]> Paul Ramsey Refractions Research Inc

Suite 300, 1207 Douglas Street Victoria British Columbia Canada pramsey@refractions.net

PostGIS is an extension to the PostgreSQL object-relational database system which allows GIS (Geographic Information Systems) objects to be stored in the database. PostGIS includes support for GiST-based R-Tree spatial indexes, and functions for analysis and processing of GIS objects. This is the manual for version @@LAST_RELEASE_VERSION@@ PostGIS is developed by Refractions Research Inc, as a spatial database technology research project. Refractions is a GIS and database consulting company in Victoria, British Columbia, Canada, specializing in data integration and custom software development. We plan on supporting and developing PostGIS to support a range of important GIS functionality, including full OpenGIS support, advanced topological constructs (coverages, surfaces, networks), desktop user interface tools for viewing and editing GIS data, and web-based access tools. Sandro Santilli <strk@refractions.net> Coordinates all bug fixing and maintenance effort, integration of new GEOS functionality, and new function enhancements. Chris Hodgson <chodgson@refractions.net> Maintains new functions and the 7.2 index bindings. Paul Ramsey <pramsey@refractions.net> Keeps track of the documentation and packaging. Jeff Lounsbury <jeffloun@refractions.net> Original development of the Shape file loader/dumper. Dave Blasby <dblasby@gmail.com> The original developer of PostGIS. Dave wrote the server side objects, index bindings, and many of the server side analytical functions. Other contributors In alphabetical order: Alex Bodnaru, Alex Mayrhofer, Bruce Rindahl, Bernhard Reiter, Bruno Wolff III, Carl Anderson, Charlie Savage, David Skea, David Techer, IIDA Tetsushi, Geographic Data BC, Gerald Fenoy, Gino Lucrezi, Klaus Foerster, Kris Jurka, Mark Cave-Ayland, Mark Sondheim, Markus Schaber, Michael Fuhr, Nikita Shulga, Norman Vine, Olivier Courtin, Ralph Mason, Steffen Macke. Important Support Libraries The GEOS geometry operations library, and the algorithmic work of Martin Davis <mbdavis@vividsolutions.com> of Vivid Solutions in making it all work. The Proj4 cartographic projection library, and the work of Gerald Evenden and Frank Warmerdam in creating and maintaining it. The latest software, documentation and news items are available at the PostGIS web site, http://postgis.refractions.net. More information about the GEOS geometry operations library is available at http://geos.refractions.net. More information about the Proj4 reprojection library is available at http://www.remotesensing.org/proj. More information about the PostgreSQL database server is available at the PostgreSQL main site http://www.postgresql.org. More information about GiST indexing is available at the PostgreSQL GiST development site, http://www.sai.msu.su/~megera/postgres/gist. More information about Mapserver internet map server is available at http://mapserver.gis.umn.edu. The "Simple Features for Specification for SQL" is available at the OpenGIS Consortium web site: http://www.opengis.org. PostGIS has the following requirements for building and usage: A complete installation of PostgreSQL (including server headers). PostgreSQL is available from http://www.postgresql.org. Version 7.2 or higher is required. GNU C compiler (gcc). Some other ANSI C compilers can be used to compile PostGIS, but we find far fewer problems when compiling with gcc. GNU Make (gmake or make). For many systems, GNU make is the default version of make. Check the version by invoking make -v. Other versions of make may not process the PostGIS Makefile properly. (Recommended) Proj4 reprojection library. The Proj4 library is used to provide coordinate reprojection support within PostGIS. Proj4 is available for download from http://www.remotesensing.org/proj. (Recommended) GEOS geometry library. The GEOS library is used to provide geometry tests (Touches(), Contains(), Intersects()) and operations (Buffer(), GeomUnion(), Difference()) within PostGIS. GEOS is available for download from http://geos.refractions.net. The PostGIS module is a extension to the PostgreSQL backend server. As such, PostGIS @@LAST_RELEASE_VERSION@@ requires full PostgreSQL server headers access in order to compile. The PostgreSQL source code is available at http://www.postgresql.org. PostGIS @@LAST_RELEASE_VERSION@@ can be built against PostgreSQL versions 7.2.0 or higher. Earlier versions of PostgreSQL are not supported. Before you can compile the PostGIS server modules, you must compile and install the PostgreSQL package. If you plan to use GEOS functionality you might need to explicitly link PostgreSQL against the standard C++ library: LDFLAGS=-lstdc++ ./configure [YOUR OPTIONS HERE] This is a workaround for bogus C++ exceptions interaction with older development tools. If you experience weird problems (backend unexpectedly closed or similar things) try this trick. This will require recompiling your PostgreSQL from scratch, of course. Retrieve the PostGIS source archive from http://postgis.refractions.net/postgis-@@LAST_RELEASE_VERSION@@.tar.gz. Uncompress and untar the archive. # gzip -d -c postgis-@@LAST_RELEASE_VERSION@@.tar.gz | tar xvf - Enter the postgis-@@LAST_RELEASE_VERSION@@ directory, and run: # ./configure If you want support for coordinate reprojection, you must have the Proj4 library installed. If ./configure didn't find it, try using --with-proj=PATH switch specify a specific Proj4 installation directory. If you want to use GEOS functionality, you must have the GEOS library installed. If ./configure didn't find it, try using --with-geos=PATH to specify the full path to the geos-config program full path. Run the compile and install commands. # make # make install All files are installed using information provided by pg_config Libraries are installed [pkglibdir]/lib/contrib. Important support files such as lwpostgis.sql are installed in [prefix]/share/contrib. Loader and dumper binaries are installed in [bindir]/. PostGIS requires the PL/pgSQL procedural language extension. Before loading the lwpostgis.sql file, you must first enable PL/pgSQL. You should use the createlang command. The PostgreSQL Programmer's Guide has the details if you want to this manually for some reason. # createlang plpgsql [yourdatabase] Now load the PostGIS object and function definitions into your database by loading the lwpostgis.sql definitions file. # psql -d [yourdatabase] -f lwpostgis.sql The PostGIS server extensions are now loaded and ready to use. For a complete set of EPSG coordinate system definition identifiers, you can also load the spatial_ref_sys.sql definitions file and populate the SPATIAL_REF_SYS table. # psql -d [yourdatabase] -f spatial_ref_sys.sql Some packaged distributions of PostGIS (in particular the Win32 installers for PostGIS >= 1.1.5) load the PostGIS functions into a template database called template_postgis. If the template_postgis database exists in your PostgreSQL installation then it is possible for users and/or applications to create spatially-enabled databases using a single command. Note that in both cases, the database user must have been granted the privilege to create new databases. From the shell: # createdb -T template_postgis my_spatial_db From SQL: postgres=# CREATE DATABASE my_spatial_db TEMPLATE=template_postgis Upgrading existing spatial databases can be tricky as it requires replacement or introduction of new PostGIS object definitions. Unfortunately not all definitions can be easily replaced in a live database, so sometimes your best bet is a dump/reload process. PostGIS provides a SOFT UPGRADE procedure for minor or bugfix releases, and an HARD UPGRADE procedure for major releases. Before attempting to upgrade postgis, it is always worth to backup your data. If you use the -Fc flag to pg_dump you will always be able to restore the dump with an HARD UPGRADE. Soft upgrade consists of sourcing the lwpostgis_upgrade.sql script in your spatial database: $ psql -f lwpostgis_upgrade.sql -d your_spatial_database If a soft upgrade is not possible the script will abort and you will be warned about HARD UPGRADE being required, so do not hesitate to try a soft upgrade first. If you can't find the lwpostgis_upgrade.sql file you are probably using a version prior to 1.1 and must generate that file by yourself. This is done with the following command: $ utils/postgis_proc_upgrade.pl lwpostgis.sql > lwpostgis_upgrade.sql By HARD UPGRADE we intend full dump/reload of postgis-enabled databases. You need an HARD UPGRADE when postgis objects' internal storage changes or when SOFT UPGRADE is not possible. The Release Notes appendix reports for each version whether you need a dump/reload (HARD UPGRADE) to upgrade. PostGIS provides an utility script to restore a dump produced with the pg_dump -Fc command. It is experimental so redirecting its output to a file will help in case of problems. The procedure is as follow: Create a "custom-format" dump of the database you want to upgrade (let's call it "olddb") $ pg_dump -Fc olddb > olddb.dump Restore the dump contextually upgrading postgis into a new database. The new database doesn't have to exist. postgis_restore accepts createdb parameters after the dump file name, and that can for instance be used if you are using a non-default character encoding for your database. Let's call it "newdb", with UNICODE as the character encoding: $ sh utils/postgis_restore.pl lwpostgis.sql