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postgres/doc/src/sgml/rules.sgml
Peter Eisentraut c326d8f4f2 Add/edit index entries.
2003-08-31 17:32:24 +00:00

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<!-- $Header: /cvsroot/pgsql/doc/src/sgml/rules.sgml,v 1.29 2003/08/31 17:32:19 petere Exp $ -->
<Chapter Id="rules">
<Title>The Rule System</Title>
<indexterm zone="rules">
<primary>rule</primary>
</indexterm>
<Para>
This chapter discusses the rule system in PostgreSQL.
Production rule systems are conceptually simple, but
there are many subtle points involved in actually using
them.
</Para>
<Para>
Some other database systems define active database rules, which
are usually stored procedures and triggers. In PostgreSQL, these
can be implemented using functions and triggers as well.
</Para>
<Para>
The rule system (more precisely speaking, the query rewrite rule
system) is totally different from stored procedures and triggers.
It modifies queries to take rules into consideration, and then
passes the modified query to the query planner for planning and
execution. It is very powerful, and can be used for many things
such as query language procedures, views, and versions. The
theoretical foundations and the power of this rule system are
also discussed in <xref linkend="STON90b"> and <xref
linkend="ONG90">.
</para>
<Sect1 id="querytree">
<Title>The Query Tree</Title>
<indexterm zone="querytree">
<primary>query tree</primary>
</indexterm>
<Para>
To understand how the rule system works it is necessary to know
when it is invoked and what its input and results are.
</Para>
<Para>
The rule system is located between the parser and the planner.
It takes the output of the parser, one query tree, and the user-defined
rewrite rules, which are also
query trees with some extra information, and creates zero or more
query trees as result. So its input and output are always things
the parser itself could have produced and thus, anything it sees
is basically representable as an <Acronym>SQL</Acronym> statement.
</Para>
<Para>
Now what is a query tree? It is an internal representation of an
<Acronym>SQL</Acronym> statement where the single parts that it is
built from are stored separately. These query trees can be shown
in the server log if you set the configuration parameters
<varname>debug_print_parse</varname>,
<varname>debug_print_rewritten</varname>, or
<varname>debug_print_plan</varname>. The rule actions are also
stored as query trees, in the system catalog
<structname>pg_rewrite</structname>. They are not formatted like
the log output, but they contain exactly the same information.
</Para>
<Para>
Reading a raw query tree requires some experience. But since
<Acronym>SQL</Acronym> representations of query trees are
sufficient to understand the rule system, this chapter will not
teach how to read them.
</Para>
<Para>
When reading the <Acronym>SQL</Acronym> representations of the
query trees in this chapter it is necessary to be able to identify
the parts the statement is broken into when it is in the query tree
structure. The parts of a query tree are
<VariableList>
<VarListEntry>
<Term>
the command type
</Term>
<ListItem>
<Para>
This is a simple value telling which command
(<command>SELECT</command>, <command>INSERT</command>,
<command>UPDATE</command>, <command>DELETE</command>) produced
the query tree.
</Para>
</ListItem>
</VarListEntry>
<VarListEntry>
<Term>
the range table
</Term>
<indexterm><primary>range table</></>
<ListItem>
<Para>
The range table is a list of relations that are used in the query.
In a <command>SELECT</command> statement these are the relations given after
the <literal>FROM</literal> key word.
</Para>
<Para>
Every range table entry identifies a table or view and tells
by which name it is called in the other parts of the query.
In the query tree, the range table entries are referenced by
number rather than by name, so here it doesn't matter if there
are duplicate names as it would in an <Acronym>SQL</Acronym>
statement. This can happen after the range tables of rules
have been merged in. The examples in this chapter will not have
this situation.
</Para>
</ListItem>
</VarListEntry>
<VarListEntry>
<Term>
the result relation
</Term>
<ListItem>
<Para>
This is an index into the range table that identifies the
relation where the results of the query go.
</Para>
<Para>
<command>SELECT</command> queries normally don't have a result
relation. The special case of a <command>SELECT INTO</command> is
mostly identical to a <command>CREATE TABLE</command> followed by a
<literal>INSERT ... SELECT</literal> and is not discussed
separately here.
</Para>
<Para>
For <command>INSERT</command>, <command>UPDATE</command>, and
<command>DELETE</command> commands, the result relation is the table
(or view!) where the changes take effect.
</Para>
</ListItem>
</VarListEntry>
<VarListEntry>
<Term>
the target list
</Term>
<indexterm><primary>target list</></>
<ListItem>
<Para>
The target list is a list of expressions that define the
result of the query. In the case of a
<command>SELECT</command>, these expressions are the ones that
build the final output of the query. They correspond to the
expressions between the key words <command>SELECT</command>
and <command>FROM</command>. (<literal>*</literal> is just an
abbreviation for all the column names of a relation. It is
expanded by the parser into the individual columns, so the
rule system never sees it.)
</Para>
<Para>
<command>DELETE</command> commands don't need a target list
because they don't produce any result. In fact, the planner will
add a special <acronym>CTID</> entry to the empty target list, but
this is after the rule system and will be discussed later; for the
rule system, the target list is empty.
</Para>
<Para>
For <command>INSERT</command> commands, the target list describes
the new rows that should go into the result relation. It consists of the
expressions in the <literal>VALUES</> clause or the ones from the
<command>SELECT</command> clause in <literal>INSERT
... SELECT</literal>. The first step of the rewrite process adds
target list entries for any columns that were not assigned to by
the original command but have defaults. Any remaining columns (with
neither a given value nor a default) will be filled in by the
planner with a constant null expression.
</Para>
<Para>
For <command>UPDATE</command> commands, the target list
describes the new rows that should replace the old ones. In the
rule system, it contains just the expressions from the <literal>SET
column = expression</literal> part of the command. The planner will handle
missing columns by inserting expressions that copy the values from
the old row into the new one. And it will add the special
<acronym>CTID</> entry just as for <command>DELETE</command>, too.
</Para>
<Para>
Every entry in the target list contains an expression that can
be a constant value, a variable pointing to a column of one
of the relations in the range table, a parameter, or an expression
tree made of function calls, constants, variables, operators, etc.
</Para>
</ListItem>
</VarListEntry>
<VarListEntry>
<Term>
the qualification
</Term>
<ListItem>
<Para>
The query's qualification is an expression much like one of
those contained in the target list entries. The result value of
this expression is a Boolean that tells whether the operation
(<command>INSERT</command>, <command>UPDATE</command>,
<command>DELETE</command>, or <command>SELECT</command>) for the
final result row should be executed or not. It corresponds to the <literal>WHERE</> clause
of an <Acronym>SQL</Acronym> statement.
</Para>
</ListItem>
</VarListEntry>
<VarListEntry>
<Term>
the join tree
</Term>
<ListItem>
<Para>
The query's join tree shows the structure of the <literal>FROM</> clause.
For a simple query like <literal>SELECT ... FROM a, b, c</literal>, the join tree is just
a list of the <literal>FROM</> items, because we are allowed to join them in
any order. But when <literal>JOIN</> expressions, particularly outer joins,
are used, we have to join in the order shown by the joins.
In that case, the join tree shows the structure of the <literal>JOIN</> expressions. The
restrictions associated with particular <literal>JOIN</> clauses (from <literal>ON</> or
<literal>USING</> expressions) are stored as qualification expressions attached
to those join-tree nodes. It turns out to be convenient to store
the top-level <literal>WHERE</> expression as a qualification attached to the
top-level join-tree item, too. So really the join tree represents
both the <literal>FROM</> and <literal>WHERE</> clauses of a <command>SELECT</command>.
</Para>
</ListItem>
</VarListEntry>
<VarListEntry>
<Term>
the others
</Term>
<ListItem>
<Para>
The other parts of the query tree like the <literal>ORDER BY</>
clause aren't of interest here. The rule system
substitutes some entries there while applying rules, but that
doesn't have much to do with the fundamentals of the rule
system.
</Para>
</ListItem>
</VarListEntry>
</VariableList>
</para>
</Sect1>
<Sect1 id="rules-views">
<Title>Views and the Rule System</Title>
<indexterm zone="rules-views">
<primary>rule</primary>
<secondary>and views</secondary>
</indexterm>
<indexterm zone="rules-views">
<primary>view</>
<secondary>implementation through rules</>
</indexterm>
<Para>
Views in <ProductName>PostgreSQL</ProductName> are implemented
using the rule system. In fact, there is essentially no difference
between
<ProgramListing>
CREATE VIEW myview AS SELECT * FROM mytab;
</ProgramListing>
compared against the two commands
<ProgramListing>
CREATE TABLE myview (<Replaceable>same column list as mytab</Replaceable>);
CREATE RULE "_RETURN" AS ON SELECT TO myview DO INSTEAD
SELECT * FROM mytab;
</ProgramListing>
because this is exactly what the <command>CREATE VIEW</command>
command does internally. This has some side effects. One of them
is that the information about a view in the
<ProductName>PostgreSQL</ProductName> system catalogs is exactly
the same as it is for a table. So for the parser, there is
absolutely no difference between a table and a view. They are the
same thing: relations.
