Osm2pgsql v2 Manual

Introduction

This is the manual for version 2.x.y of osm2pgsql. If you are running an older version of osm2pgsql, refer to the manual v1.

Osm2pgsql is used to import OSM data into a PostgreSQL/PostGIS database for rendering into maps and many other uses. Usually it is only part of a toolchain, for instance other software is needed for the actual rendering (i.e. turning the data into a map) or delivery of the maps to the user etc.

Osm2pgsql is a fairly complex piece of software and it interacts with the database system and other pieces of the toolchain in complex ways. It will take a while until you get some experience with it. It is strongly recommended that you try out osm2pgsql with small extracts of the OSM data, for instance the data for your city. Do not start with importing data for the whole planet, it is easy to get something wrong and it will break after processing the data for hours or days. You can save yourself a lot of trouble doing some trial runs starting with small extracts and working your way up, observing memory and disk usage along the way.

It helps to be familiar with the PostgreSQL database system and the PostGIS extension to it as well as the SQL database query language. Some knowledge of the Lua language is also useful.

This manual always documents the current version of osm2pgsql. If same information is only valid in certain versions, the section will have a note like this: Version >= 2.0.0 This manual is only for version 2 and above, refer to the manual v1 for older versions.

Sections labelled Experimental describe new features which might change at any point without notice. We encourage you to experiment with them and report how they work for you, but don’t rely on them for production use.

It is recommended that you always use the newest released version of osm2pgsql. Earlier versions sometimes contain bugs that have long since been fixed.

System Requirements

Operating System

Osm2pgsql works on Linux, Windows, macOS, and other systems. Only 64bit systems are supported.

Osm2pgsql is developed on Linux and most of the developers don’t have experience with running it on anything but Linux, so it probably functions best on that platform. This documentation is also somewhat geared towards Linux users. That being said, we strive to make the software work well on all systems. Please report any problems you might have.

Read the installation instructions for details on how to install osm2pgsql on your system.

Main Memory

Memory requirements for your system will vary widely depending on the size of your input file. Is it city-sized extract or the whole planet? As a rule of thumb you need at least as much main memory as the PBF file with the OSM data is large. So for a planet file you currently need at least 64 GB RAM, better are 128 GB. Osm2pgsql will not work with less than 2 GB RAM.

More memory can be used as cache by the system, osm2pgsql, or PostgreSQL and speed up processing a lot.

Disk

You are strongly encouraged to use a SSD (NVMe if possible) for your database. This will be much faster than traditional spinning hard disks.

Requirements for your system will vary widely depending on

• the amount of data you want to store (city-sized extract or the whole planet?)
• whether or not you want to update the data regularly

See the Sizing appendix for some ideas on how large a disk you might need.

Database Software

You need the PostgreSQL database system with the PostGIS extension installed.

Osm2pgsql aims to support all PostgreSQL and PostGIS versions that are currently supported by their respective maintainers. Currently PostgreSQL versions 9.6 and above and PostGIS versions 2.5 and above are supported. (Earlier versions might work but are not tested any more.) PostgreSQL version 11 or above is recommended.

In some cases older versions of osm2pgsql have problems with newer database software versions. You should always run the newest released osm2pgsql version which should ensure you get any fixes we have done to make osm2pgsql work well with any PostgreSQL version.

Osm2pgsql does not work with database systems other than PostgreSQL. The PostgreSQL/PostGIS combination is unique in its capabilities and we are using some of their special features. We are not planning to support any other database systems. There are some database systems out there which claim compatibility with PostgreSQL, they might work or they might not work. Please tell us if you have any experience with them.

Lua Scripting Language

Osm2pgsql requires the use of the Lua scripting language. If available osm2pgsql can also be compiled using the Lua JIT (just in time) compiler. Use of Lua JIT is recommended, especially for larger systems, because it will speed up processing.

Security Note: Lua scripts can do basically anything on your computer that the user running osm2pgsql is allowed to do, such as reading and writing files, opening network connections etc. This makes the Lua config files really versatile and allows lots of great functionality. But you should never use a Lua configuration file from an unknown source without checking it.

Preparing the Database

Before you can import any OSM data into a database, you need a database.

Installing PostgreSQL/PostGIS

You need the PostgreSQL database software and the PostGIS plugin for the database. Please read the respective documentation on how to install it. On Linux this can almost always be done with the package manager of your distribution.

• PostgreSQL download page
• PostGIS install page

Creating a Database

To create a database that can be used by osm2pgsql follow these steps:

1. Create a database user that osm2pgsql will use. This user doesn’t need any special rights. We’ll use osmuser here.
2. Create a database that osm2pgsql will use belonging to the user you just created. We’ll use osm as a name here.
3. Enable the postgis extension in the newly created database.
4. Optionally enable the hstore extension in the database, it is used in some popular configurations, but not needed by osm2pgsql itself.

On a typical Linux system you’ll have a system user called postgres which has admin privileges for the database system. We’ll use that user for these steps.