newdb olddb.dump -E=UNICODE > restore.log Check that all restored dump objects really had to be restored from dump and do not conflict with the ones defined in lwpostgis.sql $ grep ^KEEPING restore.log | less If upgrading from PostgreSQL < 8.0 to >= 8.0 you might want to drop the attrelid, varattnum and stats columns in the geometry_columns table, which are no-more needed. Keeping them won't hurt. DROPPING THEM WHEN REALLY NEEDED WILL DO HURT ! $ psql newdb -c "ALTER TABLE geometry_columns DROP attrelid" $ psql newdb -c "ALTER TABLE geometry_columns DROP varattnum" $ psql newdb -c "ALTER TABLE geometry_columns DROP stats" spatial_ref_sys table is restore from the dump, to ensure your custom additions are kept, but the distributed one might contain modification so you should backup your entries, drop the table and source the new one. If you did make additions we assume you know how to backup them before upgrading the table. Replace of it with the new one is done like this: $ psql newdb newdb=> delete from spatial_ref_sys; DROP newdb=> \i spatial_ref_sys.sql There are several things to check when your installation or upgrade doesn't go as you expected. It is easiest if you untar the PostGIS distribution into the contrib directory under the PostgreSQL source tree. However, if this is not possible for some reason, you can set the PGSQL_SRC environment variable to the path to the PostgreSQL source directory. This will allow you to compile PostGIS, but the make install may not work, so be prepared to copy the PostGIS library and executable files to the appropriate locations yourself. Check that you you have installed PostgreSQL 7.2 or newer, and that you are compiling against the same version of the PostgreSQL source as the version of PostgreSQL that is running. Mix-ups can occur when your (Linux) distribution has already installed PostgreSQL, or you have otherwise installed PostgreSQL before and forgotten about it. PostGIS will only work with PostgreSQL 7.2 or newer, and strange, unexpected error messages will result if you use an older version. To check the version of PostgreSQL which is running, connect to the database using psql and run this query: SELECT version(); If you are running an RPM based distribution, you can check for the existence of pre-installed packages using the rpm command as follows: rpm -qa | grep postgresql Also check that you have made any necessary changes to the top of the Makefile.config. This includes: If you want to be able to do coordinate reprojections, you must install the Proj4 library on your system, set the USE_PROJ variable to 1 and the PROJ_DIR to your installation prefix in the Makefile.config. If you want to be able to use GEOS functions you must install the GEOS library on your system, and set the USE_GEOS to 1 and the GEOS_DIR to your installation prefix in the Makefile.config The JDBC extensions provide Java objects corresponding to the internal PostGIS types. These objects can be used to write Java clients which query the PostGIS database and draw or do calculations on the GIS data in PostGIS. Enter the jdbc sub-directory of the PostGIS distribution. Edit the Makefile to provide the correct paths of your java compiler (JAVAC) and interpreter (JAVA). Run the make command. Copy the postgis.jar file to wherever you keep your java libraries. The data loader and dumper are built and installed automatically as part of the PostGIS build. To build and install them manually: # cd postgis-@@LAST_RELEASE_VERSION@@/loader # make # make install The loader is called shp2pgsql and converts ESRI Shape files into SQL suitable for loading in PostGIS/PostgreSQL. The dumper is called pgsql2shp and converts PostGIS tables (or queries) into ESRI Shape files. For more verbose documentation, see the online help, and the manual pages. What kind of geometric objects can I store? You can store point, line, polygon, multipoint, multiline, multipolygon, and geometrycollections. These are specified in the Open GIS Well Known Text Format (with XYZ,XYM,XYZM extentions). How do I insert a GIS object into the database? First, you need to create a table with a column of type "geometry" to hold your GIS data. Connect to your database with psql and try the following SQL: CREATE TABLE gtest ( ID int4, NAME varchar(20) ); SELECT AddGeometryColumn('', 'gtest','geom',-1,'LINESTRING',2); If the geometry column addition fails, you probably have not loaded the PostGIS functions and objects into this database. See the installation instructions. Then, you can insert a geometry into the table using a SQL insert statement. The GIS object itself is formatted using the OpenGIS Consortium "well-known text" format: INSERT INTO gtest (ID, NAME, GEOM) VALUES (1, 'First Geometry', GeomFromText('LINESTRING(2 3,4 5,6 5,7 8)', -1)); For more information about other GIS objects, see the object reference. To view your GIS data in the table: SELECT id, name, AsText(geom) AS geom FROM gtest; The return value should look something like this: id | name | geom ----+----------------+----------------------------- 1 | First Geometry | LINESTRING(2 3,4 5,6 5,7 8) (1 row) How do I construct a spatial query? The same way you construct any other database query, as an SQL combination of return values, functions, and boolean tests. For spatial queries, there are two issues that are important to keep in mind while constructing your query: is there a spatial index you can make use of; and, are you doing expensive calculations on a large number of geometries. In general, you will want to use the "intersects operator" (&&) which tests whether the bounding boxes of features intersect. The reason the && operator is useful is because if a spatial index is available to speed up the test, the && operator will make use of this. This can make queries much much faster. You will also make use of spatial functions, such as Distance(), Intersects(), Contains() and Within(), among others, to narrow down the results of your search. Most spatial queries include both an indexed test and a spatial function test. The index test serves to limit the number of return tuples to only tuples that might meet the condition of interest. The spatial functions are then use to test the condition exactly. SELECT id, the_geom FROM thetable WHERE the_geom && 'POLYGON((0 0, 0 10, 10 10, 10 0, 0 0))' AND Contains(the_geom,'POLYGON((0 0, 0 10, 10 10, 10 0, 0 0))'; How do I speed up spatial queries on large tables? Fast queries on large tables is the raison d'etre of spatial databases (along with transaction support) so having a good index is important. To build a spatial index on a table with a geometry column, use the "CREATE INDEX" function as follows: CREATE INDEX [indexname] ON [tablename] USING GIST ( [geometrycolumn] ); The "USING GIST" option tells the server to use a GiST (Generalized Search Tree) index. GiST indexes are assumed to be lossy. Lossy indexes uses a proxy object (in the spatial case, a bounding box) for building the index. You should also ensure that the PostgreSQL query planner has enough information about your index to make rational decisions about when to use it. To do this, you have to "gather statistics" on your geometry tables. For PostgreSQL 8.0.x and greater, just run the VACUUM ANALYZE command. For PostgreSQL 7.4.x and below, run the SELECT UPDATE_GEOMETRY_STATS() command. Why aren't PostgreSQL R-Tree indexes supported? Early versions of PostGIS used the PostgreSQL R-Tree indexes. However, PostgreSQL R-Trees have been completely discarded since version 0.6, and spatial indexing is provided with an R-Tree-over-GiST scheme. Our tests have shown search speed for native R-Tree and GiST to be comparable. Native PostgreSQL R-Trees have two limitations which make them undesirable for use with GIS features (note that these limitations are due to the current PostgreSQL native R-Tree implementation, not the R-Tree concept in general): R-Tree indexes in PostgreSQL cannot handle features which are larger than 8K in size. GiST indexes can, using the "lossy" trick of substituting the bounding box for the feature itself. R-Tree indexes in PostgreSQL are not "null safe", so building an index on a geometry column which contains null geometries will fail. Why should I use the AddGeometryColumn() function and all the other OpenGIS stuff? If you do not want to use the OpenGIS support functions, you do not have to. Simply create tables as in older versions, defining your geometry columns in the CREATE statement. All your geometries will have SRIDs of -1, and the OpenGIS meta-data tables will not be filled in properly. However, this will cause most applications based on PostGIS to fail, and it is generally suggested that you do use AddGeometryColumn() to create geometry tables. Mapserver is one application which makes use of the geometry_columns meta-data. Specifically, Mapserver can use the SRID of the geometry column to do on-the-fly reprojection of features into the correct map projection. What is the best way to find all objects within a radius of another object? To use the database most efficiently, it is best to do radius queries which combine the radius test with a bounding box test: the bounding box test uses the spatial index, giving fast access to a subset of data which the radius test is then applied to. The Expand() function is a handy way of enlarging a bounding box to allow an index search of a region of interest. The combination of a fast access index clause and a slower accurate distance test provides