</Para>
<Sect2 id="rules-select">
<Title>How <command>SELECT</command> Rules Work</Title>
<indexterm zone="rules-select">
<primary>rule</primary>
<secondary sortas="SELECT">for SELECT</secondary>
</indexterm>
<Para>
Rules <literal>ON SELECT</> are applied to all queries as the last step, even
if the command given is an <command>INSERT</command>,
<command>UPDATE</command> or <command>DELETE</command>. And they
have different semantics from rules on the other command types in that they modify the
query tree in place instead of creating a new one. So
<command>SELECT</command> rules are described first.
</Para>
<Para>
Currently, there can be only one action in an <literal>ON SELECT</> rule, and it must
be an unconditional <command>SELECT</> action that is <literal>INSTEAD</>. This restriction was
required to make rules safe enough to open them for ordinary users, and
it restricts <literal>ON SELECT</> rules to real view rules.
</Para>
<Para>
The examples for this chapter are two join views that do some
calculations and some more views using them in turn. One of the
two first views is customized later by adding rules for
<command>INSERT</command>, <command>UPDATE</command>, and
<command>DELETE</command> operations so that the final result will
be a view that behaves like a real table with some magic
functionality. This is not such a simple example to start from and
this makes things harder to get into. But it's better to have one
example that covers all the points discussed step by step rather
than having many different ones that might mix up in mind.
</Para>
<Para>
For the example, we need a little <literal>min</literal> function that
returns the lower of 2 integer values. We create that as
<ProgramListing>
CREATE FUNCTION min(integer, integer) RETURNS integer AS '
SELECT CASE WHEN $1 < $2 THEN $1 ELSE $2 END
' LANGUAGE SQL STRICT;
</ProgramListing>
</Para>
<Para>
The real tables we need in the first two rule system descriptions
are these:
<ProgramListing>
CREATE TABLE shoe_data (
shoename text, -- primary key
sh_avail integer, -- available number of pairs
slcolor text, -- preferred shoelace color
slminlen real, -- minimum shoelace length
slmaxlen real, -- maximum shoelace length
slunit text -- length unit
);
CREATE TABLE shoelace_data (
sl_name text, -- primary key
sl_avail integer, -- available number of pairs
sl_color text, -- shoelace color
sl_len real, -- shoelace length
sl_unit text -- length unit
);
CREATE TABLE unit (
un_name text, -- primary key
un_fact real -- factor to transform to cm
);
</ProgramListing>
As you can see, they represent shoe-store data.
</Para>
<Para>
The views are created as
<ProgramListing>
CREATE VIEW shoe AS
SELECT sh.shoename,
sh.sh_avail,
sh.slcolor,
sh.slminlen,
sh.slminlen * un.un_fact AS slminlen_cm,
sh.slmaxlen,
sh.slmaxlen * un.un_fact AS slmaxlen_cm,
sh.slunit
FROM shoe_data sh, unit un
WHERE sh.slunit = un.un_name;
CREATE VIEW shoelace AS
SELECT s.sl_name,
s.sl_avail,
s.sl_color,
s.sl_len,
s.sl_unit,
s.sl_len * u.un_fact AS sl_len_cm
FROM shoelace_data s, unit u
WHERE s.sl_unit = u.un_name;
CREATE VIEW shoe_ready AS
SELECT rsh.shoename,
rsh.sh_avail,
rsl.sl_name,
rsl.sl_avail,
min(rsh.sh_avail, rsl.sl_avail) AS total_avail
FROM shoe rsh, shoelace rsl
WHERE rsl.sl_color = rsh.slcolor
AND rsl.sl_len_cm >= rsh.slminlen_cm
AND rsl.sl_len_cm <= rsh.slmaxlen_cm;
</ProgramListing>
The <command>CREATE VIEW</command> command for the
<literal>shoelace</literal> view (which is the simplest one we
have) will create a relation <literal>shoelace</> and an entry in
<structname>pg_rewrite</structname> that tells that there is a
rewrite rule that must be applied whenever the relation <literal>shoelace</>
is referenced in a query's range table. The rule has no rule
qualification (discussed later, with the non-<command>SELECT</> rules, since
<command>SELECT</> rules currently cannot have them) and it is <literal>INSTEAD</>. Note
that rule qualifications are not the same as query qualifications.
The action of our rule has a query qualification.
The action of the rule is one query tree that is a copy of the
<command>SELECT</command> statement in the view creation command.
</Para>
<Note>
<Para>
The two extra range
table entries for <literal>NEW</> and <literal>OLD</> (named <literal>*NEW*</> and <literal>*OLD*</> for
historical reasons in the printed query tree) you can see in
the <structname>pg_rewrite</structname> entry aren't of interest
for <command>SELECT</command> rules.
</Para>
</Note>
<Para>
Now we populate <literal>unit</literal>, <literal>shoe_data</literal>
and <literal>shoelace_data</literal> and run a simple query on a view:
<ProgramListing>
INSERT INTO unit VALUES ('cm', 1.0);
INSERT INTO unit VALUES ('m', 100.0);
INSERT INTO unit VALUES ('inch', 2.54);
INSERT INTO shoe_data VALUES ('sh1', 2, 'black', 70.0, 90.0, 'cm');
INSERT INTO shoe_data VALUES ('sh2', 0, 'black', 30.0, 40.0, 'inch');
INSERT INTO shoe_data VALUES ('sh3', 4, 'brown', 50.0, 65.0, 'cm');
INSERT INTO shoe_data VALUES ('sh4', 3, 'brown', 40.0, 50.0, 'inch');
INSERT INTO shoelace_data VALUES ('sl1', 5, 'black', 80.0, 'cm');
INSERT INTO shoelace_data VALUES ('sl2', 6, 'black', 100.0, 'cm');
INSERT INTO shoelace_data VALUES ('sl3', 0, 'black', 35.0 , 'inch');
INSERT INTO shoelace_data VALUES ('sl4', 8, 'black', 40.0 , 'inch');
INSERT INTO shoelace_data VALUES ('sl5', 4, 'brown', 1.0 , 'm');
INSERT INTO shoelace_data VALUES ('sl6', 0, 'brown', 0.9 , 'm');
INSERT INTO shoelace_data VALUES ('sl7', 7, 'brown', 60 , 'cm');
INSERT INTO shoelace_data VALUES ('sl8', 1, 'brown', 40 , 'inch');
SELECT * FROM shoelace;
sl_name | sl_avail | sl_color | sl_len | sl_unit | sl_len_cm
-----------+----------+----------+--------+---------+-----------
sl1 | 5 | black | 80 | cm | 80
sl2 | 6 | black | 100 | cm | 100
sl7 | 7 | brown | 60 | cm | 60
sl3 | 0 | black | 35 | inch | 88.9
sl4 | 8 | black | 40 | inch | 101.6
sl8 | 1 | brown | 40 | inch | 101.6
sl5 | 4 | brown | 1 | m | 100
sl6 | 0 | brown | 0.9 | m | 90
(8 rows)
</ProgramListing>
</para>
<para>
This is the simplest <command>SELECT</command> you can do on our
views, so we take this opportunity to explain the basics of view
rules. The <literal>SELECT * FROM shoelace</literal> was
interpreted by the parser and produced the query tree
<ProgramListing>
SELECT shoelace.sl_name, shoelace.sl_avail,
shoelace.sl_color, shoelace.sl_len,
shoelace.sl_unit, shoelace.sl_len_cm
FROM shoelace shoelace;
</ProgramListing>
and this is given to the rule system. The rule system walks through the
range table and checks if there are rules
for any relation. When processing the range table entry for
<literal>shoelace</literal> (the only one up to now) it finds the
<literal>_RETURN</literal> rule with the query tree
<ProgramListing>
SELECT s.sl_name, s.sl_avail,
s.sl_color, s.sl_len, s.sl_unit,
s.sl_len * u.un_fact AS sl_len_cm
FROM shoelace *OLD*, shoelace *NEW*,
shoelace_data s, unit u
WHERE s.sl_unit = u.un_name;
</ProgramListing>
</Para>
<Para>
To expand the view, the rewriter simply creates a subquery range-table
entry containing the rule's action query tree, and substitutes this
range table entry for the original one that referenced the view. The
resulting rewritten query tree is almost the same as if you had typed
<ProgramListing>
SELECT shoelace.sl_name, shoelace.sl_avail,
shoelace.sl_color, shoelace.sl_len,
shoelace.sl_unit, shoelace.sl_len_cm
FROM (SELECT s.sl_name,
s.sl_avail,
s.sl_color,
s.sl_len,
s.sl_unit,
s.sl_len * u.un_fact AS sl_len_cm
FROM shoelace_data s, unit u
WHERE s.sl_unit = u.un_name) shoelace;
</ProgramListing>
There is one difference however: the subquery's range table has two
extra entries <literal>shoelace *OLD*</> and <literal>shoelace *NEW*</>. These entries don't
participate directly in the query, since they aren't referenced by
the subquery's join tree or target list. The rewriter uses them
to store the access privilege check information that was originally present
in the range-table entry that referenced the view. In this way, the
executor will still check that the user has proper privileges to access
the view, even though there's no direct use of the view in the rewritten
query.
