xxx'</literal> reduces the
output-rows estimate, but not the cost because we still have to visit the
same set of tuples. Notice that the <literal>stringu1</> clause
same set of rows. Notice that the <literal>stringu1</> clause
cannot be applied as an index condition (since this index is only on
the <literal>unique1</> column). Instead it is applied as a filter on
the rows retrieved by the index. Thus the cost has actually gone up
@ -185,7 +185,7 @@ regression-# stringu1 = 'xxx';
<para>
Let's try joining two tables, using the fields we have been discussing:
<programlisting>
<programlisting>
regression=# EXPLAIN SELECT * FROM tenk1 t1, tenk2 t2 WHERE t1.unique1 &lt; 50
regression-# AND t1.unique2 = t2.unique2;
QUERY PLAN
@ -197,30 +197,30 @@ regression-# AND t1.unique2 = t2.unique2;
-&gt; Index Scan using tenk2_unique2 on tenk2 t2
(cost=0.00..3.01 rows=1 width=148)
Index Cond: ("outer".unique2 = t2.unique2)
</programlisting>
</programlisting>
</para>
<para>
In this nested-loop join, the outer scan is the same index scan we had
in the example before last, and so its cost and row count are the same
because we are applying the <literal>unique1 &lt; 50</literal> WHERE clause at that node.
because we are applying the <literal>unique1 &lt; 50</literal> <literal>WHERE</> clause at that node.
The <literal>t1.unique2 = t2.unique2</literal> clause is not relevant yet, so it doesn't
affect row count of the outer scan. For the inner scan, the unique2 value of the
affect row count of the outer scan. For the inner scan, the <literal>unique2</> value of the
current
outer-scan tuple is plugged into the inner index scan
outer-scan row is plugged into the inner index scan
to produce an index condition like
<literal>t2.unique2 = <replaceable>constant</replaceable></literal>. So we get the
same inner-scan plan and costs that we'd get from, say, <literal>explain select
* from tenk2 where unique2 = 42</literal>. The costs of the loop node are then set
same inner-scan plan and costs that we'd get from, say, <literal>EXPLAIN SELECT
* FROM tenk2 WHERE unique2 = 42</literal>. The costs of the loop node are then set
on the basis of the cost of the outer scan, plus one repetition of the
inner scan for each outer tuple (49 * 3.01, here), plus a little CPU
inner scan for each outer row (49 * 3.01, here), plus a little CPU
time for join processing.
</para>
<para>
In this example the loop's output row count is the same as the product
of the two scans' row counts, but that's not true in general, because
in general you can have WHERE clauses that mention both relations and
in general you can have <literal>WHERE</> clauses that mention both relations and
so can only be applied at the join point, not to either input scan.
For example, if we added <literal>WHERE ... AND t1.hundred &lt; t2.hundred</literal>,
that would decrease the output row count of the join node, but not change
@ -233,9 +233,9 @@ regression-# AND t1.unique2 = t2.unique2;
flags for each plan type. (This is a crude tool, but useful. See
also <xref linkend="explicit-joins">.)
<programlisting>
regression=# set enable_nestloop = off;
SET VARIABLE
<programlisting>
regression=# SET enable_nestloop = off;
SET
regression=# EXPLAIN SELECT * FROM tenk1 t1, tenk2 t2 WHERE t1.unique1 &lt; 50
regression-# AND t1.unique2 = t2.unique2;
QUERY PLAN
@ -247,25 +247,25 @@ regression-# AND t1.unique2 = t2.unique2;
-&gt; Index Scan using tenk1_unique1 on tenk1 t1
(cost=0.00..179.33 rows=49 width=148)
Index Cond: (unique1 &lt; 50)
</programlisting>
</programlisting>
This plan proposes to extract the 50 interesting rows of <classname>tenk1</classname>
using ye same olde index scan, stash them into an in-memory hash table,
and then do a sequential scan of <classname>tenk2</classname>, probing into the hash table
for possible matches of <literal>t1.unique2 = t2.unique2</literal> at each <classname>tenk2</classname> tuple.
for possible matches of <literal>t1.unique2 = t2.unique2</literal> at each <classname>tenk2</classname> row.
The cost to read <classname>tenk1</classname> and set up the hash table is entirely start-up
cost for the hash join, since we won't get any tuples out until we can
cost for the hash join, since we won't get any rows out until we can
start reading <classname>tenk2</classname>. The total time estimate for the join also
includes a hefty charge for CPU time to probe the hash table
10000 times. Note, however, that we are NOT charging 10000 times 179.33;
includes a hefty charge for the CPU time to probe the hash table
10000 times. Note, however, that we are <emphasis>not</emphasis> charging 10000 times 179.33;
the hash table setup is only done once in this plan type.
