contrib/ltree module ltree - is a PostgreSQL contrib module which contains implementation of data types, indexed access methods and queries for data organized as a tree-like structures. This module will works for PostgreSQL version 7.3. (patch for 7.2 version is provided, see INSTALLATION) ------------------------------------------------------------------------------- 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. ------------------------------------------------------------------------------- LEGAL NOTICES: This module is released under BSD license (as PostgreSQL itself). This work was done in framework of Russian Scientific Network and partially supported by Russian Foundation for Basic Research and Stack Group. ------------------------------------------------------------------------------- MOTIVATION This is a placeholder for introduction to the problem. Hope, people reading this document doesn't need it too much :-) DEFINITIONS A label of a node is a sequence of one or more words separated by blank character '_' and containing letters and digits ( for example, [a-zA-Z0-9] for C locale). The length of a label is limited by 256 bytes. Example: 'Countries', 'Personal_Services' A label path of a node is a sequence of one or more dot-separated labels l1.l2...ln, represents path from root to the node. The length of a label path is limited by 65Kb, but size <= 2Kb is preferrable. We consider it's not a strict limitation ( maximal size of label path for DMOZ catalogue - http:// www.dmoz.org, is about 240 bytes !) Example: 'Top.Countries.Europe.Russia' We introduce several datatypes: ltree - is a datatype for label path. ltree[] - is a datatype for arrays of ltree. lquery - is a path expression that has regular expression in the label path and used for ltree matching. Star symbol (*) is used to specify any number of labels (levels) and could be used at the beginning and the end of lquery, for example, '*.Europe.*'. The following quantifiers are recognized for '*' (like in Perl): {n} Match exactly n levels {n,} Match at least n levels {n,m} Match at least n but not more than m levels {,m} Match at maximum m levels (eq. to {0,m}) It is possible to use several modifiers at the end of a label: @ Do case-insensitive label matching * Do prefix matching for a label % Don't account word separator '_' in label matching, that is 'Russian%' would match 'Russian_nations', but it's not true for 'Russian'. lquery could contains logical '!' (NOT) at the beginning of the label and ' |' (OR) to specify possible alternatives for label matching. Example of lquery: Top.*{0,2}.sport*@.!football|tennis.Russ*|Spain a) b) c) d) e) A label path should + a) begins from a node with label 'Top' + b) and following zero or 2 labels until + c) a node with label beginning from case-insensitive prefix 'sport' + d) following node with label not matched 'football' or 'tennis' and + e) ends on node with label beginning from 'Russ' or strictly matched 'Spain'. ltxtquery - is a datatype for label searching (like type 'query' for full text searching, see contrib/tsearch). It's possible to use modifiers @,%,* at the end of word. The meaning of modifiers are the same as for lquery. Example: 'Europe & Russia*@ & !Transportation' Search paths contain words 'Europe' and 'Russia*' (case-insensitive) and not 'Transportation'. Notice, the order of words as they appear in label path is not important ! OPERATIONS The following operations are defined for type ltree: <,>,<=,>=,=, <> - have their usual meanings. Comparison is doing in the order of direct tree traversing, children of a node are sorted lexicographic. ltree @> ltree - returns TRUE if left argument is an ancestor of right argument (or equal). ltree <@ ltree - returns TRUE if left argument is a descendant of right argument (or equal). ltree ~ lquery, lquery ~ ltree - return TRUE if node represented by ltree satisfies lquery. ltree @ ltxtquery, ltxtquery @ ltree - return TRUE if node represented by ltree satisfies ltxtquery. ltree || ltree, ltree || text, text || ltree - return concatenated ltree. Operations for arrays of ltree (ltree[]): ltree[] @> ltree, ltree <@ ltree[] - returns TRUE if array ltree[] contains an ancestor of ltree. ltree @> ltree[], ltree[] <@ ltree - returns TRUE if array ltree[] contains a descendant of ltree. ltree[] ~ lquery, lquery ~ ltree[] - returns TRUE if array ltree[] contains label paths matched lquery. ltree[] @ ltxtquery, ltxtquery @ ltree[] - returns TRUE if array ltree[] contains label paths matched ltxtquery (full text search). ltree[] ?