</Para>
<Para>
That was the first rule applied. The rule system will continue checking
the remaining range-table entries in the top query (in this example there
are no more), and it will recursively check the range-table entries in
the added subquery to see if any of them reference views. (But it
won't expand <literal>*OLD*</> or <literal>*NEW*</> --- otherwise we'd have infinite recursion!)
In this example, there are no rewrite rules for <literal>shoelace_data</> or <literal>unit</>,
so rewriting is complete and the above is the final result given to
the planner.
</Para>
<Para>
No we want to write a query that finds out for which shoes currently in the store
we have the matching shoelaces (color and length) and where the
total number of exactly matching pairs is greater or equal to two.
<ProgramListing>
SELECT * FROM shoe_ready WHERE total_avail >= 2;
shoename | sh_avail | sl_name | sl_avail | total_avail
----------+----------+---------+----------+-------------
sh1 | 2 | sl1 | 5 | 2
sh3 | 4 | sl7 | 7 | 4
(2 rows)
</ProgramListing>
</Para>
<Para>
The output of the parser this time is the query tree
<ProgramListing>
SELECT shoe_ready.shoename, shoe_ready.sh_avail,
shoe_ready.sl_name, shoe_ready.sl_avail,
shoe_ready.total_avail
FROM shoe_ready shoe_ready
WHERE shoe_ready.total_avail >= 2;
</ProgramListing>
The first rule applied will be the one for the
<literal>shoe_ready</literal> view and it results in the
query tree
<ProgramListing>
SELECT shoe_ready.shoename, shoe_ready.sh_avail,
shoe_ready.sl_name, shoe_ready.sl_avail,
shoe_ready.total_avail
FROM (SELECT rsh.shoename,
rsh.sh_avail,
rsl.sl_name,
rsl.sl_avail,
min(rsh.sh_avail, rsl.sl_avail) AS total_avail
FROM shoe rsh, shoelace rsl
WHERE rsl.sl_color = rsh.slcolor
AND rsl.sl_len_cm >= rsh.slminlen_cm
AND rsl.sl_len_cm <= rsh.slmaxlen_cm) shoe_ready
WHERE shoe_ready.total_avail >= 2;
</ProgramListing>
Similarly, the rules for <literal>shoe</literal> and
<literal>shoelace</literal> are substituted into the range table of
the subquery, leading to a three-level final query tree:
<ProgramListing>
SELECT shoe_ready.shoename, shoe_ready.sh_avail,
shoe_ready.sl_name, shoe_ready.sl_avail,
shoe_ready.total_avail
FROM (SELECT rsh.shoename,
rsh.sh_avail,
rsl.sl_name,
rsl.sl_avail,
min(rsh.sh_avail, rsl.sl_avail) AS total_avail
FROM (SELECT sh.shoename,
sh.sh_avail,
sh.slcolor,
sh.slminlen,
sh.slminlen * un.un_fact AS slminlen_cm,
sh.slmaxlen,
sh.slmaxlen * un.un_fact AS slmaxlen_cm,
sh.slunit
FROM shoe_data sh, unit un
WHERE sh.slunit = un.un_name) rsh,
(SELECT s.sl_name,
s.sl_avail,
s.sl_color,
s.sl_len,
s.sl_unit,
s.sl_len * u.un_fact AS sl_len_cm
FROM shoelace_data s, unit u
WHERE s.sl_unit = u.un_name) rsl
WHERE rsl.sl_color = rsh.slcolor
AND rsl.sl_len_cm >= rsh.slminlen_cm
AND rsl.sl_len_cm <= rsh.slmaxlen_cm) shoe_ready
WHERE shoe_ready.total_avail > 2;
</ProgramListing>
</para>
<para>
It turns out that the planner will collapse this tree into a
two-level query tree: the bottommost <command>SELECT</command>
commands will be <quote>pulled up</quote> into the middle
<command>SELECT</command> since there's no need to process them
separately. But the middle <command>SELECT</command> will remain
separate from the top, because it contains aggregate functions.
If we pulled those up it would change the behavior of the topmost
<command>SELECT</command>, which we don't want. However,
collapsing the query tree is an optimization that the rewrite
system doesn't have to concern itself with.
</para>
<Note>
<Para>
There is currently no recursion stopping mechanism for view rules
in the rule system (only for the other kinds of rules). This
doesn't hurt much, because the only way to push this into an
endless loop (bloating up the server process until it reaches the memory
limit) is to create tables and then setup the view rules by hand
with <command>CREATE RULE</command> in such a way, that one
selects from the other that selects from the one. This could
never happen if <command>CREATE VIEW</command> is used because for
the first <command>CREATE VIEW</command>, the second relation does
not exist and thus the first view cannot select from the second.
</Para>
</Note>
</Sect2>
<Sect2>
<Title>View Rules in Non-<command>SELECT</command> Statements</Title>
<Para>
Two details of the query tree aren't touched in the description of
view rules above. These are the command type and the result relation.
In fact, view rules don't need this information.
</Para>
<Para>
There are only a few differences between a query tree for a
<command>SELECT</command> and one for any other
command. Obviously, they have a different command type and for a
command other than a <command>SELECT</command>, the result
relation points to the range-table entry where the result should
go. Everything else is absolutely the same. So having two tables
<literal>t1</> and <literal>t2</> with columns <literal>a</> and
<literal>b</>, the query trees for the two statements
<ProgramListing>
SELECT t2.b FROM t1, t2 WHERE t1.a = t2.a;
UPDATE t1 SET b = t2.b WHERE t1.a = t2.a;
</ProgramListing>
are nearly identical. In particular:
<ItemizedList>
<ListItem>
<Para>
The range tables contain entries for the tables <literal>t1</> and <literal>t2</>.
</Para>
</ListItem>
<ListItem>
<Para>
The target lists contain one variable that points to column
<literal>b</> of the range table entry for table <literal>t2</>.
</Para>
</ListItem>
<ListItem>
<Para>
The qualification expressions compare the columns <literal>a</> of both
range-table entries for equality.
</Para>
</ListItem>
<ListItem>
<Para>
The join trees show a simple join between <literal>t1</> and <literal>t2</>.
</Para>
</ListItem>
</ItemizedList>
</para>
<para>
The consequence is, that both query trees result in similar
execution plans: They are both joins over the two tables. For the
<command>UPDATE</command> the missing columns from <literal>t1</> are added to
the target list by the planner and the final query tree will read
as
<ProgramListing>
UPDATE t1 SET a = t1.a, b = t2.b WHERE t1.a = t2.a;
</ProgramListing>
and thus the executor run over the join will produce exactly the
same result set as a
<ProgramListing>
SELECT t1.a, t2.b FROM t1, t2 WHERE t1.a = t2.a;
</ProgramListing>
will do. But there is a little problem in
<command>UPDATE</command>: The executor does not care what the
results from the join it is doing are meant for. It just produces
a result set of rows. The difference that one is a
<command>SELECT</command> command and the other is an
<command>UPDATE</command> is handled in the caller of the
executor. The caller still knows (looking at the query tree) that
this is an <command>UPDATE</command>, and it knows that this
result should go into table <literal>t1</>. But which of the rows that are
there has to be replaced by the new row?