</para>
<para>
It is possible to check on the accuracy of the planner's estimated costs
by using EXPLAIN ANALYZE. This command actually executes the query,
by using <command>EXPLAIN ANALYZE</>. This command actually executes the query,
and then displays the true run time accumulated within each plan node
along with the same estimated costs that a plain EXPLAIN shows.
along with the same estimated costs that a plain <command>EXPLAIN</command> shows.
For example, we might get a result like this:
<screen>
@ -296,7 +296,7 @@ regression-# WHERE t1.unique1 &lt; 50 AND t1.unique2 = t2.unique2;
<para>
In some query plans, it is possible for a subplan node to be executed more
than once. For example, the inner index scan is executed once per outer
tuple in the above nested-loop plan. In such cases, the
row in the above nested-loop plan. In such cases, the
<quote>loops</quote> value reports the
total number of executions of the node, and the actual time and rows
values shown are averages per-execution. This is done to make the numbers
@ -307,19 +307,19 @@ regression-# WHERE t1.unique1 &lt; 50 AND t1.unique2 = t2.unique2;
<para>
The <literal>Total runtime</literal> shown by <command>EXPLAIN ANALYZE</command> includes
executor start-up and shutdown time, as well as time spent processing
the result tuples. It does not include parsing, rewriting, or planning
time. For a SELECT query, the total run time will normally be just a
executor start-up and shut-down time, as well as time spent processing
the result rows. It does not include parsing, rewriting, or planning
time. For a <command>SELECT</> query, the total run time will normally be just a
little larger than the total time reported for the top-level plan node.
For INSERT, UPDATE, and DELETE queries, the total run time may be
For <command>INSERT</>, <command>UPDATE</>, and <command>DELETE</> commands, the total run time may be
considerably larger, because it includes the time spent processing the
result tuples. In these queries, the time for the top plan node
essentially is the time spent computing the new tuples and/or locating
result rows. In these commands, the time for the top plan node
essentially is the time spent computing the new rows and/or locating
the old ones, but it doesn't include the time spent making the changes.
</para>
<para>
It is worth noting that EXPLAIN results should not be extrapolated
It is worth noting that <command>EXPLAIN</> results should not be extrapolated
to situations other than the one you are actually testing; for example,
results on a toy-sized table can't be assumed to apply to large tables.
The planner's cost estimates are not linear and so it may well choose
@ -333,7 +333,7 @@ regression-# WHERE t1.unique1 &lt; 50 AND t1.unique2 = t2.unique2;
</sect1>
<sect1 id="planner-stats">
<title>Statistics used by the Planner</title>
<title>Statistics Used by the Planner</title>
<para>
As we saw in the previous section, the query planner needs to estimate
@ -351,8 +351,8 @@ regression-# WHERE t1.unique1 &lt; 50 AND t1.unique2 = t2.unique2;
with queries similar to this one:
<screen>
regression=# select relname, relkind, reltuples, relpages from pg_class
regression-# where relname like 'tenk1%';
regression=# SELECT relname, relkind, reltuples, relpages FROM pg_class
regression-# WHERE relname LIKE 'tenk1%';
relname | relkind | reltuples | relpages
---------------+---------+-----------+----------
tenk1 | r | 10000 | 233
@ -382,10 +382,10 @@ regression-# where relname like 'tenk1%';
<para>
Most queries retrieve only a fraction of the rows in a table, due
to having WHERE clauses that restrict the rows to be examined.
to having <literal>WHERE</> clauses that restrict the rows to be examined.
The planner thus needs to make an estimate of the
<firstterm>selectivity</> of WHERE clauses, that is, the fraction of
rows that match each clause of the WHERE condition. The information
<firstterm>selectivity</> of <literal>WHERE</> clauses, that is, the fraction of
rows that match each clause of the <literal>WHERE</> condition. The information
used for this task is stored in the <structname>pg_statistic</structname>
system catalog. Entries in <structname>pg_statistic</structname> are
updated by <command>ANALYZE</> and <command>VACUUM ANALYZE</> commands,
@ -406,7 +406,7 @@ regression-# where relname like 'tenk1%';
For example, we might do:
<screen>
regression=# select attname, n_distinct, most_common_vals from pg_stats where tablename = 'road';
regression=# SELECT attname, n_distinct, most_common_vals FROM pg_stats WHERE tablename = 'road';
attname | n_distinct | most_common_vals
---------+------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
name | -0.467008 | {"I- 580 Ramp","I- 880 Ramp","Sp Railroad ","I- 580 ","I- 680 Ramp","I- 80 Ramp","14th St ","5th St ","Mission Blvd","I- 880 "}
@ -414,12 +414,14 @@ regression=# select attname, n_distinct, most_common_vals from pg_stats where ta
(2 rows)
regression=#
</screen>
As of <productname>PostgreSQL</productname> 7.2 the following columns exist
in <structname>pg_stats</structname>:
</para>
<table>
<para>
<xref linkend="planner-pg-stats-table"> shows the columns that
exist in <structname>pg_stats</structname>.
