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Appendix F. Additional Supplied Modules

Table F-11.

isn

Functions

Function

Returns

Description

isn_weak(boolean)

boolean

Sets the weakinput mode

(returns new setting)

isn_weak()

boolean

Gets the current status of the

weak mode

make_valid(isn)

isn

Validates an invalid number

(clears the invalid ﬂag)

is_valid(isn)

boolean

Checks for the presence of the

invalidﬂag

Weak mode is usedtobe able to insertinvaliddata into atable. Invalidmeans the check digitis wrong,

not that there are missing numbers.

Why would you want to use the weak mode? Well, it could be that you have a huge collection of

ISBN numbers, andthatthere are somany of them that for weird reasons some have the wrong check

digit (perhaps the numbers were scanned from a printed list and the OCR got the numbers wrong,

perhaps the numbers were manually captured... who knows). Anyway, the point is you might want to

clean the mess up, but you still want to be able to have all the numbers in your database and maybe

use an external tool to locate the invalid numbers in the database so you can verify the information

and validate it more easily; so for example you’d want to select all the invalid numbers inthe table.

When you insertinvalidnumbers ina table using the weak mode, the number will be insertedwith the

corrected check digit, but it will be displayed with an exclamation mark (

)at the end, for example

0-11-000322-5!

.This invalid marker canbe checked with the

is_valid

functionandclearedwith

the

make_valid

function.

You can also force the insertion of invalid numbers even when not in the weak mode, by appending

the

character at the end of the number.

Another special featureis that duringinput, you canwrite

in place of the checkdigit, andthe correct

check digit will be inserted automatically.

F.19.4. Examples

--Using the types directly:

SELECT isbn(’978-0-393-04002-9’);

SELECT isbn13(’0901690546’);

SELECT issn(’1436-4522’);

--Casting types:

-- note that you can only cast from ean13 to another type when the

-- number would be valid in the realm of the target type;

-- thus, the following will NOT work: select isbn(ean13(’0220356483481’));

-- but these will:

SELECT upc(ean13(’0220356483481’));

SELECT ean13(upc(’220356483481’));

--Create a table with a single column to hold ISBN numbers:

CREATE TABLE test (id isbn);

INSERT INTO test VALUES(’9780393040029’);

--Automatically calculate check digits (observe the ’?’):

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Appendix F. Additional Supplied Modules

INSERT INTO test VALUES(’220500896?’);

INSERT INTO test VALUES(’978055215372?’);

SELECT issn(’3251231?’);

SELECT ismn(’979047213542?’);

--Using the weak mode:

SELECT isn_weak(true);

INSERT INTO test VALUES(’978-0-11-000533-4’);

INSERT INTO test VALUES(’9780141219307’);

INSERT INTO test VALUES(’2-205-00876-X’);

SELECT isn_weak(false);

SELECT id FROM test WHERE NOT is_valid(id);

UPDATE test SET id = make_valid(id) WHERE id = ’2-205-00876-X!’;

SELECT

FROM test;

SELECT isbn13(id) FROM test;

F.19.5. Bibliography

The information to implement this module was collected from several sites, including:

•

http://www.isbn-international.org/

•

http://www.issn.org/

•

http://www.ismn-international.org/

•

http://www.wikipedia.org/

The preﬁxes used for hyphenation were also compiled from:

•

http://www.gs1.org/productssolutions/idkeys/support/preﬁx_list.html

•

http://en.wikipedia.org/wiki/List_of_ISBN_identiﬁer_groups

•

https://www.isbn-international.org/content/isbn-users-manual

•

http://en.wikipedia.org/wiki/International_Standard_Music_Number

•

http://www.ismn-international.org/ranges.html

Care was taken during the creation of the algorithms and they were meticulously veriﬁed against the

suggested algorithms in the ofﬁcial ISBN, ISMN, ISSN User Manuals.

F.19.6. Author

Germán Méndez Bravo (Kronuz), 2004 - 2006

This module was inspiredby Garrett A. Wollman’s

isbn_issn

code.

