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71e1f531d3
ltree_73.patch.gz - for 7.3 : Fix ~ operation bug: eg '1.1.1' ~ '*.1' ltree_74.patch.gz - for current CVS Fix ~ operation bug: eg '1.1.1' ~ '*.1' Add ? operation Optimize index storage Last change needs drop/create all ltree indexes, so only for 7.4 Teodor Sigaev
493 lines
18 KiB
Plaintext
493 lines
18 KiB
Plaintext
contrib/ltree module
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ltree - is a PostgreSQL contrib module which contains implementation of data
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types, indexed access methods and queries for data organized as a tree-like
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structures.
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This module will works for PostgreSQL version 7.3.
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(version for 7.2 version is available from http://www.sai.msu.su/~megera/postgres/gist/ltree/ltree-7.2.tar.gz)
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-------------------------------------------------------------------------------
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All work was done by Teodor Sigaev (teodor@stack.net) and Oleg Bartunov
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(oleg@sai.msu.su). See http://www.sai.msu.su/~megera/postgres/gist for
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additional information. Authors would like to thank Eugeny Rodichev for helpful
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discussions. Comments and bug reports are welcome.
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-------------------------------------------------------------------------------
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LEGAL NOTICES: This module is released under BSD license (as PostgreSQL
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itself). This work was done in framework of Russian Scientific Network and
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partially supported by Russian Foundation for Basic Research and Stack Group.
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-------------------------------------------------------------------------------
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MOTIVATION
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This is a placeholder for introduction to the problem. Hope, people reading
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this document doesn't need it too much :-)
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DEFINITIONS
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A label of a node is a sequence of one or more words separated by blank
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character '_' and containing letters and digits ( for example, [a-zA-Z0-9] for
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C locale). The length of a label is limited by 256 bytes.
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Example: 'Countries', 'Personal_Services'
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A label path of a node is a sequence of one or more dot-separated labels
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l1.l2...ln, represents path from root to the node. The length of a label path
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is limited by 65Kb, but size <= 2Kb is preferrable. We consider it's not a
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strict limitation ( maximal size of label path for DMOZ catalogue - http://
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www.dmoz.org, is about 240 bytes !)
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Example: 'Top.Countries.Europe.Russia'
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We introduce several datatypes:
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ltree
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- is a datatype for label path.
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ltree[]
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- is a datatype for arrays of ltree.
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lquery
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- is a path expression that has regular expression in the label path and
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used for ltree matching. Star symbol (*) is used to specify any number of
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labels (levels) and could be used at the beginning and the end of lquery,
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for example, '*.Europe.*'.
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The following quantifiers are recognized for '*' (like in Perl):
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{n} Match exactly n levels
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{n,} Match at least n levels
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{n,m} Match at least n but not more than m levels
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{,m} Match at maximum m levels (eq. to {0,m})
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It is possible to use several modifiers at the end of a label:
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@ Do case-insensitive label matching
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* Do prefix matching for a label
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% Don't account word separator '_' in label matching, that is
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'Russian%' would match 'Russian_nations', but not 'Russian'
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lquery could contains logical '!' (NOT) at the beginning of the label and '
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|' (OR) to specify possible alternatives for label matching.
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Example of lquery:
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Top.*{0,2}.sport*@.!football|tennis.Russ*|Spain
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a) b) c) d) e)
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A label path should
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+ a) begins from a node with label 'Top'
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+ b) and following zero or 2 labels until
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+ c) a node with label beginning from case-insensitive prefix 'sport'
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+ d) following node with label not matched 'football' or 'tennis' and
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+ e) ends on node with label beginning from 'Russ' or strictly matched
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'Spain'.
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ltxtquery
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- is a datatype for label searching (like type 'query' for full text
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searching, see contrib/tsearch). It's possible to use modifiers @,%,* at
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the end of word. The meaning of modifiers are the same as for lquery.
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Example: 'Europe & Russia*@ & !Transportation'
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Search paths contain words 'Europe' and 'Russia*' (case-insensitive) and
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not 'Transportation'. Notice, the order of words as they appear in label
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path is not important !
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OPERATIONS
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The following operations are defined for type ltree:
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<,>,<=,>=,=, <>
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- have their usual meanings. Comparison is doing in the order of direct
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tree traversing, children of a node are sorted lexicographic.
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ltree @> ltree
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- returns TRUE if left argument is an ancestor of right argument (or
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equal).
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ltree <@ ltree
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- returns TRUE if left argument is a descendant of right argument (or
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equal).
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ltree ~ lquery, lquery ~ ltree
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- return TRUE if node represented by ltree satisfies lquery.