the best combination of speed and precision for this query. For example, to find all objects with 100 meters of POINT(1000 1000) the following query would work well: SELECT * FROM GEOTABLE WHERE GEOCOLUMN && Expand(GeomFromText('POINT(1000 1000)',-1),100) AND Distance(GeomFromText('POINT(1000 1000)',-1),GEOCOLUMN) < 100; How do I perform a coordinate reprojection as part of a query? To perform a reprojection, both the source and destination coordinate systems must be defined in the SPATIAL_REF_SYS table, and the geometries being reprojected must already have an SRID set on them. Once that is done, a reprojection is as simple as referring to the desired destination SRID. SELECT Transform(GEOM,4269) FROM GEOTABLE; The GIS objects supported by PostGIS are a superset of the "Simple Features" defined by the OpenGIS Consortium (OGC). As of version 0.9, PostGIS supports all the objects and functions specified in the OGC "Simple Features for SQL" specification. PostGIS extends the standard with support for 3DZ,3DM and 4D coordinates. The OpenGIS specification defines two standard ways of expressing spatial objects: the Well-Known Text (WKT) form and the Well-Known Binary (WKB) form. Both WKT and WKB include information about the type of the object and the coordinates which form the object. Examples of the text representations (WKT) of the spatial objects of the features are as follows: POINT(0 0) LINESTRING(0 0,1 1,1 2) POLYGON((0 0,4 0,4 4,0 4,0 0),(1 1, 2 1, 2 2, 1 2,1 1)) MULTIPOINT(0 0,1 2) MULTILINESTRING((0 0,1 1,1 2),(2 3,3 2,5 4)) MULTIPOLYGON(((0 0,4 0,4 4,0 4,0 0),(1 1,2 1,2 2,1 2,1 1)), ((-1 -1,-1 -2,-2 -2,-2 -1,-1 -1))) GEOMETRYCOLLECTION(POINT(2 3),LINESTRING((2 3,3 4))) The OpenGIS specification also requires that the internal storage format of spatial objects include a spatial referencing system identifier (SRID). The SRID is required when creating spatial objects for insertion into the database. Input/Output of these formats are available using the following interfaces: bytea WKB = asBinary(geometry); text WKT = asText(geometry); geometry = GeomFromWKB(bytea WKB, SRID); geometry = GeometryFromText(text WKT, SRID); For example, a valid insert statement to create and insert an OGC spatial object would be: INSERT INTO SPATIALTABLE ( THE_GEOM, THE_NAME ) VALUES ( GeomFromText('POINT(-126.4 45.32)', 312), 'A Place' ) OGC formats only support 2d geometries, and the associated SRID is *never* embedded in the input/output representations. PostGIS extended formats are currently superset of OGC one (every valid WKB/WKT is a valid EWKB/EWKT) but this might vary in the future, specifically if OGC comes out with a new format conflicting with our extensions. Thus you SHOULD NOT rely on this feature! PostGIS EWKB/EWKT add 3dm,3dz,4d coordinates support and embedded SRID information. Examples of the text representations (EWKT) of the extended spatial objects of the features are as follows: POINT(0 0 0) -- XYZ SRID=32632;POINT(0 0) -- XY with SRID POINTM(0 0 0) -- XYM POINT(0 0 0 0) -- XYZM SRID=4326;MULTIPOINTM(0 0 0,1 2 1) -- XYM with SRID MULTILINESTRING((0 0 0,1 1 0,1 2 1),(2 3 1,3 2 1,5 4 1)) POLYGON((0 0 0,4 0 0,4 4 0,0 4 0,0 0 0),(1 1 0,2 1 0,2 2 0,1 2 0,1 1 0)) MULTIPOLYGON(((0 0 0,4 0 0,4 4 0,0 4 0,0 0 0),(1 1 0,2 1 0,2 2 0,1 2 0,1 1 0)),((-1 -1 0,-1 -2 0,-2 -2 0,-2 -1 0,-1 -1 0))) GEOMETRYCOLLECTIONM(POINTM(2 3 9), LINESTRINGM(2 3 4, 3 4 5)) Input/Output of these formats are available using the following interfaces: bytea EWKB = asEWKB(geometry); text EWKT = asEWKT(geometry); geometry = GeomFromEWKB(bytea EWKB); geometry = GeomFromEWKT(text EWKT); For example, a valid insert statement to create and insert a PostGIS spatial object would be: INSERT INTO SPATIALTABLE ( THE_GEOM, THE_NAME ) VALUES ( GeomFromEWKT('SRID=312;POINTM(-126.4 45.32 15)'), 'A Place' ) The "canonical forms" of a PostgreSQL type are the representations you get with a simple query (without any function call) and the one which is guaranteed to be accepted with a simple insert, update or copy. For the postgis 'geometry' type these are: - Output - binary: EWKB ascii: HEXEWKB (EWKB in hex form) - Input - binary: EWKB ascii: HEXEWKB|EWKT For example this statement reads EWKT and returns HEXEWKB in the process of canonical ascii input/output: =# SELECT 'SRID=4;POINT(0 0)'::geometry; geometry ---------------------------------------------------- 01010000200400000000000000000000000000000000000000 (1 row) The SQL Multimedia Applications Spatial specification extends the simple features for SQL spec by defining a number of circularly interpolated curves. The SQL-MM definitions include 3dm, 3dz and 4d coordinates, but do not allow the embedding of SRID information. The well-known text extensions are not yet fully supported. Examples of some simple curved geometries are shown below: CIRCULARSTRING(0 0, 1 1, 1 0) COMPOUNDCURVE(CIRCULARSTRING(0 0, 1 1, 1 0),(1 0, 0 1)) CURVEPOLYGON(CIRCULARSTRING(0 0, 4 0, 4 4, 0 4, 0 0),(1 1, 3 3, 3 1, 1 1)) MULTICURVE((0 0, 5 5),CIRCULARSTRING(4 0, 4 4, 8 4)) MULTISURFACE(CURVEPOLYGON(CIRCULARSTRING(0 0, 4 0, 4 4, 0 4, 0 0),(1 1, 3 3, 3 1, 1 1)),((10 10, 14 12, 11 10, 10 10),(11 11, 11.5 11, 11 11.5, 11 11))) Currently, PostGIS cannot support the use of Compound Curves in a Curve Polygon. All floating point comparisons within the SQL-MM implementation are performed to a specified tolerance, currently 1E-8. The OpenGIS "Simple Features Specification for SQL" defines standard GIS object types, the functions required to manipulate them, and a set of meta-data tables. In order to ensure that meta-data remain consistent, operations such as creating and removing a spatial column are carried out through special procedures defined by OpenGIS. There are two OpenGIS meta-data tables: SPATIAL_REF_SYS and GEOMETRY_COLUMNS. The SPATIAL_REF_SYS table holds the numeric IDs and textual descriptions of coordinate systems used in the spatial database. The SPATIAL_REF_SYS table definition is as follows: CREATE TABLE SPATIAL_REF_SYS ( SRID INTEGER NOT NULL PRIMARY KEY, AUTH_NAME VARCHAR(256), AUTH_SRID INTEGER, SRTEXT VARCHAR(2048), PROJ4TEXT VARCHAR(2048) ) The SPATIAL_REF_SYS columns are as follows: SRID An integer value that uniquely identifies the Spatial Referencing System (SRS) within the database. AUTH_NAME The name of the standard or standards body that is being cited for this reference system. For example, "EPSG" would be a valid AUTH_NAME. AUTH_SRID The ID of the Spatial Reference System as defined by the Authority cited in the AUTH_NAME. In the case of EPSG, this is where the EPSG projection code would go. SRTEXT The Well-Known Text representation of the Spatial Reference System. An example of a WKT SRS representation is: PROJCS["NAD83 / UTM Zone 10N", GEOGCS["NAD83", DATUM["North_American_Datum_1983", SPHEROID["GRS 1980",6378137,298.257222101] ], PRIMEM["Greenwich",0], UNIT["degree",0.0174532925199433] ], PROJECTION["Transverse_Mercator"], PARAMETER["latitude_of_origin",0], PARAMETER["central_meridian",-123], PARAMETER["scale_factor",0.9996], PARAMETER["false_easting",500000], PARAMETER["false_northing",0], UNIT["metre",1] ] For a listing of EPSG projection codes and their corresponding WKT representations, see http://www.opengis.org/techno/interop/EPSG2WKT.TXT. For a discussion of WKT in general, see the OpenGIS "Coordinate Transformation Services Implementation Specification" at http://www.opengis.org/techno/specs.htm. For information on the European Petroleum Survey Group (EPSG) and their database of spatial reference systems, see http://epsg.org. PROJ4TEXT PostGIS uses the Proj4 library to provide coordinate transformation capabilities. The PROJ4TEXT column contains the Proj4 coordinate definition string for a particular SRID. For example: +proj=utm +zone=10 +ellps=clrk66 +datum=NAD27 +units=m For more information about, see the Proj4 web site at http://www.remotesensing.org/proj. The spatial_ref_sys.sql file contains both SRTEXT and PROJ4TEXT definitions for all EPSG projections. The GEOMETRY_COLUMNS table definition is as follows: CREATE TABLE GEOMETRY_COLUMNS ( F_TABLE_CATALOG VARCHAR(256) NOT NULL, F_TABLE_SCHEMA VARCHAR(256) NOT NULL, F_TABLE_NAME VARCHAR(256) NOT NULL, F_GEOMETRY_COLUMN VARCHAR(256) NOT NULL, COORD_DIMENSION INTEGER NOT NULL, SRID INTEGER NOT NULL, TYPE VARCHAR(30) NOT NULL ) The columns are as follows: F_TABLE_CATALOG, F_TABLE_SCHEMA, F_TABLE_NAME The fully qualified name of the feature table containing the geometry column. Note that the terms "catalog" and "schema" are Oracle-ish. There is not PostgreSQL analogue of "catalog" so that column is left blank -- for "schema" the PostgreSQL schema name is used (public is the default). F_GEOMETRY_COLUMN The name of the geometry column in the feature table. COORD_DIMENSION The spatial dimension (2, 3 or 4 dimensional) of the column. SRID The ID of the spatial reference system used for the coordinate geometry in this table. It is a foreign key reference to the SPATIAL_REF_SYS. TYPE The type of the spatial object. To restrict the spatial column to a single type, use one of: POINT, LINESTRING, POLYGON, MULTIPOINT, MULTILINESTRING, MULTIPOLYGON, GEOMETRYCOLLECTION or corresponding XYM versions POINTM, LINESTRINGM, POLYGONM, MULTIPOINTM, MULTILINESTRINGM, MULTIPOLYGONM, GEOMETRYCOLLECTIONM. For heterogeneous (mixed-type) collections, you can use "GEOMETRY" as the type. This attribute is (probably) not part of the OpenGIS specification, but is required for ensuring type homogeneity. Creating a table with spatial