Here are typical commands used:

sudo -u postgres createuser osmuser
sudo -u postgres createdb --encoding=UTF8 --owner=osmuser osm
sudo -u postgres psql osm --command='CREATE EXTENSION postgis;'
sudo -u postgres psql osm --command='CREATE EXTENSION hstore;'

Security Considerations

Osm2pgsql does not need any special database rights, it doesn’t need superuser status and doesn’t need to create databases or roles. You should create a database user for the specific use by osm2pgsql which should not have any special PostgreSQL privileges.

This manual assumes that you have ‘peer’ authentication configured when using a local database. That means a local user may connect to the database with its own username without needing to type a password. This authentication method is the default on Debian/Ubuntu-based distributions. Never configure ‘trust’ authentication where all local users can connect as any user to the database.

Any osm2pgsql setup will need a database to work on. You should create this as PostgreSQL superuser and change ownership (with --owner option on the createdb command or an OWNER= clause on the CREATE DATABASE SQL command) to the user osm2pgsql is using. This way the database user that osm2pgsql uses doesn’t need database creation privileges.

Typical osm2pgsql setups need the postgis and hstore extensions to be enabled in the database. To install these you need superuser privileges in the database. Enable them (with CREATE EXTENSION) as PostgreSQL superuser on the database that osm2pgsql is using before you run osm2pgsql.

Of course osm2pgsql needs to be able to create tables and write to the database. Usually it can do this as owner of the database created for it. Using the data, on the other hand, doesn’t need any of those rights. So the map rendering software you are using, for instance, usually only needs to read the data. It is recommended that you run these as a different database user, distinct from the database user osm2pgsql is using and only give that user SELECT rights (with the GRANT command).

If you are using a security scheme based on database schemas in your database you can use the --schema, --middle-schema and --output-pgsql-schema options and the schema table option in the flex output, respectively, to tell osm2pgsql to load data into specific schemas. You have to create those schemas and give them the correct rights before running osm2pgsql.

Before PostgreSQL 15 all database users could add objects (such as tables and indexes) to the public schema by default. Since PostgreSQL 15, by default, only the owner of the database is allowed to do this. If osm2pgsql is using a database user that’s not the owner of the database, you have to grant this user CREATE rights on the public schema of the database, or you have to configure osm2pgsql to use a different schema as described above. See the PostgreSQL manual for the details.

Encoding

OpenStreetMap data is from all around the world, it always uses UTF-8 encoding. Osm2pgsql will write the data as is into the database, so it has to be in UTF-8 encoding, too.

On any modern system the default encoding for new databases should be UTF-8, but to make sure, you can use the -E UTF8 or --encoding=UTF8 options when creating the database for osm2pgsql with createdb.

Tuning the PostgreSQL Server

Usual installs of the PostgreSQL server come with a default configuration that is not well tuned for large databases. You should change these settings in postgresql.conf and restart PostgreSQL before running osm2pgsql, otherwise your system will be much slower than necessary.

The following settings are geared towards a system with 128GB RAM and a fast SSD. The values in the second column are suggestions to provide a good starting point for a typical setup, you might have to adjust them for your use case. The value in the third column is the default set by PostgreSQL 15.

Here are the proposed settings for copy-and-paste into a config file:

shared_buffers = 1GB
work_mem = 50MB
maintenance_work_mem = 10GB
autovacuum_work_mem = 2GB
wal_level = minimal
checkpoint_timeout = 60min
max_wal_size = 10GB
checkpoint_completion_target = 0.9
max_wal_senders = 0
random_page_cost = 1.0

Increasing values for max_wal_size and checkpoint_timeout means that PostgreSQL needs to run checkpoints less often but it can require additional space on your disk and increases time required for Point in Time Recovery (PITR) restores. Monitor the PostgreSQL logs for warnings indicating checkpoints are occurring too frequently: HINT: Consider increasing the configuration parameter "max_wal_size".

Autovacuum must not be switched off because it ensures that the tables are frequently analysed. If your machine has very little memory, you might consider setting autovacuum_max_workers = 1 and reduce autovacuum_work_mem even further. This will reduce the amount of memory that autovacuum takes away from the import process.

For additional details see the Server Configuration chapter and Populating a Database in the Performance Tips chapter in the PostgreSQL documentation.

Expert Tuning

The suggestions in this section are potentially dangerous and are not suitable for all environments. These settings can cause crashes and/or corruption. Corruption in a PostgreSQL instance can lead to a “bricked” instance affecting all databases in the instance.

Additional information is on the PostgreSQL wiki: Tuning Your PostgreSQL Server. The section titled synchronous_commit contains important information to the synchronous_commit and fsync settings.

Using a Template Database

Databases are actually created in PostgreSQL by copying a template database. If you don’t specify a database to copy from, the template1 database is used. PostgreSQL allows you to change template1 or to create additional template databases. If you create a lot of databases for use with osm2pgsql, you can do initializations like CREATE EXTENSTION postgis; once in a template database and they will be available in any database you create from them.

See the PostgreSQL manual for details.

Database Maintainance

PostgreSQL tables and indexes that change a lot tend to get larger and larger over time. This can happen even with autovacuum running. This does not affect you if you just import OSM data, but when you update it regularly, you have to keep this in mind. You might want to occasionally re-import the database from scratch.

This is not something specific to osm2pgsql, but a general PostgreSQL issue. If you are running a production database, you should inform yourself about possible issues and what to do about them in the PostgreSQL literature.