@> ltree, ltree ?<@ ltree[], ltree[] ?~ lquery, ltree[] ?@ ltxtquery - returns first element of array ltree[] satisfies corresponding condition and NULL in vice versa. REMARK Operations <@, @>, @ and ~ have analogues - ^<@, ^@>, ^@, ^~, which doesn't use indices ! INDICES Various indices could be created to speed up execution of operations: * B-tree index over ltree: <, <=, =, =>, > * GiST index over ltree: <, <=, =, =>, >, @>, <@, @, ~ Example: create index path_gist_idx on test using gist_ltree_ops (path); * GiST index over ltree[]: ltree[]<@ ltree, ltree @> ltree[], @, ~. Example: create index path_gist_idx on test using gist__ltree_ops (path); Notices: This index is lossy. FUNCTIONS ltree subltree ltree subltree(ltree, start, end) returns subpath of ltree from start (inclusive) until the end. # select subltree('Top.Child1.Child2',1,2); subltree -------- Child1 ltree subpath ltree subpath(ltree, OFFSET,LEN) ltree subpath(ltree, OFFSET) returns subpath of ltree from OFFSET (inclusive) with length LEN. If OFFSET is negative returns subpath starts that far from the end of the path. If LENGTH is omitted, returns everything to the end of the path. If LENGTH is negative, leaves that many labels off the end of the path. # select subpath('Top.Child1.Child2',1,2); subpath ------- Child1.Child2 # select subpath('Top.Child1.Child2',-2,1); subpath --------- Child1 int4 nlevel int4 nlevel(ltree) - returns level of the node. # select nlevel('Top.Child1.Child2'); nlevel -------- 3 Note, that arguments start, end, OFFSET, LEN have meaning of level of the node ! INSTALLATION cd contrib/ltree make make install make installcheck for 7.2 one needs to apply patch ( patch < patch.72) before installation ! EXAMPLE OF USAGE createdb ltreetest psql ltreetest < /usr/local/pgsql/share/contrib/ltree.sql psql ltreetest < ltreetest.sql Now, we have a database ltreetest populated with a data describing hierarchy shown below: TOP / | \ Science Hobbies Collections / | \ Astronomy Amateurs_Astronomy Pictures / \ | Astrophysics Cosmology Astronomy / | \ Galaxies Stars Astronauts 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) 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) 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) 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 create SQL-function: CREATE FUNCTION ins_label(ltree, int4, text) RETURNS ltree AS 'select subpath($1,0,$2) || $3 || subpath($1,$2);' LANGUAGE SQL WITH (ISCACHABLE); and previous select could be rewritten as: 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) Or with another arguments: CREATE FUNCTION ins_label(ltree, ltree, text) RETURNS ltree AS 'select subpath($1,0,nlevel($2)) || $3 || subpath($1,nlevel($2));' LANGUAGE SQL WITH (ISCACHABLE); ltreetest=# select ins_label(path,'Top.Science'::ltree,'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 DATA To get more feeling from our ltree module you could download dmozltree-eng.sql.gz (about 3Mb tar.gz archive containing 300,274 nodes), available from http://www.sai.msu.su/~megera/postgres/gist/ltree/ dmozltree-eng.sql.gz, which is DMOZ catalogue, prepared for use with ltree. Setup your test database (dmoz), load ltree module and issue command: zcat dmozltree-eng.sql.gz| psql dmoz Data will be loaded into database dmoz and all indices will be created. BENCHMARKS All runs were performed on my IBM ThinkPad T21 (256 MB RAM, 750Mhz) using DMOZ data, containing 300,274 nodes (see above for download link). QUERIES * Q0: Count all rows (soft of base time for comparison) select count(*) from dmoz; count -------- 300274 (1 row) * Q1: Get direct children (without inheritance) select path from dmoz where path ~ 'Top.Adult.Arts.Animation.*{1}'; path ----------------------------------- Top.Adult.Arts.Animation.Cartoons Top.Adult.Arts.Animation.Anime (2 rows) * Q2: The same as Q1 but with counting of successors select path as parentpath , (select count(*)-1 from dmoz where path <@ p.path) as count from dmoz p where path ~ 'Top.Adult.Arts.Animation.