</para>
<table id="planner-pg-stats-table">
<title><structname>pg_stats</structname> Columns</title>
<tgroup cols=3>
@ -435,7 +437,7 @@ regression=#
<row>
<entry><literal>tablename</literal></entry>
<entry><type>name</type></entry>
<entry>Name of table containing column</entry>
<entry>Name of the table containing the column</entry>
</row>
<row>
@ -447,13 +449,13 @@ regression=#
<row>
<entry><literal>null_frac</literal></entry>
<entry><type>real</type></entry>
<entry>Fraction of column's entries that are NULL</entry>
<entry>Fraction of column's entries that are null</entry>
</row>
<row>
<entry><literal>avg_width</literal></entry>
<entry><type>integer</type></entry>
<entry>Average width in bytes of column's entries</entry>
<entry>Average width in bytes of the column's entries</entry>
</row>
<row>
@ -462,7 +464,7 @@ regression=#
<entry>If greater than zero, the estimated number of distinct values
in the column. If less than zero, the negative of the number of
distinct values divided by the number of rows. (The negated form
is used when ANALYZE believes that the number of distinct values
is used when <command>ANALYZE</> believes that the number of distinct values
is likely to increase as the table grows; the positive form is used
when the column seems to have a fixed number of possible values.)
For example, -1 indicates a unique column in which the number of
@ -481,7 +483,7 @@ regression=#
<entry><literal>most_common_freqs</literal></entry>
<entry><type>real[]</type></entry>
<entry>A list of the frequencies of the most common values,
ie, number of occurrences of each divided by total number of rows.
i.e., number of occurrences of each divided by total number of rows.
</entry>
</row>
@ -530,30 +532,32 @@ regression=#
<title>Controlling the Planner with Explicit <literal>JOIN</> Clauses</title>
<para>
Beginning with <productname>PostgreSQL</productname> 7.1 it is possible
to control the query planner to some extent by using explicit <literal>JOIN</>
Beginning with <productname>PostgreSQL</productname> 7.1 it has been possible
to control the query planner to some extent by using the explicit <literal>JOIN</>
syntax. To see why this matters, we first need some background.
</para>
<para>
In a simple join query, such as
<programlisting>
SELECT * FROM a,b,c WHERE a.id = b.id AND b.ref = c.id;
</programlisting>
the planner is free to join the given tables in any order. For example,
it could generate a query plan that joins A to B, using the WHERE clause
a.id = b.id, and then joins C to this joined table, using the other
WHERE clause. Or it could join B to C and then join A to that result.
Or it could join A to C and then join them with B --- but that would
be inefficient, since the full Cartesian product of A and C would have
to be formed, there being no applicable WHERE clause to allow optimization
of the join.
(All joins in the <productname>PostgreSQL</productname> executor happen
between two input tables, so it's necessary to build up the result in one
or another of these fashions.) The important point is that these different
join possibilities give semantically equivalent results but may have hugely
different execution costs. Therefore, the planner will explore all of them
to try to find the most efficient query plan.
<programlisting>
SELECT * FROM a, b, c WHERE a.id = b.id AND b.ref = c.id;
</programlisting>
the planner is free to join the given tables in any order. For
example, it could generate a query plan that joins A to B, using
the <literal>WHERE</> condition <literal>a.id = b.id</>, and then
joins C to this joined table, using the other <literal>WHERE</>
condition. Or it could join B to C and then join A to that result.
Or it could join A to C and then join them with B --- but that
would be inefficient, since the full Cartesian product of A and C
would have to be formed, there being no applicable condition in the
<literal>WHERE</> clause to allow optimization of the join. (All
joins in the <productname>PostgreSQL</productname> executor happen
between two input tables, so it's necessary to build up the result
in one or another of these fashions.) The important point is that
these different join possibilities give semantically equivalent
results but may have hugely different execution costs. Therefore,
the planner will explore all of them to try to find the most
efficient query plan.
