This directory contains an SQLite extension that implements a virtual
table type that allows users to create, query and manipulate r-tree[1]
data structures inside of SQLite databases. Users create, populate
and query r-tree structures using ordinary SQL statements.
1. SQL Interface
1.1 Table Creation
1.2 Data Manipulation
1.3 Data Querying
1.4 Introspection and Analysis
2. Compilation and Deployment
3. References
1. SQL INTERFACE
1.1 Table Creation.
All r-tree virtual tables have an odd number of columns between
3 and 11. Unlike regular SQLite tables, r-tree tables are strongly
typed.
The leftmost column is always the pimary key and contains 64-bit
integer values. Each subsequent column contains a 32-bit real
value. For each pair of real values, the first (leftmost) must be
less than or greater than the second. R-tree tables may be
constructed using the following syntax:
CREATE VIRTUAL TABLE <name> USING rtree(<column-names>)
For example:
CREATE VIRTUAL TABLE boxes USING rtree(boxno, xmin, xmax, ymin, ymax);
INSERT INTO boxes VALUES(1, 1.0, 3.0, 2.0, 4.0);
Constructing a virtual r-tree table <name> creates the following three
real tables in the database to store the data structure:
<name>_node
<name>_rowid
<name>_parent
Dropping or modifying the contents of these tables directly will
corrupt the r-tree structure. To delete an r-tree from a database,
use a regular DROP TABLE statement:
DROP TABLE <name>;
Dropping the main r-tree table automatically drops the automatically
created tables.
1.2 Data Manipulation (INSERT, UPDATE, DELETE).
The usual INSERT, UPDATE or DELETE syntax is used to manipulate data
stored in an r-tree table. Please note the following:
* Inserting a NULL value into the primary key column has the
same effect as inserting a NULL into an INTEGER PRIMARY KEY
column of a regular table. The system automatically assigns
an unused integer key value to the new record. Usually, this
is one greater than the largest primary key value currently
present in the table.
* Attempting to insert a duplicate primary key value fails with
an SQLITE_CONSTRAINT error.
* Attempting to insert or modify a record such that the value
stored in the (N*2)th column is greater than that stored in
the (N*2+1)th column fails with an SQLITE_CONSTRAINT error.
* When a record is inserted, values are always converted to
the required type (64-bit integer or 32-bit real) as if they
were part of an SQL CAST expression. Non-numeric strings are
converted to zero.
1.3 Queries.
R-tree tables may be queried using all of the same SQL syntax supported
by regular tables. However, some query patterns are more efficient
than others.
R-trees support fast lookup by primary key value (O(logN), like
regular tables).
Any combination of equality and range (<, <=, >, >=) constraints
on spatial data columns may be used to optimize other queries. This
is the key advantage to using r-tree tables instead of creating
indices on regular tables.
1.4 Introspection and Analysis.
TODO: Describe rtreenode() and rtreedepth() functions.
2. COMPILATION AND USAGE
The easiest way to compile and use the RTREE extension is to build
and use it as a dynamically loadable SQLite extension. To do this
using gcc on *nix:
gcc -shared rtree.c -o libSqliteRtree.so
You may need to add "-I" flags so that gcc can find sqlite3ext.h
and sqlite3.h. The resulting shared lib, libSqliteRtree.so, may be
loaded into sqlite in the same way as any other dynamicly loadable
extension.
3. REFERENCES
[1] Atonin Guttman, "R-trees - A Dynamic Index Structure For Spatial
Searching", University of California Berkeley, 1984.
[2] Norbert Beckmann, Hans-Peter Kriegel, Ralf Schneider, Bernhard Seeger,
"The R*-tree: An Efficient and Robust Access Method for Points and
Rectangles", Universitaet Bremen, 1990.