Geometry Processing

An important part of what osm2pgsql does is creating geometries from OSM data. In OSM only nodes have a location, ways get their geometry from member nodes and relations get their geometry from member nodes and ways. Osm2pgsql assembles all the data from the related objects into valid geometries.

Geometry Types

The geometry types supported by PostGIS are from the Simple Features defined by the OpenGIS Consortium (OGC). Osm2pgsql creates geometries of the following types from OSM data:

Single vs. Multi Geometries

Generally osm2pgsql will create the simplest geometry it can. Nodes will turn into Points, ways into LineStrings or Polygons. A multipolygon relation can be turned into a Polygon or MultiPolygon, depending on whether it has one or more outer rings. Similarly, a route relation can be turned into a LineString if the route is connected from start to finish or a MultiLineString if it is unconnected or there are places, where the route splits up.

In some cases osm2pgsql will split up Multi* geometries into simple geometries and add each one in its own database row. This can make rendering faster, because the renderer can deal with several smaller geometries instead of having to handle one large geometry. But, depending on what you are doing with the data, it can also lead to problems. This blogpost has some deeper discussion of this issue. See the flex and pgsql output chapters for details on how to configure this. It will also mean that your id columns are not unique, because there are now multiple rows created from the same OSM object. See the Primary Keys and Unique IDs section for an option how to work around this.

When using the flex output, you can decide yourself what geometries to create using the as_point(), as_linestring(), as_polygon(), as_multipoint(), as_multilinestring(), as_multipolygon(), and as_geometrycollection() functions. See the Flex Output chapter for details.

Geometry Validity

Point geometries are always valid (as long as the coordinates are inside the correct range). LineString geometries are valid if they have at least two distinct points. Osm2pgsql will collapse consecutive indentical points in a linestring into a single point. Note that a line crossing itself is still valid and not a problem.

Validity is more complex for Polygon and MultiPolygon geometries: There are multiple ways how such a geometry can be invalid. For instance, if the boundary of a polygon is drawn in a figure eight, the result will not be a valid polygon. The database will happily store such invalid polygons, but this can lead to problems later, when you try to draw them or do calculations based on the invalid geometry (such as calculating the area).

You can use the Areas view of the OpenStreetMap inspector to help diagnose problems with multipolygons.

Osm2pgsql makes sure that there are no invalid geometries in the database, either by not importing them in the first place or by using an ST_IsValid() check after import. You’ll either get NULL in your geometry columns instead or the row is not inserted at all (depending on config).

The transform() function in Lua config files projects a geometry into a different SRS. In special cases this can make the geometry invalid, for instance when two distinct points are projected onto the same point.

Processing of Nodes

Node geometries are always converted into Point geometries.

Processing of Ways

Depending on the tags, OSM ways model either a LineString or a Polygon, or both! A way tagged with highway=primary is usually a linear feature, a way tagged landuse=farmland is usually a polygon feature. If a way with polygon type tags is not closed, the geometry is invalid, this is an error and the object is ignored. For some tags, like man_made=pier non-closed ways are linear features and closed ways are polygon features.

If a mapper wants to override how a way should be interpreted, they can use the area tag: The tag area=yes turns a normally linear feature into a polygon feature, for instance it turns a pedestrian street (highway=pedestrian) into a pedestrian area. The tag area=no turns a polygon feature into a linear feature.

There is no definite list which tags indicate a linear or polygon feature. Osm2pgsql lets the user decide. It depends on your chosen output (see next chapter) how to configure this. Some of the example config files have lists that should cover most of the commonly used tags, but you might have to extend the lists if you are using more unusual tags.

Osm2pgsql can split up long LineStrings created from ways into smaller segments. This can make rendering of tiles faster, because smaller geometries need to be retrieved from the database when rendering a specific tile. The pgsql output always splits up long LineStrings, in latlong projection, lines will not be longer than 1°, in Web Mercator lines will not be longer than 100,000 units (about 100,000 meters at the equator). In the flex output you hae full control over line splitting by using (or not using) the segmentize() function. See also the Single vs. Multi Geometries section above.

When using the flex output, you can decide yourself what geometries to create from a way using the as_linestring(), or as_polygon() functions. See the Flex Output chapter for details.

Processing of Relations

Relations come in many variations and they can be used for all sorts of geometries. Usually it depends on the type tag of a relation what kind of geometry it should have:

When using the flex output, you can decide yourself what geometries to create from a way using the as_multipoint(), as_multilinestring(), or as_multipolygon() functions. Also supported now is the as_geometrycollection() function which creates GeometryCollection from all member nodes and ways of a relation (relation members are ignored).

If you are using the old “C transform” of the pgsql output, the geometry types for relations of type multipolygon, boundary, and route are hardcoded. If you are using the “Lua transform” of the pgsql output you can configure them somewhat.

Note that osm2pgsql will ignore the roles (inner and outer) on multipolygon and boundary relations when assembling multipolygons, because the roles are sometimes wrong or missing.

Relations with more than 32767 members are ignored by osm2pgsql. This protects osm2pgsql and any post-processing against bad data. The OSM database limits the number of members to 32000, but historically more members were allowed, so keep this in mind if you are working with older OSM data.