</para>
<para>
@ -567,7 +571,7 @@ SELECT * FROM a,b,c WHERE a.id = b.id AND b.ref = c.id;
search to a <firstterm>genetic</firstterm> probabilistic search
through a limited number of possibilities. (The switch-over threshold is
set by the <varname>GEQO_THRESHOLD</varname> run-time
parameter described in the <citetitle>Administrator's Guide</citetitle>.)
parameter described in the &cite-admin;.)
The genetic search takes less time, but it won't
necessarily find the best possible plan.
</para>
@ -575,9 +579,9 @@ SELECT * FROM a,b,c WHERE a.id = b.id AND b.ref = c.id;
<para>
When the query involves outer joins, the planner has much less freedom
than it does for plain (inner) joins. For example, consider
<programlisting>
<programlisting>
SELECT * FROM a LEFT JOIN (b JOIN c ON (b.ref = c.id)) ON (a.id = b.id);
</programlisting>
</programlisting>
Although this query's restrictions are superficially similar to the
previous example, the semantics are different because a row must be
emitted for each row of A that has no matching row in the join of B and C.
@ -587,27 +591,27 @@ SELECT * FROM a LEFT JOIN (b JOIN c ON (b.ref = c.id)) ON (a.id = b.id);
</para>
<para>
In <productname>PostgreSQL</productname> 7.1, the planner treats all
explicit JOIN syntaxes as constraining the join order, even though
The <productname>PostgreSQL</productname> query planner treats all
explicit <literal>JOIN</> syntaxes as constraining the join order, even though
it is not logically necessary to make such a constraint for inner
joins. Therefore, although all of these queries give the same result:
<programlisting>
SELECT * FROM a,b,c WHERE a.id = b.id AND b.ref = c.id;
<programlisting>
SELECT * FROM a, b, c WHERE a.id = b.id AND b.ref = c.id;
SELECT * FROM a CROSS JOIN b CROSS JOIN c WHERE a.id = b.id AND b.ref = c.id;
SELECT * FROM a JOIN (b JOIN c ON (b.ref = c.id)) ON (a.id = b.id);
</programlisting>
the second and third take less time to plan than the first. This effect
</programlisting>
but the second and third take less time to plan than the first. This effect
is not worth worrying about for only three tables, but it can be a
lifesaver with many tables.
</para>
<para>
You do not need to constrain the join order completely in order to
cut search time, because it's OK to use JOIN operators in a plain
FROM list. For example,
<programlisting>
cut search time, because it's OK to use <literal>JOIN</> operators in a plain
<literal>FROM</> list. For example,
<programlisting>
SELECT * FROM a CROSS JOIN b, c, d, e WHERE ...;
</programlisting>
</programlisting>
forces the planner to join A to B before joining them to other tables,
but doesn't constrain its choices otherwise. In this example, the
number of possible join orders is reduced by a factor of 5.
@ -617,22 +621,22 @@ SELECT * FROM a CROSS JOIN b, c, d, e WHERE ...;
If you have a mix of outer and inner joins in a complex query, you
might not want to constrain the planner's search for a good ordering
of inner joins inside an outer join. You can't do that directly in the
JOIN syntax, but you can get around the syntactic limitation by using
<literal>JOIN</> syntax, but you can get around the syntactic limitation by using
subselects. For example,
<programlisting>
<programlisting>
SELECT * FROM d LEFT JOIN
(SELECT * FROM a, b, c WHERE ...) AS ss
ON (...);
</programlisting>
</programlisting>
Here, joining D must be the last step in the query plan, but the
planner is free to consider various join orders for A,B,C.
planner is free to consider various join orders for A, B, C.
</para>
<para>
Constraining the planner's search in this way is a useful technique
both for reducing planning time and for directing the planner to a
good query plan. If the planner chooses a bad join order by default,
you can force it to choose a better order via JOIN syntax --- assuming
you can force it to choose a better order via <literal>JOIN</> syntax --- assuming
that you know of a better order, that is. Experimentation is recommended.
</para>
</sect1>
@ -658,6 +662,10 @@ SELECT * FROM d LEFT JOIN
If you allow each insertion to be committed separately,
<productname>PostgreSQL</productname> is doing a lot of work for each
record added.
An additional benefit of doing all insertions in one transaction
is that if the insertion of one record were to fail then the
insertion of all records inserted up to that point would be rolled
back, so you won't be stuck with partially loaded data.