data is done in two stages: Create a normal non-spatial table. For example: CREATE TABLE ROADS_GEOM ( ID int4, NAME varchar(25) ) Add a spatial column to the table using the OpenGIS "AddGeometryColumn" function. The syntax is: AddGeometryColumn(<schema_name>, <table_name>, <column_name>, <srid>, <type>, <dimension>) Or, using current schema: AddGeometryColumn(<table_name>, <column_name>, <srid>, <type>, <dimension>) Example1: SELECT AddGeometryColumn('public', 'roads_geom', 'geom', 423, 'LINESTRING', 2) Example2: SELECT AddGeometryColumn( 'roads_geom', 'geom', 423, 'LINESTRING', 2) Here is an example of SQL used to create a table and add a spatial column (assuming that an SRID of 128 exists already): CREATE TABLE parks ( PARK_ID int4, PARK_NAME varchar(128), PARK_DATE date, PARK_TYPE varchar(2) ); SELECT AddGeometryColumn('parks', 'park_geom', 128, 'MULTIPOLYGON', 2 ); Here is another example, using the generic "geometry" type and the undefined SRID value of -1: CREATE TABLE roads ( ROAD_ID int4, ROAD_NAME varchar(128) ); SELECT AddGeometryColumn( 'roads', 'roads_geom', -1, 'GEOMETRY', 3 ); Most of the functions implemented by the GEOS library rely on the assumption that your geometries are valid as specified by the OpenGIS Simple Feature Specification. To check validity of geometries you can use the IsValid() function: gisdb=# select isvalid('LINESTRING(0 0, 1 1)'), isvalid('LINESTRING(0 0,0 0)'); isvalid | isvalid ---------+--------- t | f By default, PostGIS does not apply this validity check on geometry input, because testing for validity needs lots of CPU time for complex geometries, especially polygons. If you do not trust your data sources, you can manually enforce such a check to your tables by adding a check constraint: ALTER TABLE mytable ADD CONSTRAINT geometry_valid_check CHECK (isvalid(the_geom)); If you encounter any strange error messages such as "GEOS Intersection() threw an error!" or "JTS Intersection() threw an error!" when calling PostGIS functions with valid input geometries, you likely found an error in either PostGIS or one of the libraries it uses, and you should contact the PostGIS developers. The same is true if a PostGIS function returns an invalid geometry for valid input. Strictly compliant OGC geometries cannot have Z or M values. The IsValid() function won't consider higher dimensioned geometries invalid! Invocations of AddGeometryColumn() will add a constraint checking geometry dimensions, so it is enough to specify 2 there. Once you have created a spatial table, you are ready to upload GIS data to the database. Currently, there are two ways to get data into a PostGIS/PostgreSQL database: using formatted SQL statements or using the Shape file loader/dumper. If you can convert your data to a text representation, then using formatted SQL might be the easiest way to get your data into PostGIS. As with Oracle and other SQL databases, data can be bulk loaded by piping a large text file full of SQL "INSERT" statements into the SQL terminal monitor. A data upload file (roads.sql for example) might look like this: BEGIN; INSERT INTO ROADS_GEOM (ID,GEOM,NAME ) VALUES (1,GeomFromText('LINESTRING(191232 243118,191108 243242)',-1),'Jeff Rd'); INSERT INTO ROADS_GEOM (ID,GEOM,NAME ) VALUES (2,GeomFromText('LINESTRING(189141 244158,189265 244817)',-1),'Geordie Rd'); INSERT INTO ROADS_GEOM (ID,GEOM,NAME ) VALUES (3,GeomFromText('LINESTRING(192783 228138,192612 229814)',-1),'Paul St'); INSERT INTO ROADS_GEOM (ID,GEOM,NAME ) VALUES (4,GeomFromText('LINESTRING(189412 252431,189631 259122)',-1),'Graeme Ave'); INSERT INTO ROADS_GEOM (ID,GEOM,NAME ) VALUES (5,GeomFromText('LINESTRING(190131 224148,190871 228134)',-1),'Phil Tce'); INSERT INTO ROADS_GEOM (ID,GEOM,NAME ) VALUES (6,GeomFromText('LINESTRING(198231 263418,198213 268322)',-1),'Dave Cres'); COMMIT; The data file can be piped into PostgreSQL very easily using the "psql" SQL terminal monitor: psql -d [database] -f roads.sql The shp2pgsql data loader converts ESRI Shape files into SQL suitable for insertion into a PostGIS/PostgreSQL database. The loader has several operating modes distinguished by command line flags: -d Drops the database table before creating a new table with the data in the Shape file. -a Appends data from the Shape file into the database table. Note that to use this option to load multiple files, the files must have the same attributes and same data types. -c Creates a new table and populates it from the Shape file. This is the default mode. -p Only produces the table creation SQL code, without adding any actual data. This can be used if you need to completely separate the table creation and data loading steps. -D Use the PostgreSQL "dump" format for the output data. This can be combined with -a, -c and -d. It is much faster to load than the default "insert" SQL format. Use this for very large data sets. -s <SRID> Creates and populates the geometry tables with the specified SRID. -k Keep identifiers' case (column, schema and attributes). Note that attributes in Shapefile are all UPPERCASE. -i Coerce all integers to standard 32-bit integers, do not create 64-bit bigints, even if the DBF header signature appears to warrant it. -I Create a GiST index on the geometry column. -w Output WKT format, for use with older (0.x) versions of PostGIS. Note that this will introduce coordinate drifts and will drop M values from shapefiles. -W <encoding> Specify encoding of the input data (dbf file). When used, all attributes of the dbf are converted from the specified encoding to UTF8. The resulting SQL output will contain a SET CLIENT_ENCODING to UTF8 command, so that the backend will be able to reconvert from UTF8 to whatever encoding the database is configured to use internally. Note that -a, -c, -d and -p are mutually exclusive. An example session using the loader to create an input file and uploading it might look like this: # shp2pgsql shaperoads myschema.roadstable > roads.sql # psql -d roadsdb -f roads.sql A conversion and upload can be done all in one step using UNIX pipes: # shp2pgsql shaperoads myschema.roadstable | psql -d roadsdb Data can be extracted from the database using either SQL or the Shape file loader/dumper. In the section on SQL we will discuss some of the operators available to do comparisons and queries on spatial tables. The most straightforward means of pulling data out of the database is to use a SQL select query and dump the resulting columns into a parsable text file: db=# SELECT id, AsText(geom) AS geom, name FROM ROADS_GEOM; id | geom | name ---+-----------------------------------------+----------- 1 | LINESTRING(191232 243118,191108 243242) | Jeff Rd 2 | LINESTRING(189141 244158,189265 244817) | Geordie Rd 3 | LINESTRING(192783 228138,192612 229814) | Paul St 4 | LINESTRING(189412 252431,189631 259122) | Graeme Ave 5 | LINESTRING(190131 224148,190871 228134) | Phil Tce 6 | LINESTRING(198231 263418,198213 268322) | Dave Cres 7 | LINESTRING(218421 284121,224123 241231) | Chris Way (6 rows) However, there will be times when some kind of restriction is necessary to cut down the number of fields returned. In the case of attribute-based restrictions, just use the same SQL syntax as normal with a non-spatial table. In the case of spatial restrictions, the following operators are available/useful: && This operator tells whether the bounding box of one geometry intersects the bounding box of another. ~= This operators tests whether two geometries are geometrically identical. For example, if 'POLYGON((0 0,1 1,1 0,0 0))' is the same as 'POLYGON((0 0,1 1,1 0,0 0))' (it is). = This operator is a little more naive, it only tests whether the bounding boxes of to geometries are the same. Next, you can use these operators in queries. Note that when specifying geometries and boxes on the SQL command line, you must explicitly turn the string representations into geometries by using the "GeomFromText()" function. So, for example: SELECT ID, NAME FROM ROADS_GEOM WHERE GEOM ~= GeomFromText('LINESTRING(191232 243118,191108 243242)',-1); The above query would return the single record from the "ROADS_GEOM" table in which the geometry was equal to that value. When using the "&&" operator, you can specify either a BOX3D as the comparison feature or a GEOMETRY. When you specify a GEOMETRY, however, its bounding box will be used for the comparison. SELECT ID, NAME FROM ROADS_GEOM WHERE GEOM && GeomFromText('POLYGON((191232 243117,191232 243119,191234 243117,191232 243117))',-1); The above query will use the bounding box of the polygon for comparison purposes. The most common spatial query will probably be a "frame-based" query, used by client software, like data browsers and web mappers, to grab a "map frame" worth of data for display. Using a "BOX3D" object for the frame, such a query looks like this: SELECT AsText(GEOM) AS GEOM FROM ROADS_GEOM WHERE GEOM && SetSRID('BOX3D(191232 243117,191232 243119)'::box3d,-1); Note the use of the SRID, to specify the projection of the BOX3D. The value -1 is used to indicate no specified SRID. The pgsql2shp table dumper connects directly to the database and converts a table (possibly defined by a query) into a shape file. The basic syntax is: pgsql2shp [<options>] <database> [<schema>.]