Handling of Incomplete OSM Data

Sometimes you will feed incomplete OSM data to osm2pgsql. Most often this will happen when you use geographical extracts, either data you downloaded from somewhere or created yourself. Incomplete data, in this case, means that some member nodes of ways or members of relations are missing. Often this can not be avoided when creating an extract, you just have to put that cut somewhere.

When osm2pgsql encounters incomplete OSM data it will still try to do its best to use it. Ways missing some nodes will be shortened to the available part. Multipolygons might be missing some parts. In most cases this will work well (if your extract has been created with a sufficiently large buffer), but sometimes this will lead to wrong results. In the worst case, if a complete outer ring of a multipolygon is missing, the multipolygon will appear “inverted”, with outer and inner rings switching their roles.

Unfortunately there isn’t much that osm2pgsql (or anybody) can do to improve this, this is just the nature of OSM data.

In debug mode osm2pgsql will log the ids of missing nodes and the ways they are missing from.

Projections

Osm2pgsql can create geometries in many projections. If you are using the pgsql output, the projection can be chosen with command line options. When using the flex output, the projections are specified in the Lua style file. The default is always “Web Mercator”.

When using the flex output, osm2pgsql will usually magically transform any geometry you are writing into a database table into the projection you defined your tables with. But you can use the transform() function on the geometry to force a certain transformation. This is useful, for instance, if you want to calculate the area of a polygon in a specific projection. See the Flex Output chapter for details.

	Latlong (WGS84) EPSG:4326 The original latitude & longitude coordinates from OpenStreetMap in the WGS84 coordinate reference system. This is typically chosen if you want to do some kind of analytics on the data or reproject it later.
	Web Mercator EPSG:3857 This is the projection used most often for tiled web maps. It is the default in osm2pgsql. Data beyond about 85° North and South will be cut off, because it can not be represented in this projection.
	Other Projections If osm2pgsql was compiled with support for the PROJ library, it supports all projections supported by that library. Call osm2pgsql --version to see whether your binary was compiled with PROJ and with which version.

Note that mapping styles often depend on the projection used. Most mapping style configurations will enable or disable certain rendering styles depending on the map scale or zoom level. But a meaningful scale will depend on the projection. Most styles you encounter are probably made for Web Mercator and will need to be changed if you want to use them for other projections.

Running osm2pgsql

Basic command line operation

Osm2pgsql can work in one of two ways: Import only or Import and Update.

If you are new to osm2pgsql we recommend you try the import only approach first and use a small extract of the OSM data.

Import Only

OSM data is imported once into the database and will not change afterwards. If you want to update the data, you have to delete it and do a full re-import. This approach is used when updates aren’t needed or only happen rarely. It is also sometimes the only option, for instance when you are using extracts for which change files are not available. This is also a possible approach if disk space is tight, because you don’t need to store data needed only for updates.

In this mode osm2pgsql is used with the -c, --create command line option. This is also the default mode. The following command lines are equivalent:

osm2pgsql -c OSMFILE
osm2pgsql --create OSMFILE
osm2pgsql OSMFILE

In case the system doesn’t have much main memory, you can add the -s, --slim and --drop options. In this case less main memory is used, instead more data is stored in the database. This makes the import much slower, though. See the chapter Middle for details on these options.

Import and Update

In this approach OSM data is imported once and afterwards updated more or less regularly from OSM change files. OSM offers minutely, hourly, and daily change files. This mode is used when regular updates are desired and change files are available.

In this mode osm2pgsql is used the first time with the -c, --create command line option (this is also the default mode) and, additionally the -s, --slim options. The following command lines are equivalent:

osm2pgsql -c -s OSMFILE
osm2pgsql --create --slim OSMFILE
osm2pgsql --slim OSMFILE

For the update runs the -a, --append and -s, --slim options must be used. The following command lines are equivalent:

osm2pgsql -a -s OSMFILE
osm2pgsql --append --slim OSMFILE

The OSMFILE in this case will usually be an OSM change file (with suffix .osc or .osc.gz).

You can not use replication diffs downloaded from planet.osm.org directly with osm2pgsql, see Updating an Existing Database for details.

This approach needs more disk space for your database than the “Import Only” approach, because all the information necessary for the updates must be stored somewhere.

Usually you will need to use at least the -C, --cache or -F, --flat-nodes command line options when doing imports and updates. See the chapter Middle for details.

Osm2pgsql needs the tables, indexes, etc. that it creates to be where it expects them to be. Do not rename of otherwise change anything created by osm2pgsql!

Getting Help or Version

To get help or the program version call osm2pgsql with one of the following options:

Logging

Osm2pgsql will write information about what it is doing to the console (to STDERR). If you’d rather want this information in a file, use the output redirection in your shell (osm2pgsql ... 2>osm2pgsql.log).

Several command line options allow you to change what will be logged and how:

Database Connection

In create and append mode you have to tell osm2pgsql which database to access. If left unset, it will attempt to connect to the default database (usually the username) using a unix domain socket. Most usage only requires setting -d, --database.

Note that the -W or --password option does not take a password as argument! It just makes sure that osm2pgsql will ask for a password interactively.

