Views and the Rule System

Implementation of Views in Postgres

Views in Postgres are implemented using the rule system. In fact there is absolutely no difference between a

    CREATE VIEW myview AS SELECT * FROM mytab;

    CREATE TABLE myview (same attribute list as for mytab);
    CREATE RULE "_RETmyview" AS ON SELECT TO myview DO INSTEAD
        SELECT * FROM mytab;

How SELECT Rules Work

Rules ON SELECT are applied to all queries as the last step, even if the command given is an INSERT, UPDATE or DELETE. And they have different semantics from the others in that they modify the parsetree in place instead of creating a new one. So SELECT rules are described first.

Currently, there could be only one action and it must be a SELECT action that is INSTEAD. This restriction was required to make rules safe enough to open them for ordinary users and it restricts rules ON SELECT to real view rules.

The example for this document 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 INSERT, UPDATE and DELETE operations so that the final result will be a view that behaves like a real table with some magic functionality. It 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.

The database needed to play on the examples is named al_bundy. You'll see soon why this is the database name. And it needs the procedural language PL/pgSQL installed, because we need a little min() function returning the lower of 2 integer values. We create that as

    CREATE FUNCTION min(integer, integer) RETURNS integer AS
        'BEGIN
            IF $1 < $2 THEN
                RETURN $1;
            END IF;
            RETURN $2;
        END;'
    LANGUAGE 'plpgsql';

The real tables we need in the first two rule system descripitons are these:

    CREATE TABLE shoe_data (
        shoename   char(10),      -- primary key
        sh_avail   integer,       -- available # of pairs
        slcolor    char(10),      -- preferred shoelace color
        slminlen   float,         -- miminum shoelace length
        slmaxlen   float,         -- maximum shoelace length
        slunit     char(8)        -- length unit
    );

    CREATE TABLE shoelace_data (
        sl_name    char(10),      -- primary key
        sl_avail   integer,       -- available # of pairs
        sl_color   char(10),      -- shoelace color
        sl_len     float,         -- shoelace length
        sl_unit    char(8)        -- length unit
    );

    CREATE TABLE unit (
        un_name    char(8),       -- the primary key
        un_fact    float          -- factor to transform to cm
    );

The views are created as

    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;

The rules action is one querytree that is an exact copy of the SELECT statement in the view creation command.

Note: The two extra range table entries for NEW and OLD (named *NEW* and *CURRENT* for historical reasons in the printed querytree) you can see in the pg_rewrite entry aren't of interest for SELECT rules.

    al_bundy=> INSERT INTO unit VALUES ('cm', 1.0);
    al_bundy=> INSERT INTO unit VALUES ('m', 100.0);
    al_bundy=> INSERT INTO unit VALUES ('inch', 2.54);
    al_bundy=> 
    al_bundy=> INSERT INTO shoe_data VALUES 
    al_bundy->     ('sh1', 2, 'black', 70.0, 90.0, 'cm');
    al_bundy=> INSERT INTO shoe_data VALUES 
    al_bundy->     ('sh2', 0, 'black', 30.0, 40.0, 'inch');
    al_bundy=> INSERT INTO shoe_data VALUES 
    al_bundy->     ('sh3', 4, 'brown', 50.0, 65.0, 'cm');
    al_bundy=> INSERT INTO shoe_data VALUES 
    al_bundy->     ('sh4', 3, 'brown', 40.0, 50.0, 'inch');
    al_bundy=> 
    al_bundy=> INSERT INTO shoelace_data VALUES 
    al_bundy->     ('sl1', 5, 'black', 80.0, 'cm');
    al_bundy=> INSERT INTO shoelace_data VALUES 
    al_bundy->     ('sl2', 6, 'black', 100.0, 'cm');
    al_bundy=> INSERT INTO shoelace_data VALUES 
    al_bundy->     ('sl3', 0, 'black', 35.0 , 'inch');
    al_bundy=> INSERT INTO shoelace_data VALUES 
    al_bundy->     ('sl4', 8, 'black', 40.0 , 'inch');
    al_bundy=> INSERT INTO shoelace_data VALUES 
    al_bundy->     ('sl5', 4, 'brown', 1.0 , 'm');
    al_bundy=> INSERT INTO shoelace_data VALUES 
    al_bundy->     ('sl6', 0, 'brown', 0.9 , 'm');
    al_bundy=> INSERT INTO shoelace_data VALUES 
    al_bundy->     ('sl7', 7, 'brown', 60 , 'cm');
    al_bundy=> INSERT INTO shoelace_data VALUES 
    al_bundy->     ('sl8', 1, 'brown', 40 , 'inch');
    al_bundy=> 
    al_bundy=> 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)

    SELECT shoelace.sl_name, shoelace.sl_avail,
           shoelace.sl_color, shoelace.sl_len,
           shoelace.sl_unit, shoelace.sl_len_cm
      FROM shoelace shoelace;