<table> pgsql2shp [<options>] <database> <query> The commandline options are: -f <filename> Write the output to a particular filename. -h <host> The database host to connect to. -p <port> The port to connect to on the database host. -P <password> The password to use when connecting to the database. -u <user> The username to use when connecting to the database. -g <geometry column> In the case of tables with multiple geometry columns, the geometry column to use when writing the shape file. -b Use a binary cursor. This will make the operation faster, but will not work if any NON-geometry attribute in the table lacks a cast to text. -r Raw mode. Do not drop the gid field, or escape column names. -d For backward compatibility: write a 3-dimensional shape file when dumping from old (pre-1.0.0) postgis databases (the default is to write a 2-dimensional shape file in that case). Starting from postgis-1.0.0+, dimensions are fully encoded. Indexes are what make using a spatial database for large data sets possible. Without indexing, any search for a feature would require a "sequential scan" of every record in the database. Indexing speeds up searching by organizing the data into a search tree which can be quickly traversed to find a particular record. PostgreSQL supports three kinds of indexes by default: B-Tree indexes, R-Tree indexes, and GiST indexes. B-Trees are used for data which can be sorted along one axis; for example, numbers, letters, dates. GIS data cannot be rationally sorted along one axis (which is greater, (0,0) or (0,1) or (1,0)?) so B-Tree indexing is of no use for us. R-Trees break up data into rectangles, and sub-rectangles, and sub-sub rectangles, etc. R-Trees are used by some spatial databases to index GIS data, but the PostgreSQL R-Tree implementation is not as robust as the GiST implementation. GiST (Generalized Search Trees) indexes break up data into "things to one side", "things which overlap", "things which are inside" and can be used on a wide range of data-types, including GIS data. PostGIS uses an R-Tree index implemented on top of GiST to index GIS data. GiST stands for "Generalized Search Tree" and is a generic form of indexing. In addition to GIS indexing, GiST is used to speed up searches on all kinds of irregular data structures (integer arrays, spectral data, etc) which are not amenable to normal B-Tree indexing. Once a GIS data table exceeds a few thousand rows, you will want to build an index to speed up spatial searches of the data (unless all your searches are based on attributes, in which case you'll want to build a normal index on the attribute fields). The syntax for building a GiST index on a "geometry" column is as follows: CREATE INDEX [indexname] ON [tablename] USING GIST ( [geometryfield] GIST_GEOMETRY_OPS ); Building a spatial index is a computationally intensive exercise: on tables of around 1 million rows, on a 300MHz Solaris machine, we have found building a GiST index takes about 1 hour. After building an index, it is important to force PostgreSQL to collect table statistics, which are used to optimize query plans: VACUUM ANALYZE [table_name] [column_name]; -- This is only needed for PostgreSQL 7.4 installations and below SELECT UPDATE_GEOMETRY_STATS([table_name], [column_name]); GiST indexes have two advantages over R-Tree indexes in PostgreSQL. Firstly, GiST indexes are "null safe", meaning they can index columns which include null values. Secondly, GiST indexes support the concept of "lossiness" which is important when dealing with GIS objects larger than the PostgreSQL 8K page size. Lossiness allows PostgreSQL to store only the "important" part of an object in an index -- in the case of GIS objects, just the bounding box. GIS objects larger than 8K will cause R-Tree indexes to fail in the process of being built. Ordinarily, indexes invisibly speed up data access: once the index is built, the query planner transparently decides when to use index information to speed up a query plan. Unfortunately, the PostgreSQL query planner does not optimize the use of GiST indexes well, so sometimes searches which should use a spatial index instead default to a sequence scan of the whole table. If you find your spatial indexes are not being used (or your attribute indexes, for that matter) there are a couple things you can do: Firstly, make sure statistics are gathered about the number and distributions of values in a table, to provide the query planner with better information to make decisions around index usage. For PostgreSQL 7.4 installations and below this is done by running update_geometry_stats([table_name, column_name]) (compute distribution) and VACUUM ANALYZE [table_name] [column_name] (compute number of values). Starting with PostgreSQL 8.0 running VACUUM ANALYZE will do both operations. You should regularly vacuum your databases anyways -- many PostgreSQL DBAs have VACUUM run as an off-peak cron job on a regular basis. If vacuuming does not work, you can force the planner to use the index information by using the SET ENABLE_SEQSCAN=OFF command. You should only use this command sparingly, and only on spatially indexed queries: generally speaking, the planner knows better than you do about when to use normal B-Tree indexes. Once you have run your query, you should consider setting ENABLE_SEQSCAN back on, so that other queries will utilize the planner as normal. As of version 0.6, it should not be necessary to force the planner to use the index with ENABLE_SEQSCAN. If you find the planner wrong about the cost of sequential vs index scans try reducing the value of random_page_cost in postgresql.conf or using SET random_page_cost=#. Default value for the parameter is 4, try setting it to 1 or 2. Decrementing the value makes the planner more inclined of using Index scans. The raison d'etre of spatial database functionality is performing queries inside the database which would ordinarily require desktop GIS functionality. Using PostGIS effectively requires knowing what spatial functions are available, and ensuring that appropriate indexes are in place to provide good performance. When constructing a query it is important to remember that only the bounding-box-based operators such as && can take advantage of the GiST spatial index. Functions such as distance() cannot use the index to optimize their operation. For example, the following query would be quite slow on a large table: SELECT the_geom FROM geom_table WHERE distance( the_geom, GeomFromText( 'POINT(100000 200000)', -1 ) ) < 100 This query is selecting all the geometries in geom_table which are within 100 units of the point (100000, 200000). It will be slow because it is calculating the distance between each point in the table and our specified point, ie. one distance() calculation for each row in the table. We can avoid this by using the && operator to reduce the number of distance calculations required: SELECT the_geom FROM geom_table WHERE the_geom && 'BOX3D(90900 190900, 100100 200100)'::box3d AND distance( the_geom, GeomFromText( 'POINT(100000 200000)', -1 ) ) < 100 This query selects the same geometries, but it does it in a more efficient way. Assuming there is a GiST index on the_geom, the query planner will recognize that it can use the index to reduce the number of rows before calculating the result of the distance() function. Notice that the BOX3D geometry which is used in the && operation is a 200 unit square box centered on the original point - this is our "query box". The && operator uses the index to quickly reduce the result set down to only those geometries which have bounding boxes that overlap the "query box". Assuming that our query box is much smaller than the extents of the entire geometry table, this will drastically reduce the number of distance calculations that need to be done. The examples in this section will make use of two tables, a table of linear roads, and a table of polygonal municipality boundaries. The table definitions for the bc_roads table is: Column | Type | Description ------------+-------------------+------------------- gid | integer | Unique ID name | character varying | Road Name the_geom | geometry | Location Geometry (Linestring) The table definition for the bc_municipality table is: Column | Type | Description -----------+-------------------+------------------- gid | integer | Unique ID code | integer | Unique ID name | character varying | City / Town Name the_geom | geometry | Location Geometry (Polygon) What is the total length of all roads, expressed in kilometers? You can answer this question with a very simple piece of SQL: postgis=# SELECT sum(length(the_geom))/1000 AS km_roads FROM bc_roads; km_roads ------------------ 70842.1243039643 (1 row) How large is the city of Prince George, in hectares? This query combines an attribute condition (on the municipality name) with a spatial calculation (of the area): postgis=# SELECT area(the_geom)/10000 AS hectares FROM bc_municipality WHERE name = 'PRINCE GEORGE'; hectares ------------------ 32657.9103824927 (1 row) What is the largest municipality in the province, by area? This query brings a spatial measurement into the query condition. There are several ways of approaching this problem, but the most efficient is below: postgis=# SELECT name, area(the_geom)/10000 AS hectares FROM bc_municipality ORDER BY hectares DESC LIMIT 1; name | hectares ---------------+----------------- TUMBLER RIDGE | 155020.02556131 (1 row) Note that in order to answer this query we have to calculate the area of every polygon. If we were doing this a lot it would make sense to add an area column to the table that we could separately index for performance. By ordering the results in a descending direction, and them using the PostgreSQL "LIMIT" command we can easily