You can also use libpq environment variables to set connection parameters. For a full list of available parameters, please consult the PostgreSQL documentation.

When you need a password for your database connection and want to run osm2pgsql inside scripts, then use a pgpass file with appropriate permissions to store the password. All other methods of giving the password to osm2pgsql are inherently insecure. You can either put a .pgpass file in the user’s home directory or supply its location through the PGPASSFILE environment variable.

Instead of specifying a database name with the -d, --database option you can also specify a connection string in the form of a keyword/value connection string (something like host=localhost port=5432 dbname=mydb) or a URI (postgresql://[user[:password]@][netloc][:port][,...][/dbname][?param1=value1&...]) See the PostgreSQL documentation for details.

Processing the OSM Data

Osm2pgsql processing can be separated into multiple steps:

1. The Input reads the OSM data from the OSM file.
2. The Middle stores all objects and keeps track of relationships between objects.
3. The Output transforms the data and loads it into the database.

This is, of course, a somewhat simplified view, but it is enough to understand the operation of the program. The following sections will describe each of the steps in more detail.

The Input

Depending on the operational mode your input files are either

• OSM data files (in create mode), or
• OSM change files (in append mode)

Usually osm2pgsql will autodetect the file format, but see the -r, --input-reader option below. Osm2pgsql can not work with OSM history files.

OSM data files are almost always sorted, first nodes in order of their ids, then ways in order of their ids, then relations in order of their ids. The planet files, change files, and usual extracts all follow this convention.

Osm2pgsql can only read OSM files ordered in this way. This allows some optimizations in the code which speed up the normal processing.

See the Appendix A for more information on how to get and prepare OSM data for use with osm2pgsql.

Use of the -b, --bbox option is not recommended; it is a crude way of limiting the amount of data loaded into the database and it will not always do what you expect it to do, especially at the boundaries of the bounding box. If you use it, choose a bounding box that is larger than your actual area of interest. A better option is to create an extract of the data before using osm2pgsql. See Appendix A for options.

Working with Multiple Input Files

Usually you are using osm2pgsql with a single input file.

Osm2pgsql can read multiple input files at once, merging the data from the input files ignoring any duplicate data. For this to work the input files must all have their data from the same point in time. You can use this to import two or more geographical extracts into the same database. If the extracts are from different points in time and contain different versions of the same object, this will fail!

Do not use multiple change files as input in append mode, merge and simplify them first.

The Middle

The middle keeps track of all OSM objects read by osm2pgsql and the relationships between those objects. It knows, for instance, which ways are used by which nodes, or which members a relation has. It also keeps track of all node locations. This information is necessary to build way geometries from way nodes and relation geometries from members and it is necessary when updating data, because OSM change files only contain changes objects themselves and not all the related objects needed for creating an objects geometry.

More details are in its own chapter.

The Outputs

Osm2pgsql imports OSM data into a PostgreSQL database. How it does this is governed by the output (sometimes called a backend). Several outputs for different use cases are available:

The flex Output

This is the most modern and most flexible output option. If you are starting a new project, use this output. Future improvements to osm2pgsql will only be available in this output.

Unlike all the other output options there is almost no limit to how the OSM data can be imported into the database. You can decide which OSM objects should be written to which columns in which database tables. And you can define any transformations to the data you need, for instance to unify a complex tagging schema into a simpler schema if that’s enough for your use case.

This output is described in detail in its own chapter.

The pgsql Output

The pgsql output is the original output. It is now deprecated but still widely used. Many tutorials you find on the Internet only describe this output. It is quite limited in how the data can be written to the database, but many setups still use it.

This output comes in two “flavours”: With the original “C transformation” and with the somewhat newer “Lua transformation” which allows some changes to the data before it is imported.

This output is described in detail in its own chapter.

The null Output

The null output doesn’t write the data anywhere. It is used for testing and benchmarking, not for normal operation. If --slim is used with the null output, the middle tables are still generated.

Here are the command line options pertaining to the outputs (see later chapters for command line options only used for specific outputs):

Environment Variables

Osm2pgsql itself doesn’t interpret any environment variables, but several of the libraries it uses do.

• The PostgreSQL database access library (libpq) understands many environment variables.
• The libosmium library has some internal settings you can change.
• If osm2pgsql was compiled with the PROJ library, you can use various environment variables to control the behaviour of the library.

You can access environment variables from Lua config scripts with os.getenv("VAR").

The Flex Output

The flex output, as the name suggests, allows for a flexible configuration that tells osm2pgsql what OSM data to store in your database and exactly where and how. It is configured through a Lua file which

• defines the structure of the output tables and
• defines functions to map the OSM data to the database data format

Use the -S, --style=FILE option to specify the name of the Lua file along with the -O flex or --output=flex option to specify the use of the flex output.

The flex output is much more capable than the legacy pgsql, which will be removed at some point. Use the flex output for any new projects and switch old projects over.

The flex style file is a Lua script. You can use all the power of the Lua language. It gives you a lot of freedom to write complex preprocessing scripts that might even use external libraries to extend the capabilities of osm2pgsql. But it also means that the scripts may mess with any part of your system when written badly. Only run Lua scripts from trusted sources!

