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.
A label is a sequence of alphanumeric characters
and underscores (for example, in C locale the characters
A-Za-z0-9_
are allowed). Labels must be less than 256 bytes
long.
Examples: 42
, Personal_Services
A label path is a sequence of zero or more
labels separated by dots, for example L1.L2.L3
, representing
a path from the root of a hierarchical tree 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 pathfoo
*.foo.* Match any label path containing the labelfoo
*.foo Match any label path whose last label isfoo
Star symbols can also be quantified to restrict how many labels they can match:
*{n
} Match exactlyn
labels *{n
,} Match at leastn
labels *{n
,m
} Match at leastn
but not more thanm
labels *{,m
} Match at mostm
labels — same as *{0,m
}
There are several modifiers that can be put at the end of a non-star
label in lquery
to make it match more than just the exact match:
@ Match case-insensitively, for examplea@
matchesA
* Match any label with this prefix, for examplefoo*
matchesfoobar
% Match initial underscore-separated words
The behavior of %
is a bit complicated. It tries to match
words rather than the entire label. For example
foo_bar%
matches foo_bar_baz
but not
foo_barbaz
. If combined with *
, prefix
matching 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 a. b. c. d. e.
This query will match any label path that:
begins with the label Top
and next has zero to two labels before
a label beginning with the case-insensitive prefix sport
then a label not matching football
nor
tennis
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 can be combined with &
(AND),
|
(OR), !
(NOT), and parentheses.
The key difference from
lquery
is that ltxtquery
matches words without
regard to their 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 word can be matched to any
underscore-separated word within a label, regardless of position.
Note: ltxtquery
allows whitespace between symbols, but
ltree
and lquery
do not.
Type ltree
has the usual comparison operators
=
, <>
,
<
, >
, <=
, >=
.
Comparison sorts in the order of a tree traversal, with the children
of a node sorted by label text. In addition, the specialized
operators shown in Table F.14 are available.
Table F.14. 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 ? |
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 of ltree ? |
ltree <@ ltree[] | boolean | does array contain an ancestor of ltree ? |
ltree[] <@ ltree | boolean | does array contain a descendant of ltree ? |
ltree @> ltree[] | boolean | does array contain a descendant of 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.
The available functions are shown in Table F.15.
Table F.15. ltree
Functions
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.
This example uses the following data (also available in file
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:
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@'; 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)
Additional extensions are available that implement transforms for
the ltree
type for PL/Python. The extensions are
called ltree_plpythonu
, ltree_plpython2u
,
and ltree_plpython3u
(see Section 45.1 for the PL/Python naming
convention). If you install these transforms and specify them when
creating a function, ltree
values are mapped to Python lists.
(The reverse is currently not supported, however.)
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.