pick off the largest value without using an aggregate function like max(). What is the length of roads fully contained within each municipality? This is an example of a "spatial join", because we are bringing together data from two tables (doing a join) but using a spatial interaction condition ("contained") as the join condition rather than the usual relational approach of joining on a common key: postgis=# SELECT m.name, sum(length(r.the_geom))/1000 as roads_km FROM bc_roads AS r,bc_municipality AS m WHERE r.the_geom && m.the_geom AND contains(m.the_geom,r.the_geom) GROUP BY m.name ORDER BY roads_km; name | roads_km ----------------------------+------------------ SURREY | 1539.47553551242 VANCOUVER | 1450.33093486576 LANGLEY DISTRICT | 833.793392535662 BURNABY | 773.769091404338 PRINCE GEORGE | 694.37554369147 ... This query takes a while, because every road in the table is summarized into the final result (about 250K roads for our particular example table). For smaller overlays (several thousand records on several hundred) the response can be very fast. Create a new table with all the roads within the city of Prince George. This is an example of an "overlay", which takes in two tables and outputs a new table that consists of spatially clipped or cut resultants. Unlike the "spatial join" demonstrated above, this query actually creates new geometries. An overlay is like a turbo-charged spatial join, and is useful for more exact analysis work: postgis=# CREATE TABLE pg_roads as SELECT intersection(r.the_geom, m.the_geom) AS intersection_geom, length(r.the_geom) AS rd_orig_length, r.* FROM bc_roads AS r, bc_municipality AS m WHERE r.the_geom && m.the_geom AND intersects(r.the_geom, m.the_geom) AND m.name = 'PRINCE GEORGE'; What is the length in kilometers of "Douglas St" in Victoria? postgis=# SELECT sum(length(r.the_geom))/1000 AS kilometers FROM bc_roads r, bc_municipality m WHERE r.the_geom && m.the_geom AND r.name = 'Douglas St' AND m.name = 'VICTORIA'; kilometers ------------------ 4.89151904172838 (1 row) What is the largest municipality polygon that has a hole? postgis=# SELECT gid, name, area(the_geom) AS area FROM bc_municipality WHERE nrings(the_geom) > 1 ORDER BY area DESC LIMIT 1; gid | name | area -----+--------------+------------------ 12 | SPALLUMCHEEN | 257374619.430216 (1 row) The Minnesota Mapserver is an internet web-mapping server which conforms to the OpenGIS Web Mapping Server specification. The Mapserver homepage is at http://mapserver.gis.umn.edu. The OpenGIS Web Map Specification is at http://www.opengis.org/techno/specs/01-047r2.pdf. To use PostGIS with Mapserver, you will need to know about how to configure Mapserver, which is beyond the scope of this documentation. This section will cover specific PostGIS issues and configuration details. To use PostGIS with Mapserver, you will need: Version 0.6 or newer of PostGIS. Version 3.5 or newer of Mapserver. Mapserver accesses PostGIS/PostgreSQL data like any other PostgreSQL client -- using libpq. This means that Mapserver can be installed on any machine with network access to the PostGIS server, as long as the system has the libpq PostgreSQL client libraries. Compile and install Mapserver, with whatever options you desire, including the "--with-postgis" configuration option. In your Mapserver map file, add a PostGIS layer. For example: LAYER CONNECTIONTYPE postgis NAME "widehighways" # Connect to a remote spatial database CONNECTION "user=dbuser dbname=gisdatabase host=bigserver" # Get the lines from the 'geom' column of the 'roads' table DATA "geom from roads" STATUS ON TYPE LINE # Of the lines in the extents, only render the wide highways FILTER "type = 'highway' and numlanes >= 4" CLASS # Make the superhighways brighter and 2 pixels wide EXPRESSION ([numlanes] >= 6) COLOR 255 22 22 SYMBOL "solid" SIZE 2 END CLASS # All the rest are darker and only 1 pixel wide EXPRESSION ([numlanes] < 6) COLOR 205 92 82 END END In the example above, the PostGIS-specific directives are as follows: CONNECTIONTYPE For PostGIS layers, this is always "postgis". CONNECTION The database connection is governed by the a 'connection string' which is a standard set of keys and values like this (with the default values in <>): user=<username> password=<password> dbname=<username> hostname=<server> port=<5432> An empty connection string is still valid, and any of the key/value pairs can be omitted. At a minimum you will generally supply the database name and username to connect with. DATA The form of this parameter is "<column> from <tablename>" where the column is the spatial column to be rendered to the map. FILTER The filter must be a valid SQL string corresponding to the logic normally following the "WHERE" keyword in a SQL query. So, for example, to render only roads with 6 or more lanes, use a filter of "num_lanes >= 6". In your spatial database, ensure you have spatial (GiST) indexes built for any the layers you will be drawing. CREATE INDEX [indexname] ON [tablename] USING GIST ( [geometrycolumn] GIST_GEOMETRY_OPS ); If you will be querying your layers using Mapserver you will also need an "oid index". Mapserver requires unique identifiers for each spatial record when doing queries, and the PostGIS module of Mapserver uses the PostgreSQL oid value to provide these unique identifiers. A side-effect of this is that in order to do fast random access of records during queries, an index on the oid is needed. To build an "oid index", use the following SQL: CREATE INDEX [indexname] ON [tablename] ( oid ); When I use an EXPRESSION in my map file, the condition never returns as true, even though I know the values exist in my table. Unlike shape files, PostGIS field names have to be referenced in EXPRESSIONS using lower case. EXPRESSION ([numlanes] >= 6) The FILTER I use for my Shape files is not working for my PostGIS table of the same data. Unlike shape files, filters for PostGIS layers use SQL syntax (they are appended to the SQL statement the PostGIS connector generates for drawing layers in Mapserver). FILTER "type = 'highway' and numlanes >= 4" My PostGIS layer draws much slower than my Shape file layer, is this normal? In general, expect PostGIS layers to be 10% slower than equivalent Shape files layers, due to the extra overhead involved in database connections, data transformations and data transit between the database and Mapserver. If you are finding substantial draw performance problems, it is likely that you have not build a spatial index on your table. postgis# CREATE INDEX geotable_gix ON geotable USING GIST ( geocolumn ); postgis# SELECT update_geometry_stats(); -- For PGSQL < 8.0 postgis# VACUUM ANALYZE; -- For PGSQL >= 8.0 My PostGIS layer draws fine, but queries are really slow. What is wrong? For queries to be fast, you must have a unique key for your spatial table and you must have an index on that unique key. You can specify what unique key for mapserver to use with the USING UNIQUE clause in your DATA line: DATA "the_geom FROM geotable USING UNIQUE gid" If your table does not have an explicit unique column, you can "fake" a unique column by using the PostgreSQL row "oid" for your unique column. "oid" is the default unique column if you do not declare one, so enhancing your query speed is a matter of building an index on your spatial table oid value. postgis# CREATE INDEX geotable_oid_idx ON geotable (oid); The USING pseudo-SQL clause is used to add some information to help mapserver understand the results of more complex queries. More specifically, when either a view or a subselect is used as the source table (the thing to the right of "FROM" in a DATA definition) it is more difficult for mapserver to automatically determine a unique identifier for each row and also the SRID for the table. The USING clause can provide mapserver with these two pieces of information as follows: DATA "the_geom FROM (SELECT table1.the_geom AS the_geom, table1.oid AS oid, table2.data AS data FROM table1 LEFT JOIN table2 ON table1.id = table2.id) AS new_table USING UNIQUE oid USING SRID=-1" USING UNIQUE <uniqueid> Mapserver requires a unique id for each row in order to identify the row when doing map queries. Normally, it would use the oid as the unique identifier, but views and subselects don't automatically have an oid column. If you want to use Mapserver's query functionality, you need to add a unique column to your view or subselect, and declare it with USING UNIQUE. For example, you could explicitly select one of the table's oid values for this purpose, or any other column which is guaranteed to be unique for the result set. The USING statement can also be useful even for simple DATA statements, if you are doing map queries. It was previously recommended to add an index on the oid column of tables used in query-able layers, in order to speed up the performance of map queries. However, with the USING clause, it is possible to tell mapserver to use your table's primary key as the identifier for map queries, and then it is no longer necessary to have an additional index. "Querying a Map" is the action of clicking on a map to ask for information about the map features in that location. Don't confuse "map queries" with the SQL query in a DATA definition. USING SRID=<srid> PostGIS needs to know which spatial referencing system is being used by the geometries in order to return the correct data back to mapserver. Normally it is possible to find this information in the "geometry_columns" table in the PostGIS