    SELECT s.sl_name, s.sl_avail,
           s.sl_color, s.sl_len, s.sl_unit,
           float8mul(s.sl_len, u.un_fact) AS sl_len_cm
      FROM shoelace *OLD*, shoelace *NEW*,
           shoelace_data s, unit u
     WHERE bpchareq(s.sl_unit, u.un_name);

    SELECT shoelace.sl_name, shoelace.sl_avail,
           shoelace.sl_color, shoelace.sl_len,
           shoelace.sl_unit, shoelace.sl_len_cm
      FROM shoelace shoelace, shoelace *OLD*,
           shoelace *NEW*, shoelace_data s,
           unit u;

    SELECT shoelace.sl_name, shoelace.sl_avail,
           shoelace.sl_color, shoelace.sl_len,
           shoelace.sl_unit, shoelace.sl_len_cm
      FROM shoelace shoelace, shoelace *OLD*,
           shoelace *NEW*, shoelace_data s,
           unit u
     WHERE bpchareq(s.sl_unit, u.un_name);

    SELECT s.sl_name, s.sl_avail, 
           s.sl_color, s.sl_len, 
           s.sl_unit, float8mul(s.sl_len, u.un_fact) AS sl_len_cm
      FROM shoelace shoelace, shoelace *OLD*,
           shoelace *NEW*, shoelace_data s,
           unit u
     WHERE bpchareq(s.sl_unit, u.un_name);

    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;

Now we face Al with the problem that the Blues Brothers appear in his shop and want to buy some new shoes, and as the Blues Brothers are, they want to wear the same shoes. And they want to wear them immediately, so they need shoelaces too.

Al needs to know for which shoes currently in the store he has the matching shoelaces (color and size) and where the total number of exactly matching pairs is greater or equal to two. We theach him how to do and he asks his database:

    al_bundy=> 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)

The output of the parser this time is the parsetree

    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 int4ge(shoe_ready.total_avail, 2);

    SELECT rsh.shoename, rsh.sh_avail,
           rsl.sl_name, rsl.sl_avail,
           min(rsh.sh_avail, rsl.sl_avail) AS total_avail
      FROM shoe_ready shoe_ready, shoe_ready *OLD*,
           shoe_ready *NEW*, shoe rsh,
           shoelace rsl
     WHERE int4ge(min(rsh.sh_avail, rsl.sl_avail), 2)
       AND (bpchareq(rsl.sl_color, rsh.slcolor)
            AND float8ge(rsl.sl_len_cm, rsh.slminlen_cm)
            AND float8le(rsl.sl_len_cm, rsh.slmaxlen_cm)
           );

    SELECT sh.shoename, sh.sh_avail,
           rsl.sl_name, rsl.sl_avail,
           min(sh.sh_avail, rsl.sl_avail) AS total_avail,
      FROM shoe_ready shoe_ready, shoe_ready *OLD*,
           shoe_ready *NEW*, shoe rsh,
           shoelace rsl, shoe *OLD*,
           shoe *NEW*, shoe_data sh,
           unit un
     WHERE (int4ge(min(sh.sh_avail, rsl.sl_avail), 2)
            AND (bpchareq(rsl.sl_color, sh.slcolor)
                 AND float8ge(rsl.sl_len_cm, 
                              float8mul(sh.slminlen, un.un_fact))
                 AND float8le(rsl.sl_len_cm, 
                              float8mul(sh.slmaxlen, un.un_fact))
                )
           )
       AND bpchareq(sh.slunit, un.un_name);

    SELECT sh.shoename, sh.sh_avail,
           s.sl_name, s.sl_avail,
           min(sh.sh_avail, s.sl_avail) AS total_avail
      FROM shoe_ready shoe_ready, shoe_ready *OLD*,
           shoe_ready *NEW*, shoe rsh,
           shoelace rsl, shoe *OLD*,
           shoe *NEW*, shoe_data sh,
           unit un, shoelace *OLD*,
           shoelace *NEW*, shoelace_data s,
           unit u
     WHERE (    (int4ge(min(sh.sh_avail, s.sl_avail), 2)
                 AND (bpchareq(s.sl_color, sh.slcolor)
                      AND float8ge(float8mul(s.sl_len, u.un_fact), 
                                   float8mul(sh.slminlen, un.un_fact))
                      AND float8le(float8mul(s.sl_len, u.un_fact), 
                                   float8mul(sh.slmaxlen, un.un_fact))
                     )
                )
            AND bpchareq(sh.slunit, un.un_name)
           )
       AND bpchareq(s.sl_unit, u.un_name);

    SELECT sh.shoename, sh.sh_avail,
           s.sl_name, s.sl_avail,
           min(sh.sh_avail, s.sl_avail) AS total_avail
      FROM shoe_data sh, shoelace_data s, unit u, unit un
     WHERE min(sh.sh_avail, s.sl_avail) >= 2
       AND s.sl_color = sh.slcolor
       AND s.sl_len * u.un_fact >= sh.slminlen * un.un_fact
       AND s.sl_len * u.un_fact <= sh.slmaxlen * un.un_fact
       AND sh.sl_unit = un.un_name
       AND s.sl_unit = u.un_name;

Note: There is currently no recursion stopping mechanism for view rules in the rule system (only for the other rules). This doesn't hurt much, because the only way to push this into an endless loop (blowing up the backend until it reaches the memory limit) is to create tables and then setup the view rules by hand with CREATE RULE in such a way, that one selects from the other that selects from the one. This could never happen if CREATE VIEW is used because on the first CREATE VIEW, the second relation does not exist and thus the first view cannot select from the second.

