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.
This module is considered “trusted”, that is, it can be
installed by non-superusers who have CREATE
privilege
on the current database.
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 characters 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 cannot exceed 65535 labels.
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. These can be joined with dots to form a pattern that
must match the whole label path. 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
Both star symbols and simple words can 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
} foo{n
,m
} Match at leastn
but not more thanm
occurrences offoo
foo{,} Match any number of occurrences offoo
, including zero
In the absence of any explicit quantifier, the default for a star symbol
is to match any number of labels (that is, {,}
) while
the default for a non-star item is to match exactly once (that
is, {1}
).
There are several modifiers that can be put at the end of a non-star
lquery
item 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 non-star items separated with
|
(OR) to match any of those items, and you can put
!
(NOT) at the start of a non-star group to match any
label that doesn't match any of the alternatives. A quantifier, if any,
goes at the end of the group; it means some number of matches for the
group as a whole (that is, some number of labels matching or not matching
any of the alternatives).
Here's an annotated example of lquery
:
Top.*{0,2}.sport*@.!football|tennis{1,}.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 has one or more labels, none of which
match 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.25 are available.
Table F.25. ltree
Operators
Operator Description |
---|
Is left argument an ancestor of right (or equal)? |
Is left argument a descendant of right (or equal)? |
Does |
Does |
Does |
Concatenates |
Converts text to |
Does array contain an ancestor of |
Does array contain a descendant of |
Does array contain any path matching |
Does |
Does array contain any path matching |
Returns first array entry that is an ancestor of |
Returns first array entry that is a descendant of |
Returns first array entry that matches |
Returns first array entry that matches |
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.26.
Table F.26. ltree
Functions
ltree
supports several types of indexes that can speed
up the indicated operators:
B-tree index over ltree
:
<
, <=
, =
,
>=
, >
GiST index over ltree
(gist_ltree_ops
opclass):
<
, <=
, =
,
>=
, >
,
@>
, <@
,
@
, ~
, ?
gist_ltree_ops
GiST opclass approximates a set of
path labels as a bitmap signature. Its optional integer parameter
siglen
determines the
signature length in bytes. The default signature length is 8 bytes.
Valid values of signature length are between 1 and 2024 bytes. Longer
signatures lead to a more precise search (scanning a smaller fraction of the index and
fewer heap pages), at the cost of a larger index.
Example of creating such an index with the default signature length of 8 bytes:
CREATE INDEX path_gist_idx ON test USING GIST (path);
Example of creating such an index with a signature length of 100 bytes:
CREATE INDEX path_gist_idx ON test USING GIST (path gist_ltree_ops(siglen=100));
GiST index over ltree[]
(gist__ltree_ops
opclass):
ltree[] <@ ltree
, ltree @> ltree[]
,
@
, ~
, ?
gist__ltree_ops
GiST opclass works similarly to
gist_ltree_ops
and also takes signature length as
a parameter. The default value of siglen
in
gist__ltree_ops
is 28 bytes.
Example of creating such an index with the default signature length of 28 bytes:
CREATE INDEX path_gist_idx ON test USING GIST (array_path);
Example of creating such an index with a signature length of 100 bytes:
CREATE INDEX path_gist_idx ON test USING GIST (array_path gist__ltree_ops(siglen=100));
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)
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.