database, however, this is not possible for tables which are created on the fly such as subselects and views. So the USING SRID= option allows the correct SRID to be specified in the DATA definition. The parser for Mapserver PostGIS layers is fairly primitive, and is case sensitive in a few areas. Be careful to ensure that all SQL keywords and all your USING clauses are in upper case, and that your USING UNIQUE clause precedes your USING SRID clause. Lets start with a simple example and work our way up. Consider the following Mapserver layer definition: LAYER CONNECTIONTYPE postgis NAME "roads" CONNECTION "user=theuser password=thepass dbname=thedb host=theserver" DATA "the_geom FROM roads" STATUS ON TYPE LINE CLASS COLOR 0 0 0 END END This layer will display all the road geometries in the roads table as black lines. Now lets say we want to show only the highways until we get zoomed in to at least a 1:100000 scale - the next two layers will achieve this effect: LAYER CONNECTION "user=theuser password=thepass dbname=thedb host=theserver" DATA "the_geom FROM roads" MINSCALE 100000 STATUS ON TYPE LINE FILTER "road_type = 'highway'" CLASS COLOR 0 0 0 END END LAYER CONNECTION "user=theuser password=thepass dbname=thedb host=theserver" DATA "the_geom FROM roads" MAXSCALE 100000 STATUS ON TYPE LINE CLASSITEM road_type CLASS EXPRESSION "highway" SIZE 2 COLOR 255 0 0 END CLASS COLOR 0 0 0 END END The first layer is used when the scale is greater than 1:100000, and displays only the roads of type "highway" as black lines. The FILTER option causes only roads of type "highway" to be displayed. The second layer is used when the scale is less than 1:100000, and will display highways as double-thick red lines, and other roads as regular black lines. So, we have done a couple of interesting things using only mapserver functionality, but our DATA SQL statement has remained simple. Suppose that the name of the road is stored in another table (for whatever reason) and we need to do a join to get it and label our roads. LAYER CONNECTION "user=theuser password=thepass dbname=thedb host=theserver" DATA "the_geom FROM (SELECT roads.oid AS oid, roads.the_geom AS the_geom, road_names.name as name FROM roads LEFT JOIN road_names ON roads.road_name_id = road_names.road_name_id) AS named_roads USING UNIQUE oid USING SRID=-1" MAXSCALE 20000 STATUS ON TYPE ANNOTATION LABELITEM name CLASS LABEL ANGLE auto SIZE 8 COLOR 0 192 0 TYPE truetype FONT arial END END END This annotation layer adds green labels to all the roads when the scale gets down to 1:20000 or less. It also demonstrates how to use an SQL join in a DATA definition. Java clients can access PostGIS "geometry" objects in the PostgreSQL database either directly as text representations or using the JDBC extension objects bundled with PostGIS. In order to use the extension objects, the "postgis.jar" file must be in your CLASSPATH along with the "postgresql.jar" JDBC driver package. import java.sql.*; import java.util.*; import java.lang.*; import org.postgis.*; public class JavaGIS { public static void main(String[] args) { java.sql.Connection conn; try { /* * Load the JDBC driver and establish a connection. */ Class.forName("org.postgresql.Driver"); String url = "jdbc:postgresql://localhost:5432/database"; conn = DriverManager.getConnection(url, "postgres", ""); /* * Add the geometry types to the connection. Note that you * must cast the connection to the pgsql-specific connection * implementation before calling the addDataType() method. */ ((org.postgresql.Connection)conn).addDataType("geometry","org.postgis.PGgeometry"); ((org.postgresql.Connection)conn).addDataType("box3d","org.postgis.PGbox3d"); /* * Create a statement and execute a select query. */ Statement s = conn.createStatement(); ResultSet r = s.executeQuery("select AsText(geom) as geom,id from geomtable"); while( r.next() ) { /* * Retrieve the geometry as an object then cast it to the geometry type. * Print things out. */ PGgeometry geom = (PGgeometry)r.getObject(1); int id = r.getInt(2); System.out.println("Row " + id + ":"); System.out.println(geom.toString()); } s.close(); conn.close(); } catch( Exception e ) { e.printStackTrace(); } } } The "PGgeometry" object is a wrapper object which contains a specific topological geometry object (subclasses of the abstract class "Geometry") depending on the type: Point, LineString, Polygon, MultiPoint, MultiLineString, MultiPolygon. PGgeometry geom = (PGgeometry)r.getObject(1); if( geom.getType() = Geometry.POLYGON ) { Polygon pl = (Polygon)geom.getGeometry(); for( int r = 0; r < pl.numRings(); r++ ) { LinearRing rng = pl.getRing(r); System.out.println("Ring: " + r); for( int p = 0; p < rng.numPoints(); p++ ) { Point pt = rng.getPoint(p); System.out.println("Point: " + p); System.out.println(pt.toString()); } } } The JavaDoc for the extension objects provides a reference for the various data accessor functions in the geometric objects. ... ... ... Current PostgreSQL versions (including 8.0) suffer from a query optimizer weakness regarding TOAST tables. TOAST tables are a kind of "extension room" used to store large (in the sense of data size) values that do not fit into normal data pages (like long texts, images or complex geometries with lots of vertices), see http://www.postgresql.org/docs/8.0/static/storage-toast.html for more information). The problem appears if you happen to have a table with rather large geometries, but not too much rows of them (like a table containing the boundaries of all European countries in high resolution). Then the table itself is small, but it uses lots of TOAST space. In our example case, the table itself had about 80 rows and used only 3 data pages, but the TOAST table used 8225 pages. Now issue a query where you use the geometry operator && to search for a bounding box that matches only very few of those rows. Now the query optimizer sees that the table has only 3 pages and 80 rows. He estimates that a sequential scan on such a small table is much faster than using an index. And so he decides to ignore the GIST index. Usually, this estimation is correct. But in our case, the && operator has to fetch every geometry from disk to compare the bounding boxes, thus reading all TOAST pages, too. To see whether your suffer from this bug, use the "EXPLAIN ANALYZE" postgresql command. For more information and the technical details, you can read the thread on the postgres performance mailing list: http://archives.postgresql.org/pgsql-performance/2005-02/msg00030.php The PostgreSQL people are trying to solve this issue by making the query estimation TOAST-aware. For now, here are two workarounds: The first workaround is to force the query planner to use the index. Send "SET enable_seqscan TO off;" to the server before issuing the query. This basically forces the query planner to avoid sequential scans whenever possible. So it uses the GIST index as usual. But this flag has to be set on every connection, and it causes the query planner to make misestimations in other cases, so you should "SET enable_seqscan TO on;" after the query. The second workaround is to make the sequential scan as fast as the query planner thinks. This can be achieved by creating an additional column that "caches" the bbox, and matching against this. In our example, the commands are like: SELECT addGeometryColumn('myschema','mytable','bbox','4326','GEOMETRY','2'); UPDATE mytable set bbox = Envelope(Force_2d(the_geom)); Now change your query to use the && operator against bbox instead of geom_column, like: SELECT geom_column FROM mytable WHERE bbox && SetSrid('BOX3D(0 0,1 1)'::box3d,4326); Of course, if you change or add rows to mytable, you have to keep the bbox "in sync". The most transparent way to do this would be triggers, but you also can modify your application to keep the bbox column current or run the UPDATE query above after every modification. For tables that are mostly read-only, and where a single index is used for the majority of queries, PostgreSQL offers the CLUSTER command. This command physically reorders all the data rows in the same order as the index criteria, yielding two performance advantages: First, for index range scans, the number of seeks on the data table is drastically reduced. Second, if your working set concentrates to some small intervals on the indices, you have a more efficient caching because the data rows are spread along fewer data pages. (Feel invited to read the CLUSTER command documentation from the PostgreSQL manual at this point.) However, currently PostgreSQL does not allow clustering on PostGIS GIST indices because GIST indices simply ignores NULL values, you get an error message like: lwgeom=# CLUSTER my_geom_index ON my_table; ERROR: cannot cluster when index access method does not handle null values HINT: You may be able to work around this by marking column "the_geom" NOT NULL. As the HINT message tells you, one can work around this deficiency by adding a "not null" constraint to the table: lwgeom=# ALTER TABLE my_table ALTER COLUMN the_geom SET not null; ALTER TABLE Of course, this will not work if you in fact need NULL values in your geometry column. Additionally, you must use the above method to add the constraint, using a CHECK constraint like "ALTER TABLE blubb ADD CHECK (geometry is not null);" will not work. Sometimes, you happen to have 3D or 4D data in your table, but always access it using OpenGIS compliant asText() or asBinary() functions that only output 2D geometries. They do this by