</Para>
<Para>
To resolve this problem, another entry is added to the target list
in <command>UPDATE</command> (and also in
<command>DELETE</command>) statements: the current tuple ID
(<acronym>CTID</>).<indexterm><primary>CTID</></> This is a system column containing the
file block number and position in the block for the row. Knowing
the table, the <acronym>CTID</> can be used to retrieve the
original row of <literal>t1</> to be updated. After adding the <acronym>CTID</>
to the target list, the query actually looks like
<ProgramListing>
SELECT t1.a, t2.b, t1.ctid FROM t1, t2 WHERE t1.a = t2.a;
</ProgramListing>
Now another detail of <ProductName>PostgreSQL</ProductName> enters
the stage. Old table rows aren't overwritten, and this
is why <command>ROLLBACK</command> is fast. In an <command>UPDATE</command>,
the new result row is inserted into the table (after stripping the
<acronym>CTID</>) and in the tuple header of the old row, which the
<acronym>CTID</> pointed to, the <literal>cmax</> and
<literal>xmax</> entries are set to the current command counter
and current transaction ID. Thus the old row is hidden, and after
the transaction committed the vacuum cleaner can really move it
out.
</Para>
<Para>
Knowing all that, we can simply apply view rules in absolutely
the same way to any command. There is no difference.
</Para>
</Sect2>
<Sect2>
<Title>The Power of Views in <ProductName>PostgreSQL</ProductName></Title>
<Para>
The above demonstrates how the rule system incorporates view
definitions into the original query tree. In the second example, a
simple <command>SELECT</command> from one view created a final
query tree that is a join of 4 tables (<literal>unit</> was used twice with
different names).
</Para>
<Para>
The benefit of implementing views with the rule system is,
that the planner has all
the information about which tables have to be scanned plus the
relationships between these tables plus the restrictive
qualifications from the views plus the qualifications from
the original query
in one single query tree. And this is still the situation
when the original query is already a join over views.
The planner has to decide which is
the best path to execute the query, and the more information
the planner has, the better this decision can be. And
the rule system as implemented in <ProductName>PostgreSQL</ProductName>
ensures, that this is all information available about the query
up to that point.
</Para>
</Sect2>
<Sect2 id="rules-views-update">
<Title>Updating a View</Title>
<Para>
What happens if a view is named as the target relation for an
<command>INSERT</command>, <command>UPDATE</command>, or
<command>DELETE</command>? After doing the substitutions
described above, we will have a query tree in which the result
relation points at a subquery range-table entry. This will not
work, so the rewriter throws an error if it sees it has produced
such a thing.
</Para>
<Para>
To change this, we can define rules that modify the behavior of
these kinds of commands. This is the topic of the next section.
</Para>
</Sect2>
</Sect1>
<Sect1 id="rules-update">
<Title>Rules on <command>INSERT</>, <command>UPDATE</>, and <command>DELETE</></Title>
<indexterm zone="rules-update">
<primary>rule</primary>
<secondary sortas="INSERT">for INSERT</secondary>
</indexterm>
<indexterm zone="rules-update">
<primary>rule</primary>
<secondary sortas="UPDATE">for UPDATE</secondary>
</indexterm>
<indexterm zone="rules-update">
<primary>rule</primary>
<secondary sortas="DELETE">for DELETE</secondary>
</indexterm>
<Para>
Rules that are defined on <command>INSERT</>, <command>UPDATE</>,
and <command>DELETE</> are significantly different from the view rules
described in the previous section. First, their <command>CREATE
RULE</command> command allows more:
<ItemizedList>
<ListItem>
<Para>
They are allowed to have no action.
</Para>
</ListItem>
<ListItem>
<Para>
They can have multiple actions.
</Para>
</ListItem>
<ListItem>
<Para>
They can be <literal>INSTEAD</> or not.
</Para>
</ListItem>
<ListItem>
<Para>
The pseudorelations <literal>NEW</> and <literal>OLD</> become useful.
</Para>
</ListItem>
<ListItem>
<Para>
They can have rule qualifications.
</Para>
</ListItem>
</ItemizedList>
Second, they don't modify the query tree in place. Instead they
create zero or more new query trees and can throw away the
original one.
</Para>
<Sect2>
<Title>How Update Rules Work</Title>
<Para>
Keep the syntax
<ProgramListing>
CREATE RULE <replaceable>rule_name</> AS ON <replaceable>event</>
TO <replaceable>object</> [WHERE <replaceable>rule_qualification</>]
DO [INSTEAD] [<replaceable>action</> | (<replaceable>actions</>) | NOTHING];
</ProgramListing>
in mind.
In the following, <firstterm>update rules</> means rules that are defined
on <command>INSERT</>, <command>UPDATE</>, or <command>DELETE</>.
</Para>
<Para>
Update rules get applied by the rule system when the result
relation and the command type of a query tree are equal to the
object and event given in the <command>CREATE RULE</command> command.
For update rules, the rule system creates a list of query trees.
Initially the query-tree list is empty.
There can be zero (<literal>NOTHING</> key word), one, or multiple actions.
To simplify, we will look at a rule with one action. This rule
can have a qualification or not and it can be <literal>INSTEAD</> or not.
</Para>
<Para>
What is a rule qualification? It is a restriction that tells
when the actions of the rule should be done and when not. This
qualification can only reference the pseudorelations <literal>NEW</> and/or <literal>OLD</>,
which basically represent the relation that was given as object (but with a
special meaning).
</Para>
<para>
So we have four cases that produce the following query trees for
a one-action rule.
<variablelist>
<varlistentry>
<term>No qualification and not <literal>INSTEAD</></term>
<listitem>
<para>
the query tree from the rule action with the original query
tree's qualification added
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>No qualification but <literal>INSTEAD</></term>
<listitem>
<para>
the query tree from the rule action with the original query
tree's qualification added
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Qualification given and not <literal>INSTEAD</></term>
<listitem>
<para>
the query tree from the rule action with the rule
qualification and the original query tree's qualification
added
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>Qualification given and <literal>INSTEAD</></term>
<listitem>
<para>
the query tree from the rule action with the rule
qualification and the original query tree's qualification; and
the original query tree with the negated rule qualification
added
</para>
</listitem>
</varlistentry>
</variablelist>
Finally, if the rule is not <literal>INSTEAD</>, the unchanged original query tree is
added to the list. Since only qualified <literal>INSTEAD</> rules already add the
original query tree, we end up with either one or two output query trees
for a rule with one action.
</Para>
<Para>
For <literal>ON INSERT</> rules, the original query (if not suppressed by <literal>INSTEAD</>)
is done before any actions added by rules. This allows the actions to
see the inserted row(s). But for <literal>ON UPDATE</> and <literal>ON
DELETE</> rules, the original query is done after the actions added by rules.
This ensures that the actions can see the to-be-updated or to-be-deleted
rows; otherwise, the actions might do nothing because they find no rows
matching their qualifications.
</Para>
<Para>
The query trees generated from rule actions are thrown into the
rewrite system again, and maybe more rules get applied resulting
in more or less query trees.
So the query trees in the rule actions must have either a different command type
or a different result relation, otherwise, this recursive process will end up in a loop.
There is a fixed recursion limit of currently 100 iterations.
If after 100 iterations there are still update rules to apply, the
rule system assumes a loop over multiple rule definitions and reports
an error.
</Para>
<Para>
The query trees found in the actions of the
<structname>pg_rewrite</structname> system catalog are only
templates. Since they can reference the range-table entries for
<literal>NEW</> and <literal>OLD</>, some substitutions have to be made before they can be
used. For any reference to <literal>NEW</>, the target list of the original
query is searched for a corresponding entry. If found, that
entry's expression replaces the reference. Otherwise, <literal>NEW</> means the
same as <literal>OLD</> (for an <command>UPDATE</command>) or is replaced by
a null value (for an <command>INSERT</command>). Any reference to <literal>OLD</> is
replaced by a reference to the range-table entry that is the
result relation.
</Para>
<Para>
After the system is done applying update rules, it applies view rules to the
produced query tree(s). Views cannot insert new update actions so
there is no need to apply update rules to the output of view rewriting.
</Para>
<Sect3>
<Title>A First Rule Step by Step</Title>
<Para>
Say we want to trace changes to the <literal>sl_avail</> column in the
<literal>shoelace_data</literal> relation. So we set up a log table
and a rule that conditionally writes a log entry when an
<command>UPDATE</command> is performed on
<literal>shoelace_data</literal>.