</para>
</sect2>
@ -696,7 +704,7 @@ SELECT * FROM d LEFT JOIN
</sect2>
<sect2 id="populate-analyze">
<title>ANALYZE Afterwards</title>
<title>Run ANALYZE Afterwards</title>
<para>
It's a good idea to run <command>ANALYZE</command> or <command>VACUUM

20
doc/src/sgml/queries.sgml
View File

@ -1,4 +1,4 @@
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/queries.sgml,v 1.18 2002/10/20 05:05:46 tgl Exp $ -->
<!-- $Header: /cvsroot/pgsql/doc/src/sgml/queries.sgml,v 1.18.2.1 2002/11/10 12:45:42 petere Exp $ -->
<chapter id="queries">
<title>Queries</title>
@ -668,7 +668,7 @@ SELECT <replaceable>select_list</replaceable>
order in which the columns are listed does not matter. The
purpose is to reduce each group of rows sharing common values into
one group row that is representative of all rows in the group.
This is done to eliminate redundancy in the output and/or obtain
This is done to eliminate redundancy in the output and/or compute
aggregates that apply to these groups. For instance:
<screen>
<prompt>=></> <userinput>SELECT * FROM test1;</>
@ -694,7 +694,12 @@ SELECT <replaceable>select_list</replaceable>
In the second query, we could not have written <literal>SELECT *
FROM test1 GROUP BY x</literal>, because there is no single value
for the column <literal>y</> that could be associated with each
group. In general, if a table is grouped, columns that are not
group. The grouped-by columns can be referenced in the select list since
they have a known constant value per group.
</para>
<para>
In general, if a table is grouped, columns that are not
used in the grouping cannot be referenced except in aggregate
expressions. An example with aggregate expressions is:
<screen>
@ -712,11 +717,6 @@ SELECT <replaceable>select_list</replaceable>
linkend="functions-aggregate">.
</para>
<para>
The grouped-by columns can be referenced in the select list since
they have a known constant value per group.
</para>
<tip>
<para>
Grouping without aggregate expressions effectively calculates the
@ -740,7 +740,7 @@ SELECT product_id, p.name, (sum(s.units) * p.price) AS sales
in the <literal>GROUP BY</> clause since they are referenced in
the query select list. (Depending on how exactly the products
table is set up, name and price may be fully dependent on the
product ID, so the additional groups could theoretically be
product ID, so the additional groupings could theoretically be
unnecessary, but this is not implemented yet.) The column
<literal>s.units</> does not have to be in the <literal>GROUP
BY</> list since it is only used in an aggregate expression
@ -828,7 +828,7 @@ SELECT product_id, p.name, (sum(s.units) * (p.price - p.cost)) AS profit
</para>
<sect2 id="queries-select-list-items">
<title>Select List Items</title>
<title>Select-List Items</title>
<para>
The simplest kind of select list is <literal>*</literal> which

117
doc/src/sgml/syntax.sgml
View File

@ -1,5 +1,5 @@
<!--
$Header: /cvsroot/pgsql/doc/src/sgml/syntax.sgml,v 1.72 2002/10/24 17:48:54 petere Exp $
$Header: /cvsroot/pgsql/doc/src/sgml/syntax.sgml,v 1.72.2.1 2002/11/10 12:45:42 petere Exp $
-->
<chapter id="sql-syntax">
@ -121,7 +121,7 @@ INSERT INTO MY_TABLE VALUES (3, 'hi there');
characters of an identifier; longer names can be written in
commands, but they will be truncated. By default,
<symbol>NAMEDATALEN</symbol> is 64 so the maximum identifier length
is 63 (but at the time the system is built,
is 63 (but at the time PostgreSQL is built,
<symbol>NAMEDATALEN</symbol> can be changed in
<filename>src/include/postgres_ext.h</filename>).
</para>
@ -170,8 +170,9 @@ UPDATE "my_table" SET "a" = 5;
<para>
Quoted identifiers can contain any character other than a double
quote itself. This allows constructing table or column names that
would otherwise not be possible, such as ones containing spaces or
quote itself. To include a double quote, write two double quotes.
This allows constructing table or column names that would
otherwise not be possible, such as ones containing spaces or
ampersands. The length limitation still applies.
</para>
@ -272,7 +273,7 @@ SELECT 'foobar';
SELECT 'foo' 'bar';
</programlisting>
is not valid syntax. (This slightly bizarre behavior is specified
by <acronym>SQL9x</acronym>; <productname>PostgreSQL</productname> is
by <acronym>SQL</acronym>; <productname>PostgreSQL</productname> is
following the standard.)
</para>
</sect3>
@ -298,7 +299,7 @@ SELECT 'foo' 'bar';
Alternatively, bit-string constants can be specified in hexadecimal
notation, using a leading <literal>X</literal> (upper or lower case),
e.g., <literal>X'1FF'</literal>. This notation is equivalent to
a bit-string constant with four binary digits for each hex digit.
a bit-string constant with four binary digits for each hexadecimal digit.
