Installation might be a bit tricky - the underlying library is written
in C++. If problems occur (Tree::M is configured for linux, i.e. an
ELF-system using g++ and gcc) you need to change CXX in the Makefile.PL
and/or hack the GiST/Makefile and MT/Makefile themselves.
=============================================================================
NAME
Tree::M - implement M-trees for efficient "metric/multimedia-searches"
SYNOPSIS
use Tree::M;
$M = new Tree::M
DESCRIPTION
(not yet)
Ever had the problem of managing multi-dimensional (spatial) data but
your database only had one-dimensional indices (b-tree etc.)? Queries
like
select data from table where latitude > 40 and latitude < 50
and longitude> 50 and longitude< 60;
are quite inefficient, unless longitude and latitude are part of the
same spatial index (e.g. an R-tree).
An M-tree is an index tree that does not directly look at the stored
keys but rather requires a *distance* (a metric, e.g. a vector norm)
function to be defined that sorts keys according to their distance. In
the example above the distance function could be the maximum norm
("max(x1-x2, y1-y2)"). The lookup above would then be something like
this:
my $res = $M->range([45,55], 5);
This module implements an M-tree. Although the data structure and the
distance function is arbitrary, the current version only implements
n-dimensional discrete vectors and hardwires the distance function to
the suared euclidean metric (i.e. "(x1-x2)**2 + (y1-y2)**2 + (z1-z2)**2
+ ..."). Evolution towards more freedom is expected ;)
THE Tree::M CLASS
$M = new Tree::M arg => value, ...
Creates a new M-Tree. Before it can be used you have to call one of
the "create" or "open" methods below.
ndims => integer
the number of dimensions each vector has
range => [min, max, steps]
min the lowest allowable scalar value in each dimension
max the maximum allowable number
steps the number of discrete steps (used when stored externally)
pagesize => integer
the size of one page on underlying storage. usually 4096, but
large objects (ndims > 20 or so) might want to increase this
Example: create an M-Tree that stores 8-bit rgb-values:
$M = new Tree::M ndims => 3, range => [0, 255, 256];
Example: create an M-Tree that stores coordinates from -1..1 with
100 different steps:
$M = new Tree::M ndims => 2, range => [-1, 1, 100];
$M->open(path)
$M->create($path)
Open or create the external storage file $path and associate it with
the tree.
[this braindamaged API will go away ;)]
$M->insert(\@v, $data)
Insert a vector (given by an array reference) into the index and
associate it with the value $data (a 32-bit integer).
$M->sync
Synchronize the data file with memory. Useful after calling "insert"
to ensure the data actually reaches stable storage.
$res = $M->range(\@v, $radius)
Search all entries not farther away from @v then $radius and return
an arrayref containing the searchresults.
Each result is again anarrayref composed like this:
[\@v, $data]
e.g. the same as given to the "insert" method.
$res = $M->top(\@v, $n)
Return the $n "nearest neighbours". The results arrayref (see
"range") contains the $n index values nearest to @v, sorted for
distance.
$distance = $M->distance(\@v1, \@v2)
Calculcate the distance between two vectors, just as they databse
engine would do it.
$depth = $M->maxlevel
Return the maximum height of the tree (usually a small integer
specifying the length of the path from the root to the farthest
leaf)
BUGS
Inserting too many duplicate keys into the tree cause the C++ library to
die, so don't do that.
AUTHOR
Marc Lehmann <
[email protected]>.
SEE ALSO
perl(1), DBIx::SpatialKeys.