This description assumes that you are somewhat familiar with the Lua language, but it is pretty easy to pick up the basics and you can use the example config files in the flex-config directory which contain lots of comments to get you started.

All configuration is done through the osm2pgsql global object in Lua. It has the following fields and functions:

Osm2pgsql also provides some additional functions in the Lua helper library described in Appendix B.

Defining a Table

Usually you want to define one or more database tables where your data should end up. This is done with the osm2pgsql.define_table() function or, more commonly, with one of the slightly more convenient functions osm2pgsql.define_(node|way|relation|area)_table(). In create mode, osm2pgsql will create those tables for you in the database.

Basic Table Definition

The simple way to define a table looks like this:

osm2pgsql.define_(node|way|relation|area)_table(NAME, COLUMNS[, OPTIONS])

Here NAME is the name of the table, COLUMNS is a list of Lua tables describing the columns as documented below. OPTIONS is a Lua table with options for the table as a whole. An example might be more helpful:

local restaurants = osm2pgsql.define_node_table('restaurants', {
    { column = 'name', type = 'text' },
    { column = 'tags', type = 'jsonb' },
    { column = 'geom', type = 'point' }
})

In this case we are creating a table that is intended to be filled with OSM nodes, the table called restaurants will be created in the database with four columns: A name column of type text (which will presumably later be filled with the name of the restaurant), a column called tags with type jsonb (which will presumable be filled later with all tags of a node), a column called geom which will contain the Point geometry of the node and an Id column called node_id.

Each table is either a node table, way table, relation table, or area table. This means that the data for that table comes primarily from a node, way, relation, or area, respectively. Osm2pgsql makes sure that the OSM object id will be stored in the table so that later updates to those OSM objects (or deletions) will be properly reflected in the tables. Area tables are special, they can contain data derived from ways and from (multipolygon) relations.

Advanced Table Definition

Sometimes the osm2pgsql.define_(node|way|relation|area)_table() functions are a bit too restrictive, for instance if you want more control over the type and naming of the Id column(s). In this case you can use the function osm2pgsql.define_table().

Here are the available OPTIONS for the osm2pgsql.define_table(OPTIONS) function. You can use the same options on the osm2pgsql.define_(node|way|relation|area)_table() functions, except the name and columns options.

All the osm2pgsql.define*table() functions return a database table Lua object. You can call the following functions on it:

Id Handling

Id columns allows osm2pgsql to track which database table entries have been generated by which objects. When objects change or are deleted, osm2pgsql uses the ids to update or remove all existing rows from the database with those ids.

If you are using the osm2pgsql.define_(node|way|relation|area)_table() convenience functions, osm2pgsql will automatically create an id column named (node|way|relation|area)_id, respectively.

If you want more control over the id column(s), use the osm2pgsql.define_table() function. You can then use the ids option to define how the id column(s) should look like. To generate the same “restaurants” table described above, the osm2pgsql.define_table() call will look like this:

local restaurants = osm2pgsql.define_table({
    name = 'restaurants',
    ids = { type = 'node', id_column = 'node_id' },
    columns = {
        { column = 'name', type = 'text' },
        { column = 'tags', type = 'jsonb' },
        { column = 'geom', type = 'point' }
}})

If you don’t have an ids field, the table is generated without Id. Tables without Id can not be updated, so you can fill them in create mode, but they will not work in append mode.

The following values are allowed for the type of the ids field:

The any type is for tables that can store any type of OSM object (nodes, ways, or relations). There are two ways the id can be stored:

1. If you have a type_column setting in your ids field, it will store the type of the object in an additional char(1) column as N, W, or R.
2. If you don’t have a type_column, the id of nodes stays the same (so they are positive), way ids will be stored as negative numbers and relation ids are stored as negative numbers and 1e17 is subtracted from them. This results in distinct ranges for all ids so they can be kept apart. (This is the same transformation that the Imposm program uses.)

Osm2pgsql will only create these Id indexes if an updatable database is created, i.e. if osm2pgsql is run with --slim (but not --drop). You can set the optional field create_index in the ids setting to 'always' to force osm2pgsql to always create this index, even in non-updatable databases (the default is 'auto', only create the index if needed for updating).

Generalized data (see Generalization chapter) is sometimes stored in tables indexed by x, y tile coordinates. For such tables use the tile value for the ids field. Two columns called x and y with SQL type int will be created (it is not possible to change those column names or the type). In “create” mode, if the database is updatable or when the create_index option is set to always, an index will automatically be generated on those columns after the generalization step is run with osm2pgsql-gen.

Unique Ids

It is often desirable to have a unique PRIMARY KEY on database tables. Many programs need this.

There seems to be a natural unique key, the OSM node, way, or relation ID the data came from. But there is a problem with that: It depends on the Lua config file whether a key is unique or not. Nothing prevents you from inserting multiple rows into the database with the same id. It often makes sense in fact, for instance when splitting a multipolygon into its constituent polygons.

If you need unique keys on your database tables there are two options: Using those natural keys and making sure that you don’t have duplicate entries. Or adding an additional ID column. The latter is easier to do and will work in all cases, but it adds some overhead.