</para>
<para>
@ -328,7 +329,7 @@ SELECT 'foo' 'bar';
decimal point, if one is used. At least one digit must follow the
exponent marker (<literal>e</literal>), if one is present.
There may not be any spaces or other characters embedded in the
constant. Notice that any leading plus or minus sign is not actually
constant. Note that any leading plus or minus sign is not actually
considered part of the constant; it is an operator applied to the
constant.
</para>
@ -650,13 +651,16 @@ CAST ( '<replaceable>string</replaceable>' AS <replaceable>type</replaceable> )
</indexterm>
<para>
The precedence and associativity of the operators is hard-wired
into the parser. Most operators have the same precedence and are
left-associative. This may lead to non-intuitive behavior; for
example the Boolean operators <literal>&lt;</> and <literal>&gt;</> have a different
precedence than the Boolean operators <literal>&lt;=</> and <literal>&gt;=</>. Also,
you will sometimes need to add parentheses when using combinations
of binary and unary operators. For instance
<xref linkend="sql-precedence-table"> shows the precedence and
associativity of the operators in PostgreSQL. Most operators have
the same precedence and are left-associative. The precedence and
associativity of the operators is hard-wired into the parser.
This may lead to non-intuitive behavior; for example the Boolean
operators <literal>&lt;</> and <literal>&gt;</> have a different
precedence than the Boolean operators <literal>&lt;=</> and
<literal>&gt;=</>. Also, you will sometimes need to add
parentheses when using combinations of binary and unary operators.
For instance
<programlisting>
SELECT 5 ! - 6;
</programlisting>
@ -673,7 +677,7 @@ SELECT (5 !) - 6;
This is the price one pays for extensibility.
</para>
<table tocentry="1">
<table id="sql-precedence-table">
<title>Operator Precedence (decreasing)</title>
<tgroup cols="3">
@ -825,7 +829,7 @@ SELECT (5 !) - 6;
SELECT 3 OPERATOR(pg_catalog.+) 4;
</programlisting>
the <literal>OPERATOR</> construct is taken to have the default precedence
shown above for <quote>any other</> operator. This is true no matter
shown in <xref linkend="sql-precedence-table"> for <quote>any other</> operator. This is true no matter
which specific operator name appears inside <literal>OPERATOR()</>.
</para>
</sect2>
@ -901,9 +905,8 @@ SELECT 3 OPERATOR(pg_catalog.+) 4;
</listitem>
<listitem>
<synopsis>( <replaceable>expression</replaceable> )</synopsis>
<para>
Parentheses are used to group subexpressions and override precedence.
Another value expression in parentheses, useful to group subexpressions and override precedence.
</para>
</listitem>
</itemizedlist>
@ -928,21 +931,30 @@ SELECT 3 OPERATOR(pg_catalog.+) 4;
<title>Column References</title>
<para>
A column can be referenced in the form:
A column can be referenced in the form
<synopsis>
<replaceable>correlation</replaceable>.<replaceable>columnname</replaceable> `['<replaceable>subscript</replaceable>`]'
<replaceable>correlation</replaceable>.<replaceable>columnname</replaceable>
</synopsis>
or
<synopsis>
<replaceable>correlation</replaceable>.<replaceable>columnname</replaceable>[<replaceable>subscript</replaceable>]
</synopsis>
(Here, the brackets <literal>[ ]</literal> are meant to appear literally.)
</para>
<para>
<replaceable>correlation</replaceable> is the name of a
table (possibly qualified), or an alias for a table defined by means of a
FROM clause, or
<literal>FROM</literal> clause, or
the key words <literal>NEW</literal> or <literal>OLD</literal>.
(NEW and OLD can only appear in rules,
(<literal>NEW</literal> and <literal>OLD</literal> can only appear in rewrite rules,
while other correlation names can be used in any SQL statement.)
The correlation name and separating dot may be omitted if the column name
is unique
across all the tables being used in the current query. If
<replaceable>column</replaceable> is of an array type, then the
is unique across all the tables being used in the current query. (See also <xref linkend="queries">.)