<ProgramListing>
CREATE TABLE shoelace_log (
sl_name text, -- shoelace changed
sl_avail integer, -- new available value
log_who text, -- who did it
log_when timestamp -- when
);
CREATE RULE log_shoelace AS ON UPDATE TO shoelace_data
WHERE NEW.sl_avail &lt;&gt; OLD.sl_avail
DO INSERT INTO shoelace_log VALUES (
NEW.sl_name,
NEW.sl_avail,
current_user,
current_timestamp
);
</ProgramListing>
</Para>
<Para>
Now someone does:
<ProgramListing>
UPDATE shoelace_data SET sl_avail = 6 WHERE sl_name = 'sl7';
</ProgramListing>
and we look at the log table:
<ProgramListing>
SELECT * FROM shoelace_log;
sl_name | sl_avail | log_who | log_when
---------+----------+---------+----------------------------------
sl7 | 6 | Al | Tue Oct 20 16:14:45 1998 MET DST
(1 row)
</ProgramListing>
</para>
<para>
That's what we expected. What happened in the background is the following.
The parser created the query tree
<ProgramListing>
UPDATE shoelace_data SET sl_avail = 6
FROM shoelace_data shoelace_data
WHERE shoelace_data.sl_name = 'sl7';
</ProgramListing>
There is a rule <literal>log_shoelace</literal> that is <literal>ON UPDATE</> with the rule
qualification expression
<ProgramListing>
NEW.sl_avail &lt;&gt; OLD.sl_avail
</ProgramListing>
and the action
<ProgramListing>
INSERT INTO shoelace_log VALUES (
*NEW*.sl_name, *NEW*.sl_avail,
current_user, current_timestamp )
FROM shoelace_data *NEW*, shoelace_data *OLD*;
</ProgramListing>
(This looks a little strange since you can't normally write
<literal>INSERT ... VALUES ... FROM</>. The <literal>FROM</>
clause here is just to indicate that there are range-table entries
in the query tree for <literal>*NEW*</> and <literal>*OLD*</>.
These are needed so that they can be referenced by variables in
the <command>INSERT</command> command's query tree.)
</Para>
<Para>
The rule is a qualified non-<literal>INSTEAD</> rule, so the rule system
has to return two query trees: the modified rule action and the original
query tree. In step 1, the range table of the original query is
incorporated into the rule's action query tree. This results in:
<ProgramListing>
INSERT INTO shoelace_log VALUES (
*NEW*.sl_name, *NEW*.sl_avail,
current_user, current_timestamp )
FROM shoelace_data *NEW*, shoelace_data *OLD*,
<emphasis>shoelace_data shoelace_data</emphasis>;
</ProgramListing>
In step 2, the rule qualification is added to it, so the result set
is restricted to rows where <literal>sl_avail</> changes:
<ProgramListing>
INSERT INTO shoelace_log VALUES (
*NEW*.sl_name, *NEW*.sl_avail,
current_user, current_timestamp )
FROM shoelace_data *NEW*, shoelace_data *OLD*,
shoelace_data shoelace_data
<emphasis>WHERE *NEW*.sl_avail &lt;&gt; *OLD*.sl_avail</emphasis>;
</ProgramListing>
(This looks even stranger, since <literal>INSERT ... VALUES</> doesn't have
a <literal>WHERE</> clause either, but the planner and executor will have no
difficulty with it. They need to support this same functionality
anyway for <literal>INSERT ... SELECT</>.)
</para>
<para>
In step 3, the original query tree's qualification is added,
restricting the result set further to only the rows that would have been touched
by the original query:
<ProgramListing>
INSERT INTO shoelace_log VALUES (
*NEW*.sl_name, *NEW*.sl_avail,
current_user, current_timestamp )
FROM shoelace_data *NEW*, shoelace_data *OLD*,
shoelace_data shoelace_data
WHERE *NEW*.sl_avail &lt;&gt; *OLD*.sl_avail
<emphasis>AND shoelace_data.sl_name = 'sl7'</emphasis>;
</ProgramListing>
</para>
<para>
Step 4 replaces references to <literal>NEW</> by the target list entries from the
original query tree or by the matching variable references
from the result relation:
<ProgramListing>
INSERT INTO shoelace_log VALUES (
<emphasis>shoelace_data.sl_name</emphasis>, <emphasis>6</emphasis>,
current_user, current_timestamp )
FROM shoelace_data *NEW*, shoelace_data *OLD*,
shoelace_data shoelace_data
WHERE <emphasis>6</emphasis> &lt;&gt; *OLD*.sl_avail
AND shoelace_data.sl_name = 'sl7';
</ProgramListing>
</para>
<para>
Step 5 changes <literal>OLD</> references into result relation references:
<ProgramListing>
INSERT INTO shoelace_log VALUES (
shoelace_data.sl_name, 6,
current_user, current_timestamp )
FROM shoelace_data *NEW*, shoelace_data *OLD*,
shoelace_data shoelace_data
WHERE 6 &lt;&gt; <emphasis>shoelace_data.sl_avail</emphasis>
AND shoelace_data.sl_name = 'sl7';
</ProgramListing>
</para>
<para>
That's it. Since the rule is not <literal>INSTEAD</>, we also output the
original query tree. In short, the output from the rule system
is a list of two query trees that correspond to these statements:
<ProgramListing>
INSERT INTO shoelace_log VALUES (
shoelace_data.sl_name, 6,
current_user, current_timestamp )
FROM shoelace_data
WHERE 6 &lt;&gt; shoelace_data.sl_avail
AND shoelace_data.sl_name = 'sl7';
UPDATE shoelace_data SET sl_avail = 6
WHERE sl_name = 'sl7';
</ProgramListing>
These are executed in this order, and that is exactly what
the rule was meant to do.
</para>
<para>
The substitutions and the added qualifications
ensure that, if the original query would be, say,
<ProgramListing>
UPDATE shoelace_data SET sl_color = 'green'
WHERE sl_name = 'sl7';
</ProgramListing>
no log entry would get written. In that case, the original query
tree does not contain a target list entry for
<literal>sl_avail</>, so <literal>NEW.sl_avail</> will get
replaced by <literal>shoelace_data.sl_avail</>. Thus, the extra
command generated by the rule is
<ProgramListing>
INSERT INTO shoelace_log VALUES (
shoelace_data.sl_name, <emphasis>shoelace_data.sl_avail</emphasis>,
current_user, current_timestamp )
FROM shoelace_data
WHERE <emphasis>shoelace_data.sl_avail</emphasis> &lt;&gt; shoelace_data.sl_avail
AND shoelace_data.sl_name = 'sl7';
</ProgramListing>
and that qualification will never be true.
</para>
<para>
It will also work if the original query modifies multiple rows. So
if someone issued the command
<ProgramListing>
UPDATE shoelace_data SET sl_avail = 0
WHERE sl_color = 'black';
</ProgramListing>
four rows in fact get updated (<literal>sl1</>, <literal>sl2</>, <literal>sl3</>, and <literal>sl4</>).
But <literal>sl3</> already has <literal>sl_avail = 0</>. In this case, the original
query trees qualification is different and that results
in the extra query tree
<ProgramListing>
INSERT INTO shoelace_log
SELECT shoelace_data.sl_name, 0,
current_user, current_timestamp
FROM shoelace_data
WHERE 0 &lt;&gt; shoelace_data.sl_avail
AND <emphasis>shoelace_data.sl_color = 'black'</emphasis>;
</ProgramListing>
being generated by the rule. This query tree will surely insert
three new log entries. And that's absolutely correct.
</Para>
<Para>
Here we can see why it is important that the original query tree
is executed last. If the <command>UPDATE</command> had been
executed first, all the rows would have already been set to zero, so the
logging <command>INSERT</command> would not find any row where
<literal>0 &lt;&gt; shoelace_data.sl_avail</literal>.
</Para>
</Sect3>
</Sect2>
<Sect2 id="rules-update-views">
<Title>Cooperation with Views</Title>
<indexterm zone="rules-update-views"><primary>view</><secondary>updating</></>
<Para>
A simple way to protect view relations from the mentioned
possibility that someone can try to run <command>INSERT</command>,
<command>UPDATE</command>, or <command>DELETE</command> on them is
to let those query trees get thrown away. So we create the rules
<ProgramListing>
CREATE RULE shoe_ins_protect AS ON INSERT TO shoe
DO INSTEAD NOTHING;
CREATE RULE shoe_upd_protect AS ON UPDATE TO shoe
DO INSTEAD NOTHING;
CREATE RULE shoe_del_protect AS ON DELETE TO shoe
DO INSTEAD NOTHING;
</ProgramListing>
If someone now tries to do any of these operations on the view
relation <literal>shoe</literal>, the rule system will
apply these rules. Since the rules have
no actions and are <literal>INSTEAD</>, the resulting list of
query trees will be empty and the whole query will become
nothing because there is nothing left to be optimized or
executed after the rule system is done with it.