Using Natural Keys for Unique Ids

To use OSM IDs as primary keys, you have to make sure that you only ever add a single row per OSM object to an output table, i.e. do not call insert multiple times on the same table for the same OSM object.

Set the create_index option in the ids setting (see above) to 'unique' to get a UNIQUE index instead of the normal non-unique index for the ID column.

Using an Additional ID Column

PostgreSQL has the somewhat magic “serial” data type. If you use that datatype in a column definition, PostgreSQL will add an integer column to the table and automatically fill it with an autoincrementing value.

In the flex config you can add such a column to your tables with something like this:

...
{ column = 'id', sql_type = 'serial', create_only = true },
...

The create_only tells osm2pgsql that it should create this column but not try to fill it when adding rows (because PostgreSQL does it for us).

You probably also want an index on this column. See the chapter on Defining Indexes on how to create this index from osm2pgsql.

Since PostgreSQL 10 you can use the GENERATED ... AS IDENTITY clause instead of the SERIAL type which does something very similar, although using anything but a proper PostgreSQL type here is not officially supported.

Defining Columns

In the table definitions the columns are specified as a list of Lua tables with the following keys:

The type field describes the type of the column from the point of view of osm2pgsql, the sql_type describes the type of the column from the point of view of the PostgreSQL database. Usually they are either the same or the SQL type is derived directly from the type according to the following table. But it is possible to set them individually for special cases.

The SRID for the geometry SQL types comes from the projection parameter.

For special cases you usually want to keep the type field unset and only set the sql_type field. So if you want to have an array of integer column, for instance, set only the sql_type to int[]. The type field will default to text which means you have to create the text representation of your array in the form that PostgreSQL expects it.

For details on how the data is converted depending on the type, see the section on Type Conversions.

The content of the sql_type field is not checked by osm2pgsql, it is passed on to PostgreSQL as is. Do not set this to anything else but a valid PostgreSQL type. Correct use of sql_type is not easy. Only use sql_type if you have some familiarity with PostgreSQL types and how they are converted from/to text. If you get this wrong you’ll get error messages about “Ending COPY mode” that are hard to interpret. Considering using the json or jsonb type instead, for which osm2pgsql does the correct conversions.

Defining Geometry Columns

Most tables will have a geometry column. The types of the geometry column possible depend on the type of the input data. For node tables you are pretty much restricted to point geometries, but there is a variety of options for relation tables for instance.

You can have zero, one or more geometry columns. An index will only be built automatically for the first (or only) geometry column you define. The table will be clustered by the first (or only) geometry column (unless disabled).

The supported geometry types are:

By default geometry columns will be created in web mercator (EPSG 3857). To change this, set the projection parameter of the column to the EPSG code you want (or one of the strings latlon(g), WGS84, or merc(ator), case is ignored).

Geometry columns can have expire configurations attached to them. See the section on Defining and Using Expire Outputs for details.

Defining Indexes

Osm2pgsql will always create indexes on the id column(s) of all tables if the database is updateable (i.e. in slim mode), because it needs those indexes to update the database. You can not control those indexes with the settings described in this section.

To define indexes, set the indexes field of the table definition to an array of Lua tables. If the array is empty, no indexes are created for this table (except possibly an index on the id column(s)). If there is no indexes field (or if it is set to nil) a GIST index will be created on the first (or only) geometry column of this table.

The following fields can be set in an index definition. You have to set at least the method and either column or expression.

If you need an index that can not be expressed with these definitions, you have to create it yourself using the SQL CREATE INDEX command after osm2pgsql has finished its job.

Defining and Using Expire Outputs

When osm2pgsql is working in ‘append’ mode, i.e. when it is updating an existing database from OSM change files, it can figure out which changes will potentially affect which Web Mercator tiles, so that you can re-render those tiles later. See the Expire chapter for some general information about expiry.

The list of tile coordinates can be written to a file and/or to a database table. Use the osm2pgsql.define_expire_output() Lua function to define an expire output. The function has a single paramater, a Lua table with the following fields:

You have to supply the filename and/or the table (possibly with schema). You can provide either or both. The database table will be created for you if it isn’t available already.

Defined expire outputs can then be used in table definitions. Geometry columns using Web Mercator projection (EPSG 3857) can have an expire field which specifies which expire outputs should be triggered by changes affecting this geometry.

For an example showing how the expire output works, see the flex-config/expire.lua example config file.

Processing Callbacks

You are expected to define one or more of the following functions:

They all have a single argument of type table (here called object) and no return value. If you are not interested in all object types, you do not have to supply all the functions.

Usually you are only interested in tagged objects, i.e. OSM objects that have at least one tag, so you will only define one or more of the first three functions. But if you are interested in untagged objects also, define the last three functions. If you want to have the same behaviour for untagged and tagged objects, you can define the functions to be the same.

These functions are called for each new or modified OSM object in the input file. No function is called for deleted objects, osm2pgsql will automatically delete all data in your database tables that were derived from deleted objects. Modifications are handled as deletions followed by creation of a “new” object, for which the functions are called.

You can do anything in those processing functions to decide what to do with this data. If you are not interested in that OSM object, simply return from the function. If you want to add the OSM object to some table call the insert() function on that table.