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Appendix F. Additional Supplied Modules

F.20. lo

The

module provides support for managing Large Objects (also called LOs or BLOBs). This

includes a data type

and a trigger

lo_manage

F.20.1. Rationale

One of the problems with the JDBC driver (and this affects the ODBC driver also), is that the speciﬁ-

cation assumes thatreferences to BLOBs (Binary Large OBjects) are stored withina table, and if that

entry is changed, the associated BLOB is deleted from the database.

As PostgreSQL stands, this doesn’t occur. Large objects are treated as objects in their own right; a

table entry can reference a large object by OID, but there can be multiple table entries referencing

the same large object OID, so the system doesn’t delete the large object just because you change or

remove one such entry.

Now this is ﬁne for PostgreSQL-speciﬁc applications, but standard code using JDBCor ODBCwon’t

delete the objects, resulting in orphan objects — objects that are not referenced by anything, and

simply occupy disk space.

The

module allows ﬁxing this by attaching a trigger to tables that contain LO reference columns.

The trigger essentially just does a

lo_unlink

whenever you delete or modify a value referencing a

large object. When you use this trigger, you are assuming that there is only one database reference to

any large object that is referenced in a trigger-controlled column!

The module also provides a data type

,whichis really just a domain of the

oid

type. This is useful

for differentiating database columns that hold large object references from those that are OIDs of

other things. You don’t have to use the

type to use the trigger, but it may be convenient to use it to

keep track of which columns in your database represent large objects that you are managing with the

trigger. Itis also rumored that the ODBC driver gets confusedif you don’t use

for BLOB columns.

F.20.2. How to Use It

Here’s a simple example of usage:

CREATE TABLE image (title TEXT, raster lo);

CREATE TRIGGER t_raster BEFORE UPDATE OR DELETE ON image

FOR EACH ROW EXECUTE PROCEDURE lo_manage(raster);

For each column that will contain unique references to large objects, create a

BEFORE UPDATE OR

DELETE

trigger, and give the column name as the sole trigger argument. You can also restrict the

trigger to only execute on updates to the column by using

BEFORE UPDATE OF column_name

.If

you need multiple

columns in the same table, create a separate trigger for each one, remembering

to give a different name to each trigger on the same table.

F.20.3. Limitations

•

Dropping a table will still orphan any objects it contains, as the trigger is not executed. You can

avoid this by preceding the

DROP TABLE

with

DELETE FROM

table

TRUNCATE

has the same hazard.

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Appendix F. Additional Supplied Modules

If you already have, or suspect you have, orphaned large objects, see the vacuumlo module to help

you clean them up. It’s a good idea to run vacuumlo occasionally as a back-stop to the

lo_manage

trigger.

•

Some frontends may create their own tables, and will not create the associated trigger(s). Also,

users maynot remember (or know) to create the triggers.

F.20.4. Author

Peter Mount <

peter@retep.org.uk

F.21. ltree

This module implements a data type

ltree

for representing labels of data stored in a hierarchical

tree-like structure. Extensive facilities for searching through label trees are provided.

F.21.1. Deﬁnitions

Alabel is a sequence of alphanumeric characters and underscores (for example, in C locale the char-

acters

A-Za-z0-9_

are allowed). Labels must be less than 256 bytes long.

Examples:

Personal_Services

Alabel path is a sequence of zero or more labels separated by dots, for example

L1.L2.L3

,repre-

senting a path from the root of a hierarchicaltree to a particular node. The length of a label path must

be less than 65Kb, but keeping it under 2Kb is preferable. In practice this is not a major limitation;

for example, the longest label path in the DMOZ catalog (http://www.dmoz.org) is about 240 bytes.

Example:

Top.Countries.Europe.Russia

The

ltree

module provides several data types:

•

ltree

stores a label path.

•

lquery

represents a regular-expression-like pattern for matching

ltree

values. A simple word

matches that label within a path. A star symbol (

)matches zero or more labels. For example:

foo

Match the exact label path

foo

.foo.