</Para>
<Para>
A more sophisticated way to use the rule system is to
create rules that rewrite the query tree into one that
does the right operation on the real tables. To do that
on the <literal>shoelace</literal> view, we create
the following rules:
<ProgramListing>
CREATE RULE shoelace_ins AS ON INSERT TO shoelace
DO INSTEAD
INSERT INTO shoelace_data VALUES (
NEW.sl_name,
NEW.sl_avail,
NEW.sl_color,
NEW.sl_len,
NEW.sl_unit
);
CREATE RULE shoelace_upd AS ON UPDATE TO shoelace
DO INSTEAD
UPDATE shoelace_data
SET sl_name = NEW.sl_name,
sl_avail = NEW.sl_avail,
sl_color = NEW.sl_color,
sl_len = NEW.sl_len,
sl_unit = NEW.sl_unit
WHERE sl_name = OLD.sl_name;
CREATE RULE shoelace_del AS ON DELETE TO shoelace
DO INSTEAD
DELETE FROM shoelace_data
WHERE sl_name = OLD.sl_name;
</ProgramListing>
</para>
<para>
Now assume that once in a while, a pack of shoelaces arrives at
the shop and a big parts list along with it. But you don't want
to manually update the <literal>shoelace</literal> view every
time. Instead we setup two little tables: one where you can
insert the items from the part list, and one with a special
trick. The creation commands for these are:
<ProgramListing>
CREATE TABLE shoelace_arrive (
arr_name text,
arr_quant integer
);
CREATE TABLE shoelace_ok (
ok_name text,
ok_quant integer
);
CREATE RULE shoelace_ok_ins AS ON INSERT TO shoelace_ok
DO INSTEAD
UPDATE shoelace
SET sl_avail = sl_avail + NEW.ok_quant
WHERE sl_name = NEW.ok_name;
</ProgramListing>
Now you can fill the table <literal>shoelace_arrive</literal> with
the data from the parts list:
<ProgramListing>
SELECT * FROM shoelace_arrive;
arr_name | arr_quant
----------+-----------
sl3 | 10
sl6 | 20
sl8 | 20
(3 rows)
</ProgramListing>
Take a quick look at the current data:
<ProgramListing>
SELECT * FROM shoelace;
sl_name | sl_avail | sl_color | sl_len | sl_unit | sl_len_cm
----------+----------+----------+--------+---------+-----------
sl1 | 5 | black | 80 | cm | 80
sl2 | 6 | black | 100 | cm | 100
sl7 | 6 | brown | 60 | cm | 60
sl3 | 0 | black | 35 | inch | 88.9
sl4 | 8 | black | 40 | inch | 101.6
sl8 | 1 | brown | 40 | inch | 101.6
sl5 | 4 | brown | 1 | m | 100
sl6 | 0 | brown | 0.9 | m | 90
(8 rows)
</ProgramListing>
Now move the arrived shoelaces in:
<ProgramListing>
INSERT INTO shoelace_ok SELECT * FROM shoelace_arrive;
</ProgramListing>
and check the results:
<ProgramListing>
SELECT * FROM shoelace ORDER BY sl_name;
sl_name | sl_avail | sl_color | sl_len | sl_unit | sl_len_cm
----------+----------+----------+--------+---------+-----------
sl1 | 5 | black | 80 | cm | 80
sl2 | 6 | black | 100 | cm | 100
sl7 | 6 | brown | 60 | cm | 60
sl4 | 8 | black | 40 | inch | 101.6
sl3 | 10 | black | 35 | inch | 88.9
sl8 | 21 | brown | 40 | inch | 101.6
sl5 | 4 | brown | 1 | m | 100
sl6 | 20 | brown | 0.9 | m | 90
(8 rows)
SELECT * FROM shoelace_log;
sl_name | sl_avail | log_who| log_when
---------+----------+--------+----------------------------------
sl7 | 6 | Al | Tue Oct 20 19:14:45 1998 MET DST
sl3 | 10 | Al | Tue Oct 20 19:25:16 1998 MET DST
sl6 | 20 | Al | Tue Oct 20 19:25:16 1998 MET DST
sl8 | 21 | Al | Tue Oct 20 19:25:16 1998 MET DST
(4 rows)
</ProgramListing>
</para>
<para>
It's a long way from the one <literal>INSERT ... SELECT</literal>
to these results. And the description of the query-tree
transformation will be the last in this chapter. First, there is
the parser's output
<ProgramListing>
INSERT INTO shoelace_ok
SELECT shoelace_arrive.arr_name, shoelace_arrive.arr_quant
FROM shoelace_arrive shoelace_arrive, shoelace_ok shoelace_ok;
</ProgramListing>
Now the first rule <literal>shoelace_ok_ins</literal> is applied and turns this
into
<ProgramListing>
UPDATE shoelace
SET sl_avail = shoelace.sl_avail + shoelace_arrive.arr_quant
FROM shoelace_arrive shoelace_arrive, shoelace_ok shoelace_ok,
shoelace_ok *OLD*, shoelace_ok *NEW*,
shoelace shoelace
WHERE shoelace.sl_name = shoelace_arrive.arr_name;
</ProgramListing>
and throws away the original <command>INSERT</command> on
<literal>shoelace_ok</literal>. This rewritten query is passed to
the rule system again, and the second applied rule
<literal>shoelace_upd</literal> produces
<ProgramListing>
UPDATE shoelace_data
SET sl_name = shoelace.sl_name,
sl_avail = shoelace.sl_avail + shoelace_arrive.arr_quant,
sl_color = shoelace.sl_color,
sl_len = shoelace.sl_len,
sl_unit = shoelace.sl_unit
FROM shoelace_arrive shoelace_arrive, shoelace_ok shoelace_ok,
shoelace_ok *OLD*, shoelace_ok *NEW*,
shoelace shoelace, shoelace *OLD*,
shoelace *NEW*, shoelace_data shoelace_data
WHERE shoelace.sl_name = shoelace_arrive.arr_name
AND shoelace_data.sl_name = shoelace.sl_name;
</ProgramListing>
Again it's an <literal>INSTEAD</> rule and the previous query tree is trashed.
Note that this query still uses the view <literal>shoelace</literal>.
But the rule system isn't finished with this step, so it continues
and applies the <literal>_RETURN</literal> rule on it, and we get
<ProgramListing>
UPDATE shoelace_data
SET sl_name = s.sl_name,
sl_avail = s.sl_avail + shoelace_arrive.arr_quant,
sl_color = s.sl_color,
sl_len = s.sl_len,
sl_unit = s.sl_unit
FROM shoelace_arrive shoelace_arrive, shoelace_ok shoelace_ok,
shoelace_ok *OLD*, shoelace_ok *NEW*,
shoelace shoelace, shoelace *OLD*,
shoelace *NEW*, shoelace_data shoelace_data,
shoelace *OLD*, shoelace *NEW*,
shoelace_data s, unit u
WHERE s.sl_name = shoelace_arrive.arr_name
AND shoelace_data.sl_name = s.sl_name;
</ProgramListing>
Finally, the rule <literal>log_shoelace</literal> gets applied,
producing the extra query tree
<ProgramListing>
INSERT INTO shoelace_log
SELECT s.sl_name,
s.sl_avail + shoelace_arrive.arr_quant,
current_user,
current_timestamp
FROM shoelace_arrive shoelace_arrive, shoelace_ok shoelace_ok,
shoelace_ok *OLD*, shoelace_ok *NEW*,
shoelace shoelace, shoelace *OLD*,
shoelace *NEW*, shoelace_data shoelace_data,
shoelace *OLD*, shoelace *NEW*,
shoelace_data s, unit u,
shoelace_data *OLD*, shoelace_data *NEW*
shoelace_log shoelace_log
WHERE s.sl_name = shoelace_arrive.arr_name
AND shoelace_data.sl_name = s.sl_name
AND (s.sl_avail + shoelace_arrive.arr_quant) &lt;&gt; s.sl_avail;
</ProgramListing>
After that the rule system runs out of rules and returns the
generated query trees.