</para>
<para>
If <replaceable>column</replaceable> is of an array type, then the
optional <replaceable>subscript</replaceable> selects a specific
element or elements in the array. If no subscript is provided, then the
whole array is selected. (See <xref linkend="arrays"> for more about
@ -968,9 +980,9 @@ $<replaceable>number</replaceable>
<function>dept</function>, as
<programlisting>
CREATE FUNCTION dept (text) RETURNS dept
AS 'SELECT * FROM dept WHERE name = $1'
LANGUAGE SQL;
CREATE FUNCTION dept(text) RETURNS dept
AS 'SELECT * FROM dept WHERE name = $1'
LANGUAGE SQL;
</programlisting>
Here the <literal>$1</literal> will be replaced by the first
@ -993,7 +1005,7 @@ CREATE FUNCTION dept (text) RETURNS dept
keywords <token>AND</token>, <token>OR</token>, and
<token>NOT</token>, or is a qualified operator name
<synopsis>
<literal>OPERATOR(</><replaceable>schema</><literal>.</><replaceable>operatorname</><literal>)</>
<literal>OPERATOR(</><replaceable>schema</><literal>.</><replaceable>operatorname</><literal>)</>
</synopsis>
Which particular operators exist and whether
they are unary or binary depends on what operators have been
@ -1042,12 +1054,12 @@ sqrt(2)
output value, such as the sum or average of the inputs. The
syntax of an aggregate expression is one of the following:
<simplelist>
<member><replaceable>aggregate_name</replaceable> (<replaceable>expression</replaceable>)</member>
<member><replaceable>aggregate_name</replaceable> (ALL <replaceable>expression</replaceable>)</member>
<member><replaceable>aggregate_name</replaceable> (DISTINCT <replaceable>expression</replaceable>)</member>
<member><replaceable>aggregate_name</replaceable> ( * )</member>
</simplelist>
<synopsis>
<replaceable>aggregate_name</replaceable> (<replaceable>expression</replaceable>)
<replaceable>aggregate_name</replaceable> (ALL <replaceable>expression</replaceable>)
<replaceable>aggregate_name</replaceable> (DISTINCT <replaceable>expression</replaceable>)
<replaceable>aggregate_name</replaceable> ( * )
</synopsis>
where <replaceable>aggregate_name</replaceable> is a previously
defined aggregate (possibly a qualified name), and
@ -1101,7 +1113,7 @@ sqrt(2)
CAST ( <replaceable>expression</replaceable> AS <replaceable>type</replaceable> )
<replaceable>expression</replaceable>::<replaceable>type</replaceable>
</synopsis>
The <literal>CAST</> syntax conforms to SQL92; the syntax with
The <literal>CAST</> syntax conforms to SQL; the syntax with
<literal>::</literal> is historical <productname>PostgreSQL</productname>
usage.
</para>
@ -1123,8 +1135,8 @@ CAST ( <replaceable>expression</replaceable> AS <replaceable>type</replaceable>
to the type that a value expression must produce (for example, when it is
assigned to a table column); the system will automatically apply a
type cast in such cases. However, automatic casting is only done for
cast functions that are marked <quote>OK to apply implicitly</>
in the system catalogs. Other cast functions must be invoked with
casts that are marked <quote>OK to apply implicitly</>
in the system catalogs. Other casts must be invoked with
explicit casting syntax. This restriction is intended to prevent
surprising conversions from being applied silently.
</para>
@ -1143,6 +1155,13 @@ CAST ( <replaceable>expression</replaceable> AS <replaceable>type</replaceable>
double-quoted, because of syntactic conflicts. Therefore, the use of
the function-like cast syntax leads to inconsistencies and should
probably be avoided in new applications.
(The function-like syntax is in fact just a function call. When
one of the two standard cast syntaxes is used to do a run-time
conversion, it will internally invoke a registered function to
perform the conversion. By convention, these conversion functions
have the same name as their output type, but this is not something
that a portable application should rely on.)
</para>
</sect2>
@ -1151,8 +1170,9 @@ CAST ( <replaceable>expression</replaceable> AS <replaceable>type</replaceable>
<para>
A scalar subquery is an ordinary
<command>SELECT</command> in parentheses that returns exactly one
row with one column. The <command>SELECT</command> query is executed
<command>SELECT</command> query in parentheses that returns exactly one
row with one column. (See <xref linkend="queries"> for information about writing queries.)
The <command>SELECT</command> query is executed
and the single returned value is used in the surrounding value expression.
It is an error to use a query that
returns more than one row or more than one column as a scalar subquery.
@ -1168,7 +1188,7 @@ CAST ( <replaceable>expression</replaceable> AS <replaceable>type</replaceable>
state:
<programlisting>
SELECT name, (SELECT max(pop) FROM cities WHERE cities.state = states.name)
FROM states;
FROM states;
</programlisting>
</para>
</sect2>
@ -1202,25 +1222,26 @@ SELECT somefunc() OR true;
<para>
As a consequence, it is unwise to use functions with side effects
as part of complex expressions. It is particularly dangerous to
rely on side effects or evaluation order in WHERE and HAVING clauses,
rely on side effects or evaluation order in <literal>WHERE</> and <literal>HAVING</> clauses,
since those clauses are extensively reprocessed as part of
developing an execution plan. Boolean
expressions (AND/OR/NOT combinations) in those clauses may be reorganized
expressions (<literal>AND</>/<literal>OR</>/<literal>NOT</> combinations) in those clauses may be reorganized
in any manner allowed by the laws of Boolean algebra.