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ltree ? lquery[], lquery ? ltree[]
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- return TRUE if node represented by ltree satisfies at least one lquery
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from array.
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ltree @ ltxtquery, ltxtquery @ ltree
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- return TRUE if node represented by ltree satisfies ltxtquery.
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ltree || ltree, ltree || text, text || ltree
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- return concatenated ltree.
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Operations for arrays of ltree (ltree[]):
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ltree[] @> ltree, ltree <@ ltree[]
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- returns TRUE if array ltree[] contains an ancestor of ltree.
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ltree @> ltree[], ltree[] <@ ltree
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- returns TRUE if array ltree[] contains a descendant of ltree.
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ltree[] ~ lquery, lquery ~ ltree[]
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- returns TRUE if array ltree[] contains label paths matched lquery.
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ltree[] ? lquery[], lquery[] ? ltree[]
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- returns TRUE if array ltree[] contains label paths matched atleaset one
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lquery from array.
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ltree[] @ ltxtquery, ltxtquery @ ltree[]
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- returns TRUE if array ltree[] contains label paths matched ltxtquery
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(full text search).
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ltree[] ?@> ltree, ltree ?<@ ltree[], ltree[] ?~ lquery, ltree[] ?@ ltxtquery
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- returns first element of array ltree[] satisfies corresponding condition
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and NULL in vice versa.
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REMARK
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Operations <@, @>, @ and ~ have analogues - ^<@, ^@>, ^@, ^~, which doesn't use
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indices !
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INDICES
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Various indices could be created to speed up execution of operations:
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* B-tree index over ltree:
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<, <=, =, =>, >
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* GiST index over ltree:
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<, <=, =, =>, >, @>, <@, @, ~, ?
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Example:
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create index path_gist_idx on test using gist (path);
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* GiST index over ltree[]:
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ltree[]<@ ltree, ltree @> ltree[], @, ~, ?.
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Example:
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create index path_gist_idx on test using gist (array_path);
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Notices: This index is lossy.
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FUNCTIONS
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ltree subltree
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ltree subltree(ltree, start, end)
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returns subpath of ltree from start (inclusive) until the end.
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# select subltree('Top.Child1.Child2',1,2);
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subltree
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--------
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Child1
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ltree subpath
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ltree subpath(ltree, OFFSET,LEN)
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ltree subpath(ltree, OFFSET)
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returns subpath of ltree from OFFSET (inclusive) with length LEN.
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If OFFSET is negative returns subpath starts that far from the end
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of the path. If LENGTH is omitted, returns everything to the end
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of the path. If LENGTH is negative, leaves that many labels off
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the end of the path.
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# select subpath('Top.Child1.Child2',1,2);
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subpath
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-------
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Child1.Child2
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# select subpath('Top.Child1.Child2',-2,1);
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subpath
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---------
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Child1
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int4 nlevel
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int4 nlevel(ltree) - returns level of the node.
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# select nlevel('Top.Child1.Child2');
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nlevel
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--------
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3
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Note, that arguments start, end, OFFSET, LEN have meaning of level of the
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node !
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ltree lca(ltree,ltree,...) (up to 8 arguments)
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ltree lca(ltree[])
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Returns Lowest Common Ancestor (lca)
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# select lca('1.2.2.3','1.2.3.4.5.6');
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lca
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-----
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1.2
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# select lca('{la.2.3,1.2.3.4.5.6}') is null;
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?column?
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----------
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f
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INSTALLATION
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cd contrib/ltree
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make
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make install
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make installcheck
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EXAMPLE OF USAGE
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createdb ltreetest
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psql ltreetest < /usr/local/pgsql/share/contrib/ltree.sql
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psql ltreetest < ltreetest.sql
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Now, we have a database ltreetest populated with a data describing hierarchy
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shown below:
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TOP
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/ | \
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Science Hobbies Collections
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/ | \
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Astronomy Amateurs_Astronomy Pictures
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/ \ |
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Astrophysics Cosmology Astronomy
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/ | \
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Galaxies Stars Astronauts
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Inheritance:
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ltreetest=# select path from test where path <@ 'Top.Science';
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path
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------------------------------------
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Top.Science
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Top.Science.Astronomy
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Top.Science.Astronomy.Astrophysics
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Top.Science.Astronomy.Cosmology
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(4 rows)
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Matching:
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ltreetest=# select path from test where path ~ '*.Astronomy.*';
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path
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-----------------------------------------------
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Top.Science.Astronomy
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Top.Science.Astronomy.Astrophysics
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Top.Science.Astronomy.Cosmology
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Top.Collections.Pictures.Astronomy
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Top.Collections.Pictures.Astronomy.Stars
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Top.Collections.Pictures.Astronomy.Galaxies
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Top.Collections.Pictures.Astronomy.Astronauts
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(7 rows)
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ltreetest=# select path from test where path ~ '*.!pictures@.*.Astronomy.*';
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path
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------------------------------------
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Top.Science.Astronomy
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Top.Science.Astronomy.Astrophysics
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Top.Science.Astronomy.Cosmology
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(3 rows)
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Full text search:
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ltreetest=# select path from test where path @ 'Astro*% & !pictures@';
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path
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------------------------------------
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Top.Science.Astronomy
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Top.Science.Astronomy.Astrophysics
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Top.Science.Astronomy.Cosmology
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Top.Hobbies.Amateurs_Astronomy
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(4 rows)
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ltreetest=# select path from test where path @ 'Astro* & !pictures@';
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path
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------------------------------------
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Top.Science.Astronomy
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Top.Science.Astronomy.Astrophysics
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Top.Science.Astronomy.Cosmology
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(3 rows)
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Using Functions:
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ltreetest=# select subpath(path,0,2)||'Space'||subpath(path,2) from test where path <@ 'Top.Science.Astronomy';
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?column?