*{1}'; parentpath | count -----------------------------------+------- Top.Adult.Arts.Animation.Cartoons | 2 Top.Adult.Arts.Animation.Anime | 61 (2 rows) * Q3: Get all parents select path from dmoz where path @> 'Top.Adult.Arts.Animation' order by path asc; path -------------------------- Top Top.Adult Top.Adult.Arts Top.Adult.Arts.Animation (4 rows) * Q4: Get all parents with counting of children select path, (select count(*)-1 from dmoz where path <@ p.path) as count from dmoz p where path @> 'Top.Adult.Arts.Animation' order by path asc; path | count --------------------------+-------- Top | 300273 Top.Adult | 4913 Top.Adult.Arts | 339 Top.Adult.Arts.Animation | 65 (4 rows) * Q5: Get all children with levels select path, nlevel(path) - nlevel('Top.Adult.Arts.Animation') as level from dmoz where path ~ 'Top.Adult.Arts.Animation.*{1,2}' order by path asc; path | level ------------------------------------------------+------- Top.Adult.Arts.Animation.Anime | 1 Top.Adult.Arts.Animation.Anime.Fan_Works | 2 Top.Adult.Arts.Animation.Anime.Games | 2 Top.Adult.Arts.Animation.Anime.Genres | 2 Top.Adult.Arts.Animation.Anime.Image_Galleries | 2 Top.Adult.Arts.Animation.Anime.Multimedia | 2 Top.Adult.Arts.Animation.Anime.Resources | 2 Top.Adult.Arts.Animation.Anime.Titles | 2 Top.Adult.Arts.Animation.Cartoons | 1 Top.Adult.Arts.Animation.Cartoons.AVS | 2 Top.Adult.Arts.Animation.Cartoons.Members | 2 (11 rows) Timings +---------------------------------------------+ |Query|Rows|Time (ms) index|Time (ms) no index| |-----+----+---------------+------------------| | Q0| 1| NA| 1453.44| |-----+----+---------------+------------------| | Q1| 2| 0.49| 1001.54| |-----+----+---------------+------------------| | Q2| 2| 9.42| 16669.24| |-----+----+---------------+------------------| | Q3| 4| 0.55| 906.98| |-----+----+---------------+------------------| | Q4| 4| 3523.65| 4951.91| |-----+----+---------------+------------------| | Q5| 11| 0.85| 1003.23| +---------------------------------------------+ Timings without indices were obtained using operations which doesn't use indices (see above) Remarks We didn't run full-scale tests, also we didn't present (yet) data for operations with arrays of ltree (ltree[]) and full text searching. We'll appreciate your input. So far, below some (rather obvious) results: * Indices does help execution of queries * Q4 performs bad because one needs to read almost all data from the HDD, but index is still better than without one. CHANGES July 13, 2002 Initial release. TODO * Testing on 64-bit platforms. There are several known problems with byte alignment; * Better documentation; * We plan (probably) to improve regular expressions processing using non-deterministic automata; * Some sort of XML support; * Better full text searching; SOME BACKGROUNDS The approach we use for ltree is much like one we used in our other GiST based contrib modules (intarray, tsearch, tree, btree_gist, rtree_gist). Theoretical background is available in papers referenced from our GiST development page (http://www.sai.msu.su/~megera/postgres/gist). A hierarchical data structure (tree) is a set of nodes. Each node has a signature (LPS) of a fixed size, which is a hashed label path of that node. Traversing a tree we could *certainly* prune branches if LQS (bitwise AND) LPS != LQS where LQS is a signature of lquery or ltxtquery, obtained in the same way as LPS. ltree[]: For array of ltree LPS is a bitwise OR-ed signatures of *ALL* children reachable from that node. Signatures are stored in RD-tree, implemented using GiST, which provides indexed access. ltree: For ltree we store LPS in a B-tree, implemented using GiST. Each node entry is represented by (left_bound, signature, right_bound), so that we could speedup operations <, <=, =, =>, > using left_bound, right_bound and prune branches of a tree using signature. ------------------------------------------------------------------------------- We ask people who find the module useful to send us a postcards to: Moscow, 119899, Universitetski pr.13, Moscow State University, Sternberg Astronomical Institute, Russia For: Bartunov O.S. and Moscow, Bratislavskaya str.23, appt. 18, Russia For: Sigaev F.G.