Match any label path containing the label

foo

.foo

Match any label path whose last label is

foo

Star symbols can alsobe quantiﬁed torestrict how many labels theycan match:

{

}

Match exactly

labels

{

Match at least

labels

{

}

Match at least

but not more than

labels

}

Match at most

labels -- same as

{0,

}

Thereare severalmodiﬁers thatcanbe put atthe endof a non-star label in

lquery

to makeit match

more thanjust the exact match:

Match case-insensitively, for example

matches

Match any label with this prefix, for example

foo

matches

foobar

Match initial underscore-separated words

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Appendix F. Additional Supplied Modules

The behavior of

is a bit complicated. It tries to match words rather than the entire label. For ex-

ample

foo_bar%

matches

foo_bar_baz

but not

foo_barbaz

.If combined with

,preﬁx match-

ing applies to each word separately, for example

foo_bar%

matches

foo1_bar2_baz

but not

foo1_br2_baz

Also, you can write several possibly-modiﬁed labels separated with

(OR) to match any of those

labels, and you can put

(NOT) at the start to match any label that doesn’t match any of the

alternatives.

Here’s an annotated example of

lquery

Top.

{0,2}.sport

@.!football|tennis.Russ

|Spain

This query will match any label path that:

a. begins with the label

Top

b. and next has zero to two labels before

c. a label beginning with the case-insensitive preﬁx

sport

d. then a label not matching

football

nor

tennis

e. and then ends with a label beginning with

Russ

or exactly matching

Spain

•

ltxtquery

represents a full-text-search-like pattern for matching

ltree

values. An

ltxtquery

value contains words, possibly with the modiﬁers

at the end; the modiﬁers have the same

meanings as in

lquery

.Words canbe combinedwith

(AND),

(OR),

(NOT), and parentheses.

The key difference from

lquery

is that

ltxtquery

matches words withoutregard totheir position

in the label path.

Here’s an example

ltxtquery

Europe & Russia

@ & !Transportation

This will match paths that contain the label

Europe

and any label beginning with

Russia

(case-

insensitive), but not paths containing the label

Transportation

. The location of these words

within the path is not important. Also, when

is used, the wordcan be matched toanyunderscore-

separated word within a label, regardless of position.

Note:

ltxtquery

allows whitespace between symbols, but

ltree

and

lquery

do not.

F.21.2. Operators and Functions

Type

ltree

has the usual comparison operators

.Comparison sorts inthe order

of a treetraversal, withthechildrenof a nodesortedbylabeltext. In addition, thespecialized operators

shown in Table F-12 are available.

Table F-12.

ltree

Operators

Operator

Returns

Description

ltree @> ltree

boolean

is left argument an ancestor of

right (or equal)?

ltree <@ ltree

boolean

is left argument a descendant of

right (or equal)?

ltree ~ lquery

boolean

does

ltree

match

lquery

lquery ~ ltree

boolean

does

ltree

match

lquery

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Appendix F. Additional Supplied Modules

Operator

Returns

Description

ltree ? lquery[]

boolean

does

ltree

match any

lquery

in array?

lquery[] ? ltree

boolean

does

ltree

match any

lquery

in array?

ltree @ ltxtquery

boolean

does

ltree

match

ltxtquery

ltxtquery @ ltree

boolean

does

ltree

match

ltxtquery

ltree || ltree

ltree

concatenate

ltree

paths

ltree || text

ltree

convert text to

ltree

and

concatenate

text || ltree

ltree

convert text to

ltree

and

concatenate

ltree[] @> ltree

boolean

does array contain an ancestor

ltree

ltree <@ ltree[]

boolean

does array contain an ancestor

ltree

ltree[] <@ ltree

boolean

does array contain a descendant

ltree

ltree @> ltree[]

boolean

does array contain a descendant

ltree

ltree[] ~ lquery

boolean

does array contain any path

matching

lquery

lquery ~ ltree[]

boolean

does array contain any path

matching

lquery

ltree[] ? lquery[]

boolean

does

ltree

array contain any

path matching any

lquery

lquery[] ? ltree[]

boolean

does

ltree

array contain any

path matching any

lquery

ltree[] @ ltxtquery

boolean

does array contain any path

matching

ltxtquery

ltxtquery @ ltree[]