</para>
<para>
So we end up with two final query trees that are equivalent to the
<Acronym>SQL</Acronym> statements
<ProgramListing>
INSERT INTO shoelace_log
SELECT s.sl_name,
s.sl_avail + shoelace_arrive.arr_quant,
current_user,
current_timestamp
FROM shoelace_arrive shoelace_arrive, shoelace_data shoelace_data,
shoelace_data s
WHERE s.sl_name = shoelace_arrive.arr_name
AND shoelace_data.sl_name = s.sl_name
AND s.sl_avail + shoelace_arrive.arr_quant &lt;&gt; s.sl_avail;
UPDATE shoelace_data
SET sl_avail = shoelace_data.sl_avail + shoelace_arrive.arr_quant
FROM shoelace_arrive shoelace_arrive,
shoelace_data shoelace_data,
shoelace_data s
WHERE s.sl_name = shoelace_arrive.sl_name
AND shoelace_data.sl_name = s.sl_name;
</ProgramListing>
The result is that data coming from one relation inserted into another,
changed into updates on a third, changed into updating
a fourth plus logging that final update in a fifth
gets reduced into two queries.
</Para>
<Para>
There is a little detail that's a bit ugly. Looking at the two
queries, it turns out that the <literal>shoelace_data</literal>
relation appears twice in the range table where it could
definitely be reduced to one. The planner does not handle it and
so the execution plan for the rule systems output of the
<command>INSERT</command> will be
<literallayout class="monospaced">
Nested Loop
-> Merge Join
-> Seq Scan
-> Sort
-> Seq Scan on s
-> Seq Scan
-> Sort
-> Seq Scan on shoelace_arrive
-> Seq Scan on shoelace_data
</literallayout>
while omitting the extra range table entry would result in a
<literallayout class="monospaced">
Merge Join
-> Seq Scan
-> Sort
-> Seq Scan on s
-> Seq Scan
-> Sort
-> Seq Scan on shoelace_arrive
</literallayout>
which produces exactly the same entries in the log table. Thus,
the rule system caused one extra scan on the table
<literal>shoelace_data</literal> that is absolutely not
necessary. And the same redundant scan is done once more in the
<command>UPDATE</command>. But it was a really hard job to make
that all possible at all.
</Para>
<Para>
Now we make a final demonstration of the
<ProductName>PostgreSQL</ProductName> rule system and its power.
Say you add some shoelaces with extraordinary colors to your
database:
<ProgramListing>
INSERT INTO shoelace VALUES ('sl9', 0, 'pink', 35.0, 'inch', 0.0);
INSERT INTO shoelace VALUES ('sl10', 1000, 'magenta', 40.0, 'inch', 0.0);
</ProgramListing>
We would like to make a view to check which
<literal>shoelace</literal> entries do not fit any shoe in color.
The view for this is
<ProgramListing>
CREATE VIEW shoelace_mismatch AS
SELECT * FROM shoelace WHERE NOT EXISTS
(SELECT shoename FROM shoe WHERE slcolor = sl_color);
</ProgramListing>
Its output is
<ProgramListing>
SELECT * FROM shoelace_mismatch;
sl_name | sl_avail | sl_color | sl_len | sl_unit | sl_len_cm
---------+----------+----------+--------+---------+-----------
sl9 | 0 | pink | 35 | inch | 88.9
sl10 | 1000 | magenta | 40 | inch | 101.6
</ProgramListing>
</para>
<para>
Now we want to set it up so that mismatching shoelaces that are
not in stock are deleted from the database.
To make it a little harder for <ProductName>PostgreSQL</ProductName>,
we don't delete it directly. Instead we create one more view
<ProgramListing>
CREATE VIEW shoelace_can_delete AS
SELECT * FROM shoelace_mismatch WHERE sl_avail = 0;
</ProgramListing>
and do it this way:
<ProgramListing>
DELETE FROM shoelace WHERE EXISTS
(SELECT * FROM shoelace_can_delete
WHERE sl_name = shoelace.sl_name);
</ProgramListing>
<foreignphrase>Voil<69></foreignphrase>:
<ProgramListing>
SELECT * FROM shoelace;
sl_name | sl_avail | sl_color | sl_len | sl_unit | sl_len_cm
---------+----------+----------+--------+---------+-----------
sl1 | 5 | black | 80 | cm | 80
sl2 | 6 | black | 100 | cm | 100
sl7 | 6 | brown | 60 | cm | 60
sl4 | 8 | black | 40 | inch | 101.6
sl3 | 10 | black | 35 | inch | 88.9
sl8 | 21 | brown | 40 | inch | 101.6
sl10 | 1000 | magenta | 40 | inch | 101.6
sl5 | 4 | brown | 1 | m | 100
sl6 | 20 | brown | 0.9 | m | 90
(9 rows)
</ProgramListing>
</para>
<para>
A <command>DELETE</command> on a view, with a subquery qualification that
in total uses 4 nesting/joined views, where one of them
itself has a subquery qualification containing a view
and where calculated view columns are used,
gets rewritten into
one single query tree that deletes the requested data
from a real table.
</Para>
<Para>
There are probably only a few situations out in the real world
where such a construct is necessary. But it makes you feel
comfortable that it works.
</Para>
</Sect2>
</Sect1>
<Sect1 id="rules-privileges">
<Title>Rules and Privileges</Title>
<indexterm zone="rules-privileges">
<primary>privilege</primary>
<secondary sortas="Regeln">with rules</secondary>
</indexterm>
<indexterm zone="rules-privileges">
<primary>privilege</primary>
<secondary sortas="Sichten">with views</secondary>
</indexterm>
<Para>
Due to rewriting of queries by the <ProductName>PostgreSQL</ProductName>
rule system, other tables/views than those used in the original
query get accessed. When update rules are used, this can include write access
to tables.
</Para>
<Para>
Rewrite rules don't have a separate owner. The owner of
a relation (table or view) is automatically the owner of the
rewrite rules that are defined for it.
The <ProductName>PostgreSQL</ProductName> rule system changes the
behavior of the default access control system. Relations that
are used due to rules get checked against the
privileges of the rule owner, not the user invoking the rule.
This means that a user only needs the required privileges
for the tables/views that he names explicitly in his queries.
</Para>
<Para>
For example: A user has a list of phone numbers where some of
them are private, the others are of interest for the secretary of the office.
He can construct the following:
<ProgramListing>
CREATE TABLE phone_data (person text, phone text, private boolean);
CREATE VIEW phone_number AS
SELECT person, phone FROM phone_data WHERE NOT private;
GRANT SELECT ON phone_number TO secretary;
</ProgramListing>
Nobody except him (and the database superusers) can access the
<literal>phone_data</> table. But because of the <command>GRANT</>,
the secretary can run a <command>SELECT</command> on the
<literal>phone_number</> view. The rule system will rewrite the
<command>SELECT</command> from <literal>phone_number</> into a
<command>SELECT</command> from <literal>phone_data</> and add the
qualification that only entries where <literal>private</> is false
are wanted. Since the user is the owner of
<literal>phone_number</> and therefore the owner of the rule, the
read access to <literal>phone_data</> is now checked against his
privileges and the query is permitted. The check for accessing
<literal>phone_number</> is also performed, but this is done
against the invoking user, so nobody but the user and the
secretary can use it.
</Para>
<Para>
The privileges are checked rule by rule. So the secretary is for now the
only one who can see the public phone numbers. But the secretary can setup
another view and grant access to that to the public. Then, anyone
can see the <literal>phone_number</> data through the secretary's view.
What the secretary cannot do is to create a view that directly
accesses <literal>phone_data</>. (Actually he can, but it will not work since
every access will be denied during the permission checks.)
And as soon as the user will notice, that the secretary opened
his <literal>phone_number</> view, he can revoke his access. Immediately, any
access to the secretary's view would fail.
</Para>
<Para>
One might think that this rule-by-rule checking is a security
hole, but in fact it isn't. But if it did not work this way, the secretary
could set up a table with the same columns as <literal>phone_number</> and
copy the data to there once per day. Then it's his own data and
he can grant access to everyone he wants. A
<command>GRANT</command> command means, <quote>I trust you</quote>.
If someone you trust does the thing above, it's time to
think it over and then use <command>REVOKE</command>.
</Para>
<Para>
This mechanism also works for update rules. In the examples of
the previous section, the owner of the tables in the example
database could grant the privileges <literal>SELECT</>,
<literal>INSERT</>, <literal>UPDATE</>, and <literal>DELETE</> on
the <literal>shoelace</> view to someone else, but only
<literal>SELECT</> on <literal>shoelace_log</>. The rule action to
write log entries will still be executed successfully, and that
other user could see the log entries. But he cannot create fake
entries, nor could he manipulate or remove existing ones.