</para>
<para>
When it is essential to force evaluation order, a CASE construct may
be used. For example, this is an untrustworthy way of trying to
avoid division by zero in a WHERE clause:
When it is essential to force evaluation order, a <literal>CASE</>
construct (see <xref linkend="functions-conditional">) may be
used. For example, this is an untrustworthy way of trying to
avoid division by zero in a <literal>WHERE</> clause:
<programlisting>
SELECT ... WHERE x &lt;&gt; 0 AND y/x &gt; 1.5;
</programlisting>
but this is safe:
But this is safe:
<programlisting>
SELECT ... WHERE CASE WHEN x &lt;&gt; 0 THEN y/x &gt; 1.5 ELSE false END;
</programlisting>
A CASE construct used in this fashion will defeat optimization attempts,
A <literal>CASE</> construct used in this fashion will defeat optimization attempts,
so it should only be done when necessary.
</para>
</sect2>

24
doc/src/sgml/typeconv.sgml
View File

@ -1,9 +1,6 @@
<chapter Id="typeconv">
<title>Type Conversion</title>
<sect1 id="typeconv-intro">
<title>Introduction</title>
<para>
<acronym>SQL</acronym> queries can, intentionally or not, require
mixing of different data types in the same expression.
@ -29,10 +26,9 @@ operators.
</para>
<para>
The <citetitle>Programmer's Guide</citetitle> has more details on the exact algorithms used for
The &cite-programmer; has more details on the exact algorithms used for
implicit type conversion and coercion.
</para>
</sect1>
<sect1 id="typeconv-overview">
<title>Overview</title>
@ -41,7 +37,7 @@ implicit type conversion and coercion.
<acronym>SQL</acronym> is a strongly typed language. That is, every data item
has an associated data type which determines its behavior and allowed usage.
<productname>PostgreSQL</productname> has an extensible type system that is
much more general and flexible than other <acronym>RDBMS</acronym> implementations.
much more general and flexible than other <acronym>SQL</acronym> implementations.
Hence, most type conversion behavior in <productname>PostgreSQL</productname>
should be governed by general rules rather than by <foreignphrase>ad hoc</> heuristics, to allow
mixed-type expressions to be meaningful even with user-defined types.
@ -142,13 +138,13 @@ conventions for the <acronym>SQL</acronym> standard native types such as
</para>
<para>
The <productname>PostgreSQL</productname> parser uses the convention that all
type conversion functions take a single argument of the source type and are
named with the same name as the target type. Any function meeting these
criteria is considered to be a valid conversion function, and may be used
by the parser as such. This simple assumption gives the parser the power
to explore type conversion possibilities without hardcoding, allowing
extended user-defined types to use these same features transparently.
The system catalogs store information about which conversions, called
<firstterm>casts</firstterm>, between data types are valid, and how to
perform those conversions. Additional casts can be added by the user
with the <command>CREATE CAST</command> command. (This is usually
done in conjunction with defining new data types. The set of casts
between the built-in types has been carefully crafted and should not
be altered.)
</para>
<para>
@ -169,7 +165,7 @@ types.
<para>
All type conversion rules are designed with several principles in mind:
<itemizedlist mark="bullet" spacing="compact">
<itemizedlist>
<listitem>
<para>
Implicit conversions should never have surprising or unpredictable outcomes.

4
doc/src/sgml/user.sgml
View File

@ -1,5 +1,5 @@
<!--
$Header: /cvsroot/pgsql/doc/src/sgml/Attic/user.sgml,v 1.33 2002/10/24 17:48:54 petere Exp $
$Header: /cvsroot/pgsql/doc/src/sgml/Attic/user.sgml,v 1.33.2.1 2002/11/10 12:45:43 petere Exp $
-->
<book id="user">
@ -29,7 +29,7 @@ $Header: /cvsroot/pgsql/doc/src/sgml/Attic/user.sgml,v 1.33 2002/10/24 17:48:54
database, and how to query it. The middle part lists the
available data types and functions for use in SQL data commands.
The rest of the book treats several aspects that are important for
tuning a database for optimial performance.
tuning a database for optimal performance.
</para>
<para>