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------------------------------------------
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Top.Science.Space.Astronomy
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Top.Science.Space.Astronomy.Astrophysics
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Top.Science.Space.Astronomy.Cosmology
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(3 rows)
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We could create SQL-function:
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CREATE FUNCTION ins_label(ltree, int4, text) RETURNS ltree
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AS 'select subpath($1,0,$2) || $3 || subpath($1,$2);'
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LANGUAGE SQL WITH (ISCACHABLE);
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and previous select could be rewritten as:
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ltreetest=# select ins_label(path,2,'Space') from test where path <@ 'Top.Science.Astronomy';
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ins_label
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------------------------------------------
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Top.Science.Space.Astronomy
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Top.Science.Space.Astronomy.Astrophysics
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Top.Science.Space.Astronomy.Cosmology
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(3 rows)
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Or with another arguments:
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CREATE FUNCTION ins_label(ltree, ltree, text) RETURNS ltree
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AS 'select subpath($1,0,nlevel($2)) || $3 || subpath($1,nlevel($2));'
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LANGUAGE SQL WITH (ISCACHABLE);
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ltreetest=# select ins_label(path,'Top.Science'::ltree,'Space') from test where path <@ 'Top.Science.Astronomy';
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ins_label
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------------------------------------------
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Top.Science.Space.Astronomy
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Top.Science.Space.Astronomy.Astrophysics
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Top.Science.Space.Astronomy.Cosmology
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(3 rows)
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ADDITIONAL DATA
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To get more feeling from our ltree module you could download
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dmozltree-eng.sql.gz (about 3Mb tar.gz archive containing 300,274 nodes),
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available from http://www.sai.msu.su/~megera/postgres/gist/ltree/
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dmozltree-eng.sql.gz, which is DMOZ catalogue, prepared for use with ltree.
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Setup your test database (dmoz), load ltree module and issue command:
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zcat dmozltree-eng.sql.gz| psql dmoz
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Data will be loaded into database dmoz and all indices will be created.
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BENCHMARKS
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All runs were performed on my IBM ThinkPad T21 (256 MB RAM, 750Mhz) using DMOZ
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data, containing 300,274 nodes (see above for download link). We used some
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basic queries typical for walking through catalog.