boolean

does array contain any path

matching

ltxtquery

ltree[] ?@> ltree

ltree

ﬁrst array entry that is an

ancestor of

ltree

;NULL if

none

ltree[] ?<@ ltree

ltree

ﬁrst array entry that is a

descendant of

ltree

;NULL if

none

ltree[] ?~ lquery

ltree

ﬁrst array entry that matches

lquery

;NULL if none

ltree[] ?@ ltxtquery

ltree

ﬁrst array entry that matches

ltxtquery

;NULL if none

The operators

and

have analogues

^<@

^@>

,which are the same except they do

not use indexes. These are useful only for testing purposes.

2813

Appendix F. Additional Supplied Modules

The available functions are shown in Table F-13.

Table F-13.

ltree

Functions

Function

Return Type

Description

Example

Result

subltree(ltree,

int start,

int end)

ltree

subpath of

ltree

from position

start

to position

end

-1 (counting

from 0)

subltree(’Top.Child1.Child2’,1,2)

Child1

subpath(ltree,

int offset,

int len)

ltree

subpath of

ltree

starting at position

offset

,length

len

.If

offset

negative, subpath

starts that far from

the end of the

path. If

len

negative, leaves

that many labels

off the end of the

path.

subpath(’Top.Child1.Child2’,0,2)

Top.Child1

subpath(ltree,

int offset)

ltree

subpath of

ltree

starting at position

offset

extending to end

of path. If

offset

is negative,

subpath starts that

far from the end

of the path.

subpath(’Top.Child1.Child2’,1)

Child1.Child2

nlevel(ltree)

integer

number of labels

in path

nlevel(’Top.Child1.Child2’)

index(ltree

a, ltree b)

integer

position of ﬁrst

occurrence of

;-1 if not found

index(’0.1.2.3.5.4.5.6.8.5.6.8’,’5.6’)

index(ltree

a, ltree b,

int offset)

integer

position of ﬁrst

occurrence of

,searching

starting at

offset

;negative

offset

means

start

-offset

labels from the

end of the path

index(’0.1.2.3.5.4.5.6.8.5.6.8’,’5.6’,-4)

text2ltree(text)

ltree

cast

text

ltree

ltree2text(ltree)

text

cast

ltree

text

2814

Appendix F. Additional Supplied Modules

Function

Return Type

Description

Example

Result

lca(ltree,

ltree, ...)

ltree

lowest common

ancestor, i.e.,

longest common

preﬁx of paths (up

to 8 arguments

supported)

lca(’1.2.2.3’,’1.2.3.4.5.6’)

1.2

lca(ltree[])

ltree

lowest common

ancestor, i.e.,

longest common

preﬁx of paths

lca(array[’1.2.2.3’::ltree,’1.2.3’])

1.2

F.21.3. Indexes

ltree

supports several types of indexes that can speed up the indicated operators:

•

B-tree index over

ltree

•

GiST index over

ltree

Example of creating such an index:

CREATE INDEX path_gist_idx ON test USING GIST (path);

•

GiST index over

ltree[]

ltree[] <@ ltree

ltree @> ltree[]

Example of creating such an index:

CREATE INDEX path_gist_idx ON test USING GIST (array_path);

Note: This index type is lossy.

F.21.4. Example

This exampleuses thefollowingdata(alsoavailable inﬁle

contrib/ltree/ltreetest.sql

in the

source distribution):

CREATE TABLE test (path ltree);

INSERT INTO test VALUES (’Top’);

INSERT INTO test VALUES (’Top.Science’);

INSERT INTO test VALUES (’Top.Science.Astronomy’);

INSERT INTO test VALUES (’Top.Science.Astronomy.Astrophysics’);

INSERT INTO test VALUES (’Top.Science.Astronomy.Cosmology’);

INSERT INTO test VALUES (’Top.Hobbies’);

INSERT INTO test VALUES (’Top.Hobbies.Amateurs_Astronomy’);

INSERT INTO test VALUES (’Top.Collections’);

INSERT INTO test VALUES (’Top.Collections.Pictures’);