</Para>
</Sect1>
<Sect1 id="rules-status">
<Title>Rules and Command Status</Title>
<Para>
The <ProductName>PostgreSQL</ProductName> server returns a command
status string, such as <literal>INSERT 149592 1</>, for each
command it receives. This is simple enough when there are no rules
involved, but what happens when the query is rewritten by rules?
</Para>
<Para>
Rules affect the command status as follows:
<itemizedlist>
<listitem>
<para>
If there is no unconditional <literal>INSTEAD</> rule for the query, then
the originally given query will be executed, and its command
status will be returned as usual. (But note that if there were
any conditional <literal>INSTEAD</> rules, the negation of their qualifications
will have been added to the original query. This may reduce the
number of rows it processes, and if so the reported status will
be affected.)
</para>
</listitem>
<listitem>
<para>
If there is any unconditional <literal>INSTEAD</> rule for the query, then
the original query will not be executed at all. In this case,
the server will return the command status for the last query
that was inserted by an <literal>INSTEAD</> rule (conditional or
unconditional) and is of the same command type
(<command>INSERT</command>, <command>UPDATE</command>, or
<command>DELETE</command>) as the original query. If no query
meeting those requirements is added by any rule, then the
returned command status shows the original query type and
zeroes for the row-count and OID fields.
</para>
</listitem>
</itemizedlist>
(This system was established in PostgreSQL 7.3. In versions
before that, the command status might show different results when
rules exist.)
</Para>
<Para>
The programmer can ensure that any desired <literal>INSTEAD</> rule is the one
that sets the command status in the second case, by giving it the
alphabetically last rule name among the active rules, so that it
gets applied last.
</Para>
</Sect1>
<Sect1 id="rules-triggers">
<Title>Rules versus Triggers</Title>
<indexterm zone="rules-triggers">
<primary>rule</primary>
<secondary sortas="Trigger">compared with triggers</secondary>
</indexterm>
<indexterm zone="rules-triggers">
<primary>trigger</primary>
<secondary sortas="Regeln">compared with rules</secondary>
</indexterm>
<Para>
Many things that can be done using triggers can also be
implemented using the <ProductName>PostgreSQL</ProductName>
rule system. One of the things that cannot be implemented by
rules are some kinds of constraints, especially foreign keys. It is possible
to place a qualified rule that rewrites a command to <literal>NOTHING</>
if the value of a column does not appear in another table.
But then the data is silently thrown away and that's
not a good idea. If checks for valid values are required,
and in the case of an invalid value an error message should
be generated, it must be done by a trigger.
</Para>
<Para>
On the other hand, a trigger that is fired on
<command>INSERT</command> on a view can do the same as a rule: put
the data somewhere else and suppress the insert in the view. But
it cannot do the same thing on <command>UPDATE</command> or
<command>DELETE</command>, because there is no real data in the
view relation that could be scanned, and thus the trigger would
never get called. Only a rule will help.
</Para>
<Para>
For the things that can be implemented by both,
it depends on the usage of the database, which is the best.
A trigger is fired for any affected row once. A rule manipulates
the query tree or generates an additional one. So if many
rows are affected in one statement, a rule issuing one extra
command would usually do a better job than a trigger that is
called for every single row and must execute its operations
many times.
</Para>
<Para>
Here we show an example of how the choice of rules versus triggers
plays out in one situation. There are two tables:
<ProgramListing>
CREATE TABLE computer (
hostname text, -- indexed
manufacturer text -- indexed
);
CREATE TABLE software (
software text, -- indexed
hostname text -- indexed
);
</ProgramListing>
Both tables have many thousands of rows and the indexes on
<structfield>hostname</> are unique. The rule or trigger should
implement a constraint that deletes rows from <literal>software</>
that reference a deleted computer. The trigger would use this command:
<ProgramListing>
DELETE FROM software WHERE hostname = $1;
</ProgramListing>
Since the trigger is called for each individual row deleted from
<literal>computer</>, it can prepare and save the plan for this
command and pass the <structfield>hostname</> value in the
parameter. The rule would be written as
<ProgramListing>
CREATE RULE computer_del AS ON DELETE TO computer
DO DELETE FROM software WHERE hostname = OLD.hostname;
</ProgramListing>
</para>
<para>
Now we look at different types of deletes. In the case of a
<ProgramListing>
DELETE FROM computer WHERE hostname = 'mypc.local.net';
</ProgramListing>
the table <literal>computer</> is scanned by index (fast), and the
command issued by the trigger would also use an index scan (also fast).
The extra command from the rule would be
<ProgramListing>
DELETE FROM software WHERE computer.hostname = 'mypc.local.net'
AND software.hostname = computer.hostname;
</ProgramListing>
Since there are appropriate indexes setup, the planner
will create a plan of
<literallayout class="monospaced">
Nestloop
-> Index Scan using comp_hostidx on computer
-> Index Scan using soft_hostidx on software
</literallayout>
So there would be not that much difference in speed between
the trigger and the rule implementation.
</para>
<para>
With the next delete we want to get rid of all the 2000 computers
where the <structfield>hostname</> starts with
<literal>old</>. There are two possible commands to do that. One
is
<ProgramListing>
DELETE FROM computer WHERE hostname >= 'old'
AND hostname < 'ole'
</ProgramListing>
The command added by the rule will be
<ProgramListing>
DELETE FROM software WHERE computer.hostname >= 'old' AND computer.hostname < 'ole'
AND software.hostname = computer.hostname;
</ProgramListing>
with the plan
<literallayout class="monospaced">
Hash Join
-> Seq Scan on software
-> Hash
-> Index Scan using comp_hostidx on computer
</literallayout>
The other possible command is
<ProgramListing>
DELETE FROM computer WHERE hostname ~ '^old';
</ProgramListing>
which results in the following executing plan for the command
added by the rule:
<literallayout class="monospaced">
Nestloop
-> Index Scan using comp_hostidx on computer
-> Index Scan using soft_hostidx on software
</literallayout>
This shows, that the planner does not realize that the
qualification for <structfield>hostname</> in
<literal>computer</> could also be used for an index scan on
<literal>software</> when there are multiple qualification
expressions combined with <literal>AND</>, which is what it does
in the regular-expression version of the command. The trigger will
get invoked once for each of the 2000 old computers that have to be
deleted, and that will result in one index scan over
<literal>computer</> and 2000 index scans over
<literal>software</>. The rule implementation will do it with two
commands that use indexes. And it depends on the overall size of
the table <literal>software</> whether the rule will still be faster in the
sequential scan situation. 2000 command executions from the trigger over the SPI
manager take some time, even if all the index blocks will soon be in the cache.
</Para>
<Para>
The last command we look at is
<ProgramListing>
DELETE FROM computer WHERE manufacurer = 'bim';
</ProgramListing>
Again this could result in many rows to be deleted from
<literal>computer</>. So the trigger will again run many commands
through the executor. The command generated by the rule will be
<ProgramListing>
DELETE FROM software WHERE computer.manufacurer = 'bim'
AND software.hostname = computer.hostname;
</ProgramListing>
The plan for that command will again be the nested loop over two
index scans, only using a different index on <literal>computer</>:
<ProgramListing>
Nestloop
-> Index Scan using comp_manufidx on computer
-> Index Scan using soft_hostidx on software
</ProgramListing>
In any of these cases, the extra commands from the rule system
will be more or less independent from the number of affected rows
in a command.
</Para>
<![IGNORE[
<!-- What's happening with this? If it doesn't come back, remove this section. -->
<Para>
Another situation is cases on <command>UPDATE</command> where it depends on the
change of an attribute if an action should be performed or
not. In <ProductName>PostgreSQL</ProductName> version 6.4, the
attribute specification for rule events is disabled (it will have
its comeback latest in 6.5, maybe earlier
- stay tuned). So for now the only way to
create a rule as in the shoelace_log example is to do it with
a rule qualification. That results in an extra query that is
performed always, even if the attribute of interest cannot
change at all because it does not appear in the target list
of the initial query. When this is enabled again, it will be
one more advantage of rules over triggers. Optimization of
a trigger must fail by definition in this case, because the
fact that its actions will only be done when a specific attribute
is updated is hidden in its functionality. The definition of
a trigger only allows to specify it on row level, so whenever a
row is touched, the trigger must be called to make its
decision. The rule system will know it by looking up the
target list and will suppress the additional query completely
if the attribute isn't touched. So the rule, qualified or not,
will only do its scans if there ever could be something to do.
</Para>
]]>
<Para>
The summary is, rules will only be significantly slower than
triggers if their actions result in large and badly qualified
joins, a situation where the planner fails.
</Para>
</Sect1>
</Chapter>
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