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QUERIES
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* Q0: Count all rows (sort of base time for comparison)
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select count(*) from dmoz;
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count
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--------
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300274
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(1 row)
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* Q1: Get direct children (without inheritance)
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select path from dmoz where path ~ 'Top.Adult.Arts.Animation.*{1}';
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path
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-----------------------------------
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Top.Adult.Arts.Animation.Cartoons
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Top.Adult.Arts.Animation.Anime
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(2 rows)
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* Q2: The same as Q1 but with counting of successors
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select path as parentpath , (select count(*)-1 from dmoz where path <@
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p.path) as count from dmoz p where path ~ 'Top.Adult.Arts.Animation.*{1}';
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parentpath | count
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-----------------------------------+-------
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Top.Adult.Arts.Animation.Cartoons | 2
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Top.Adult.Arts.Animation.Anime | 61
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(2 rows)
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* Q3: Get all parents
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select path from dmoz where path @> 'Top.Adult.Arts.Animation' order by
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path asc;
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path
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--------------------------
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Top
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Top.Adult
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Top.Adult.Arts
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Top.Adult.Arts.Animation
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(4 rows)
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* Q4: Get all parents with counting of children
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select path, (select count(*)-1 from dmoz where path <@ p.path) as count
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from dmoz p where path @> 'Top.Adult.Arts.Animation' order by path asc;
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path | count
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--------------------------+--------
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Top | 300273
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Top.Adult | 4913
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Top.Adult.Arts | 339
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Top.Adult.Arts.Animation | 65
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(4 rows)
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* Q5: Get all children with levels
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select path, nlevel(path) - nlevel('Top.Adult.Arts.Animation') as level
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from dmoz where path ~ 'Top.Adult.Arts.Animation.*{1,2}' order by path asc;
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path | level
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------------------------------------------------+-------
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Top.Adult.Arts.Animation.Anime | 1
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Top.Adult.Arts.Animation.Anime.Fan_Works | 2
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Top.Adult.Arts.Animation.Anime.Games | 2
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Top.Adult.Arts.Animation.Anime.Genres | 2
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Top.Adult.Arts.Animation.Anime.Image_Galleries | 2
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Top.Adult.Arts.Animation.Anime.Multimedia | 2
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Top.Adult.Arts.Animation.Anime.Resources | 2
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Top.Adult.Arts.Animation.Anime.Titles | 2
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Top.Adult.Arts.Animation.Cartoons | 1
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Top.Adult.Arts.Animation.Cartoons.AVS | 2
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Top.Adult.Arts.Animation.Cartoons.Members | 2
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(11 rows)
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Timings
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+---------------------------------------------+
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|Query|Rows|Time (ms) index|Time (ms) no index|
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|-----+----+---------------+------------------|
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| Q0| 1| NA| 1453.44|
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|-----+----+---------------+------------------|
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| Q1| 2| 0.49| 1001.54|
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|-----+----+---------------+------------------|
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| Q2| 2| 1.48| 3009.39|
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|-----+----+---------------+------------------|
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| Q3| 4| 0.55| 906.98|
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|-----+----+---------------+------------------|
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| Q4| 4| 24385.07| 4951.91|
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|-----+----+---------------+------------------|
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| Q5| 11| 0.85| 1003.23|
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+---------------------------------------------+
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Timings without indices were obtained using operations which doesn't use
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indices (see above)
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Remarks
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We didn't run full-scale tests, also we didn't present (yet) data for
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operations with arrays of ltree (ltree[]) and full text searching. We'll
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appreciate your input. So far, below some (rather obvious) results:
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* Indices does help execution of queries
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* Q4 performs bad because one needs to read almost all data from the HDD
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CHANGES
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Feb 7, 2003
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Add ? operation
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Fix ~ operation bug: eg '1.1.1' ~ '*.1'
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Optimize index storage
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Aug 9, 2002
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Fixed very stupid but important bug :-)
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July 31, 2002
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Now works on 64-bit platforms.
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Added function lca - lowest common ancestor
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Version for 7.2 is distributed as separate package -
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http://www.sai.msu.su/~megera/postgres/gist/ltree/ltree-7.2.tar.gz
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July 13, 2002
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Initial release.
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TODO
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* Testing on 64-bit platforms. There are several known problems with byte
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alignment; -- RESOLVED
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* Better documentation;
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* We plan (probably) to improve regular expressions processing using
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non-deterministic automata;
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* Some sort of XML support;
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* Better full text searching;
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SOME BACKGROUNDS
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The approach we use for ltree is much like one we used in our other GiST based
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contrib modules (intarray, tsearch, tree, btree_gist, rtree_gist). Theoretical
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background is available in papers referenced from our GiST development page
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(http://www.sai.msu.su/~megera/postgres/gist).
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A hierarchical data structure (tree) is a set of nodes. Each node has a
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signature (LPS) of a fixed size, which is a hashed label path of that node.
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Traversing a tree we could *certainly* prune branches if
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LQS (bitwise AND) LPS != LQS
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where LQS is a signature of lquery or ltxtquery, obtained in the same way as
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LPS.
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ltree[]:
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For array of ltree LPS is a bitwise OR-ed signatures of *ALL* children
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reachable from that node. Signatures are stored in RD-tree, implemented using
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GiST, which provides indexed access.
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ltree:
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For ltree we store LPS in a B-tree, implemented using GiST. Each node entry is
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represented by (left_bound, signature, right_bound), so that we could speedup
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operations <, <=, =, =>, > using left_bound, right_bound and prune branches of
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a tree using signature.
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-------------------------------------------------------------------------------
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We ask people who find the module useful to send us a postcards to:
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Moscow, 119899, Universitetski pr.13, Moscow State University, Sternberg
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Astronomical Institute, Russia
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For: Bartunov O.S.
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and
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Moscow, Bratislavskaya str.23, appt. 18, Russia
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For: Sigaev F.G.
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