INSERT INTO test VALUES (’Top.Collections.Pictures.Astronomy’);

INSERT INTO test VALUES (’Top.Collections.Pictures.Astronomy.Stars’);

INSERT INTO test VALUES (’Top.Collections.Pictures.Astronomy.Galaxies’);

INSERT INTO test VALUES (’Top.Collections.Pictures.Astronomy.Astronauts’);

CREATE INDEX path_gist_idx ON test USING gist(path);

CREATE INDEX path_idx ON test USING btree(path);

Now, we have a table

test

populated with data describing the hierarchy shown below:

2815

Appendix F. Additional Supplied Modules

Top

Science Hobbies Collections

Astronomy

Amateurs_Astronomy Pictures

Astrophysics

Cosmology

Astronomy

Galaxies Stars Astronauts

We can do inheritance:

ltreetest=> SELECT path FROM test WHERE path <@ ’Top.Science’;

path

------------------------------------

Top.Science

Top.Science.Astronomy

Top.Science.Astronomy.Astrophysics

Top.Science.Astronomy.Cosmology

(4 rows)

Here are some examples of path matching:

ltreetest=> SELECT path FROM test WHERE path ~ ’

.Astronomy.

’;

path

-----------------------------------------------

Top.Science.Astronomy

Top.Science.Astronomy.Astrophysics

Top.Science.Astronomy.Cosmology

Top.Collections.Pictures.Astronomy

Top.Collections.Pictures.Astronomy.Stars

Top.Collections.Pictures.Astronomy.Galaxies

Top.Collections.Pictures.Astronomy.Astronauts

(7 rows)

ltreetest=> SELECT path FROM test WHERE path ~ ’

.!pictures@.

.Astronomy.

’;

path

------------------------------------

Top.Science.Astronomy

Top.Science.Astronomy.Astrophysics

Top.Science.Astronomy.Cosmology

(3 rows)

Here are some examples of full text search:

ltreetest=> SELECT path FROM test WHERE path @ ’Astro

% & !pictures@’;

path

------------------------------------

Top.Science.Astronomy

Top.Science.Astronomy.Astrophysics

Top.Science.Astronomy.Cosmology

Top.Hobbies.Amateurs_Astronomy

(4 rows)

ltreetest=> SELECT path FROM test WHERE path @ ’Astro

& !pictures@’;

2816

Appendix F. Additional Supplied Modules

path

------------------------------------

Top.Science.Astronomy

Top.Science.Astronomy.Astrophysics

Top.Science.Astronomy.Cosmology

(3 rows)

Path construction using functions:

ltreetest=> SELECT subpath(path,0,2)||’Space’||subpath(path,2) FROM test WHERE path <@ ’Top.Science.Astronomy’;

?column?

------------------------------------------

Top.Science.Space.Astronomy

Top.Science.Space.Astronomy.Astrophysics

Top.Science.Space.Astronomy.Cosmology

(3 rows)

We could simplify this by creating a SQL function that inserts a label at a speciﬁed position in a path:

CREATE FUNCTION ins_label(ltree, int, text) RETURNS ltree

AS ’select subpath($1,0,$2) || $3 || subpath($1,$2);’

LANGUAGE SQL IMMUTABLE;

ltreetest=> SELECT ins_label(path,2,’Space’) FROM test WHERE path <@ ’Top.Science.Astronomy’;

ins_label

------------------------------------------

Top.Science.Space.Astronomy

Top.Science.Space.Astronomy.Astrophysics

Top.Science.Space.Astronomy.Cosmology

(3 rows)

F.21.5. Authors

All work was done by Teodor Sigaev (<

teodor@stack.net

>) and Oleg Bartunov

oleg@sai.msu.su

>). See

http://www.sai.msu.su/~megera/postgres/gist/ for additional

information. Authors would like to thank Eugeny Rodichev for helpful discussions. Comments and

bug reports are welcome.

F.22. pageinspect

The

pageinspect

module provides functions thatallowyoutoinspectthe contents of database pages

at a low level, which is useful for debugging purposes. All of these functions may be used only by

superusers.

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