View Rules in Non-SELECT Statements

Two details of the parsetree aren't touched in the description of view rules above. These are the commandtype and the resultrelation. In fact, view rules don't need these informations.

There are only a few differences between a parsetree for a SELECT and one for any other command. Obviously they have another commandtype and this time the resultrelation points to the rangetable entry where the result should go. Anything else is absolutely the same. So having two tables t1 and t2 with attributes a and b, the parsetrees for the two statements

    SELECT t2.b FROM t1, t2 WHERE t1.a = t2.a;

    UPDATE t1 SET b = t2.b WHERE t1.a = t2.a;

• The rangetables contain entries for the tables t1 and t2.

• The targetlists contain one variable that points to attribute b of the rangetable entry for table t2.

• The qualification expressions compare the attributes a of both ranges for equality.

    UPDATE t1 SET a = t1.a, b = t2.b WHERE t1.a = t2.a;

    SELECT t1.a, t2.b FROM t1, t2 WHERE t1.a = t2.a;

To resolve this problem, another entry is added to the targetlist in UPDATE and DELETE statements. The current tuple ID (ctid). This is a system attribute with a special feature. It contains the block and position in the block for the row. Knowing the table, the ctid can be used to find one specific row in a 1.5GB sized table containing millions of rows by fetching one single data block. After adding the ctid to the targetlist, the final result set could be defined as

    SELECT t1.a, t2.b, t1.ctid FROM t1, t2 WHERE t1.a = t2.a;

Knowing that all, we can simply apply view rules in absolutely the same way to any command. There is no difference.

The Power of Views in Postgres

The above demonstrates how the rule system incorporates view definitions into the original parsetree. In the second example a simple SELECT from one view created a final parsetree that is a join of 4 tables (unit is used twice with different names).

Benefits

The benefit of implementing views with the rule system is, that the optimizer 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 parsetree. And this is still the situation when the original query is already a join over views. Now the optimizer has to decide which is the best path to execute the query. The more information the optimizer has, the better this decision can be. And the rule system as implemented in Postgres ensures, that this is all information available about the query up to now.

Concerns

There was a long time where the Postgres rule system was considered broken. The use of rules was not recommended and the only part working was view rules. And also these view rules gave problems because the rule system wasn't able to apply them properly on statements other than a SELECT (for example an UPDATE that used data from a view didn't work).

During that time, development moved on and many features were added to the parser and optimizer. The rule system got more and more out of sync with their capabilities and it became harder and harder to start fixing it. Thus, no one did.

For 6.4, someone locked the door, took a deep breath and shuffled that damned thing up. What came out was a rule system with the capabilities described in this document. But there are still some constructs not handled and some where it fails due to things that are currently not supported by the Postgres query optimizer.

• Views with aggregate columns have bad problems. Aggregate expressions in qualifications must be used in subselects. Currently it is not possible to do a join of two views, each having an aggregate column, and compare the two aggregate values in the qualification. In the meantime it is possible to put these aggregate expressions into functions with the appropriate arguments and use them in the view definition.

• Views of unions are currently not supported. Well it's easy to rewrite a simple SELECT into a union. But it is a little difficult if the view is part of a join doing an update.

• ORDER BY clauses in view definitions aren't supported.

• DISTINCT isn't supported in view definitions.

Implementation Side Effects

Using the described rule system to implement views has a funny side effect. The following does not seem to work:

    al_bundy=> INSERT INTO shoe (shoename, sh_avail, slcolor)
    al_bundy->     VALUES ('sh5', 0, 'black');
    INSERT 20128 1
    al_bundy=> SELECT shoename, sh_avail, slcolor FROM shoe_data;
    shoename  |sh_avail|slcolor   
    ----------+--------+----------
    sh1       |       2|black     
    sh3       |       4|brown     
    sh2       |       0|black     
    sh4       |       3|brown     
    (4 rows)

We can also issue a DELETE and if it does not have a qualification, it tells us that rows have been deleted and the next vacuum run will reset the file to zero size.

The reason for that behaviour is, that the parsetree for the INSERT does not reference the shoe relation in any variable. The targetlist contains only constant values. So there is no rule to apply and it goes down unchanged into execution and the row is inserted. And so for the DELETE.

To change this we can define rules that modify the behaviour of non-SELECT queries. This is the topic of the next section.