internally calling the force_2d() function, which introduces a significant overhead for large geometries. To avoid this overhead, it may be feasible to pre-drop those additional dimensions once and forever: UPDATE mytable SET the_geom = force_2d(the_geom); VACUUM FULL ANALYZE mytable; Note that if you added your geometry column using AddGeometryColumn() there'll be a constraint on geometry dimension. To bypass it you will need to drop the constraint. Remember to update the entry in the geometry_columns table and recreate the constraint afterwards. In case of large tables, it may be wise to divide this UPDATE into smaller portions by constraining the UPDATE to a part of the table via a WHERE clause and your primary key or another feasible criteria, and running a simple "VACUUM;" between your UPDATEs. This drastically reduces the need for temporary disk space. Additionally, if you have mixed dimension geometries, restricting the UPDATE by "WHERE dimension(the_geom)>2" skips re-writing of geometries that already are in 2D. The functions given below are the ones which a user of PostGIS is likely to need. There are other functions which are required support functions to the PostGIS objects which are not of use to a general user. PostGIS has begun a transition from the existing naming convension to an SQL-MM-centric convension. As a result, most of the functions that you know and love have been renamed using the standard spatial type (ST) prefix. Previous functions are still available, though are not listed in this document where updated functions are equivalent. These will be deprecated in a future release. AddGeometryColumn(varchar, varchar, varchar, integer, varchar, integer) Syntax: AddGeometryColumn(<schema_name>, <table_name>, <column_name>, <srid>, <type>, <dimension>). Adds a geometry column to an existing table of attributes. The schema_name is the name of the table schema (unused for pre-schema PostgreSQL installations). The srid must be an integer value reference to an entry in the SPATIAL_REF_SYS table. The type must be an uppercase string corresponding to the geometry type, eg, 'POLYGON' or 'MULTILINESTRING'. DropGeometryColumn(varchar, varchar, varchar) Syntax: DropGeometryColumn(<schema_name>, <table_name>, <column_name>). Remove a geometry column from a spatial table. Note that schema_name will need to match the f_schema_name field of the table's row in the geometry_columns table. ST_SetSRID(geometry, integer) Set the SRID on a geometry to a particular integer value. Useful in constructing bounding boxes for queries. ST_Distance(geometry, geometry) Return the cartesian distance between two geometries in projected units. ST_Equals(geometry, geometry) Returns 1 (TRUE) if the given Geometries are "spatially equal". Use this for a 'better' answer than '='. equals('LINESTRING(0 0, 10 10)','LINESTRING(0 0, 5 5, 10 10)') is true. Performed by the GEOS module OGC SPEC s2.1.1.2 ST_Disjoint(geometry, geometry) Returns 1 (TRUE) if the Geometries are "spatially disjoint". Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 //s2.1.13.3 - a.Relate(b, 'FF*FF****') ST_Intersects(geometry, geometry) Returns 1 (TRUE) if the Geometries "spatially intersect". Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 //s2.1.13.3 - Intersects(g1, g2 ) --> Not (Disjoint(g1, g2 )) ST_Touches(geometry, geometry) Returns 1 (TRUE) if the Geometries "spatially touch". Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 // s2.1.13.3- a.Touches(b) -> (I(a) intersection I(b) = {empty set} ) and (a intersection b) not empty ST_Crosses(geometry, geometry) Returns 1 (TRUE) if the Geometries "spatially cross". Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 // s2.1.13.3 - a.Relate(b, 'T*T******') ST_Within(geometry A, geometry B) Returns 1 (TRUE) if Geometry A is "spatially within" Geometry B. Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 // s2.1.13.3 - a.Relate(b, 'T*F**F***') ST_Overlaps(geometry, geometry) Returns 1 (TRUE) if the Geometries "spatially overlap". Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 // s2.1.13.3 ST_Contains(geometry A, geometry B) Returns 1 (TRUE) if Geometry A "spatially contains" Geometry B. Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 // s2.1.13.3 - same as within(geometry B, geometry A) ST_Intersects(geometry, geometry) Returns 1 (TRUE) if the Geometries "spatially intersect". Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 // s2.1.13.3 - NOT disjoint(geometry, geometry) ST_Relate(geometry, geometry, intersectionPatternMatrix) Returns 1 (TRUE) if this Geometry is spatially related to anotherGeometry, by testing for intersections between the Interior, Boundary and Exterior of the two geometries as specified by the values in the intersectionPatternMatrix. Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is the "allowable" version that returns a boolean, not an integer. OGC SPEC s2.1.1.2 // s2.1.13.3 ST_Relate(geometry, geometry) returns the DE-9IM (dimensionally extended nine-intersection matrix) Performed by the GEOS module Do not call with a GeometryCollection as an argument not in OGC spec, but implied. see s2.1.13.2 ST_Centroid(geometry) Returns the centroid of the geometry as a point. Computation will be more accurate if performed by the GEOS module (enabled at compile time). ST_Area(geometry) Returns the area of the geometry if it is a polygon or multi-polygon. ST_Length(geometry) The length of this Curve in its associated spatial reference. synonym for length2d() OGC SPEC 2.1.5.1 ST_PointOnSurface(geometry) Return a Point guaranteed to lie on the surface Implemented using GEOS OGC SPEC 3.2.14.2 and 3.2.18.2 - ST_Boundary(geometry) Returns the closure of the combinatorial boundary of this Geometry. The combinatorial boundary is defined as described in section 3.12.3.2 of the OGC SPEC. Because the result of this function is a closure, and hence topologically closed, the resulting boundary can be represented using representational geometry primitives as discussed in the OGC SPEC, section 3.12.2. Performed by the GEOS module OGC SPEC s2.1.1.1 ST_Buffer(geometry, double, [integer]) Returns a geometry that represents all points whose distance from this Geometry is less than or equal to distance. Calculations are in the Spatial Reference System of this Geometry. The optional third parameter sets the number of segment used to approximate a quarter circle (defaults to 8). Performed by the GEOS module Do not call with a GeometryCollection as an argument OGC SPEC s2.1.1.3 ST_ConvexHull(geometry) Returns a geometry that represents the convex hull of this Geometry. Performed by the GEOS module OGC SPEC s2.1.1.3 ST_Intersection(geometry, geometry) Returns a geometry that represents the point set intersection of the Geometries. Performed by the GEOS module Do not call with a GeometryCollection as an argument OGC SPEC s2.1.1.3 ST_SymDifference(geometry A, geometry B) Returns a geometry that represents the point set symmetric difference of Geometry A with Geometry B. Performed by the GEOS module Do not call with a GeometryCollection as an argument OGC SPEC s2.1.1.3 ST_Difference(geometry A, geometry B) Returns a geometry that represents the point set difference of Geometry A with Geometry B. Performed by the GEOS module Do not call with a GeometryCollection as an argument OGC SPEC s2.1.1.3 ST_GeomUnion(geometry, geometry) Returns a geometry that represents the point set union of the Geometries. Performed by the GEOS module Do not call with a GeometryCollection as an argument NOTE: this is renamed from "union" because union is an SQL reserved word OGC SPEC s2.1.1.3 ST_Union(geometry set) Returns a geometry that represents the point set union of this all Geometries in given set. Performed by the GEOS module Do not call with a GeometryCollection in the argument set Not explicitly defined in OGC SPEC ST_MemGeomUnion(geometry set) Same as the above, only memory-friendly (uses less memory and more processor time). ST_AsText(geometry) Return the Well-Known Text representation of the geometry. For example: POLYGON(0 0,0 1,1 1,1 0,0 0) OGC SPEC s2.1.1.1 ST_AsBinary(geometry) Returns the geometry in the OGC "well-known-binary" format, using the endian encoding of the server on which the database is running. This is useful in binary cursors to pull data out of the database without converting it to a string representation. OGC SPEC s2.1.1.1 - also see asBinary(<geometry>,'XDR') and asBinary(<geometry>,'NDR') ST_SRID(geometry) Returns the integer SRID number of the spatial reference system of the geometry. OGC SPEC s2.1.1.1 ST_Dimension(geometry) The inherent dimension of this Geometry object, which must be less than or equal to the coordinate dimension. OGC SPEC s2.1.1.1 - returns 0 for points, 1 for lines, 2 for polygons, and the largest dimension of the components of a GEOMETRYCOLLECTION. select dimension('GEOMETRYCOLLECTION(LINESTRING(1 1,0 0),POINT(0 0)'); dimension ----------- 1 ST_Envelope(geometry) Returns a POLYGON representing the bounding box of the geometry. OGC SPEC s2.1.1.1 - The minimum bounding box for this Geometry, returned as a Geometry. The polygon is defined by the corner points of the bounding box ((MINX, MINY), (MAXX, MINY), (MAXX, MAXY), (MINX, MAXY), (MINX, MINY)). NOTE:PostGIS will add a Zmin/Zmax coordinate as well. ST_IsEmpty(geometry) Returns 1 (TRUE) if this Geometry is the empty geometry . If true, then this Geometry represents the empty point set - i.e. GEOMETRYCOLLECTION(EMPTY). OGC SPEC s2.1.1.1 ST_IsSimple(geometry)