The parameter table (object) has the following fields and functions:

These are only available if the OSM input file actually contains those fields. When handling updates they are only included if the middle table contain this data (i.e. when -x|--extra-attributes option was used).

The as_* functions will return a NULL geometry if the geometry can not be created for some reason, for instance a polygon can only be created from closed ways. This can also happen if your input data is incomplete, for instance when nodes referenced from a way are missing. You can check the geometry object for is_null(), for example object:as_multipolygon():is_null().

The as_linestring() and as_polygon() functions can only be used on ways.

The as_multipoint() function can be used on nodes and relations. For nodes it will always return a point geometry, for relations a point or multipoint geometry with all available node members.

The as_multilinestring() and as_multipolygon() functions, on the other hand, can be used for ways and for relations. The latter will either return a linestring/polygon or a multilinestring/multipolygon, depending on whether the result is a single geometry or a multi-geometry.

If you need all geometries of a relation, you can use as_geometrycollection(). It will contain all geometries which can be generated from node and way members of the relation in order of those members. Members of type “relation” are ignored. Node members will result in a point geometry, way members will result in a linestring geometry. Geometries that can’t be built are missing. (You can detect this by counting the number of geometries with num_geometries() and comparing that to the number of members of type node and relation.) If no valid geometry can be created, so if the geometry collection would be empty, a null geometry is returned instead.

The after Callback Functions

There are three additional processing functions that are sometimes useful:

OSM data files contain objects in the order nodes, then ways, then relations. This means you will first get all the process_(untagged_)node calls, then the after_nodes call, then all the process_(untagged_)way calls, then the after_ways call, then all the process_(untagged_)relation calls, and lastly the after_relationscall.

The insert() Function

Use the insert() function to add data to a previously defined table:

-- definition of the table:
local table_pois = osm2pgsql.define_node_table('pois', {
    { column = 'tags', type = 'jsonb' },
    { column = 'name', type = 'text' },
    { column = 'geom', type = 'point' },
})
...
function osm2pgsql.process_node(object)
...
    table_pois:insert({
        tags = object.tags,
        name = object.tags.name,
        geom = object:as_point()
    })
...
end

The insert() function takes a single table parameter, that describes what to fill into all the database columns. Any column not mentioned will be set to NULL. It returns true if the insert was successful.

Note that you can’t set the object id, this will be handled for you behind the scenes.

Handling of NULL in insert() Function

Any column not set, or set to nil (which is the same thing in Lua), or set to the null geometry, will be set to NULL in the database. If the column is defined with not_null = true in the table definition, the row will not be inserted. Usually that is just what you want, bad data is silently ignored that way.

If you want to check whether the insert actually happened, you can look at the return values of the insert() command. The insert() function actually returns up to four values:

local inserted, message, column, object = table:insert(...)

The last three are only set if the first is false.

Stages

When processing OSM data, osm2pgsql reads the input file(s) in order, nodes first, then ways, then relations. This means that when the nodes or ways are read and processed, osm2pgsql can’t know yet whether a node or way is in a relation (or in several). But for some use cases we need to know in which relations a node or way is and what the tags of these relations are or the roles of those member ways. The typical case are relations of type route (bus routes etc.) where we might want to render the name or ref from the route relation onto the way geometry.

The osm2pgsql flex output supports this use case by adding an additional “reprocessing” step. Osm2pgsql will call the Lua function osm2pgsql.select_relation_members() for each added, modified, or deleted relation. Your job is to figure out which node or way members in that relation might need the information from the relation to be rendered correctly and return those ids in a Lua table with the ‘nodes’ and/or ‘ways’ fields. This is usually done with a function like this:

function osm2pgsql.select_relation_members(relation)
    if relation.tags.type == 'route' then
        return {
            nodes = {},
            ways = osm2pgsql.way_member_ids(relation)
        }
    end
end

Instead of using the helper function osm2pgsql.way_member_ids() which returns the ids of all way members (or the analog osm2pgsql.node_member_ids() function), you can write your own code, for instance if you want to check the roles.

Note that select_relation_members() is called for deleted relations and for the old version of a modified relation as well as for new relations and the new version of a modified relation. This is needed, for instance, to correctly mark member ways of deleted relations, because they need to be updated, too. The decision whether a node/way is to be marked or not can only be based on the tags of the relation and/or the roles of the members. If you take other information into account, updates might not work correctly.

In addition you have to store whatever information you need about the relation in your process_relation() function in a global variable.

Make sure you use select_relation_members() only for deciding which nodes/ways to reprocess, do not store information about the relations from that function, it will not work with updates. Use the process_relation() function instead.

After all relations are processed, osm2pgsql will reprocess all marked nodes/ways by calling the process_node() and process_way() functions, respectively, for them again. This time around you have the information from the relation in the global variable and can use it.

If you don’t mark any nodes or ways, nothing will be done in this reprocessing stage.

(It is currently not possible to mark relations. This might or might not be added in future versions of osm2pgsql.)

You can look at osm2pgsql.stage to see in which stage you are.

You want to do all the processing you can in stage 1, because it is faster and there is less memory overhead. For most use cases, stage 1 is enough.

Processing in two stages can add quite a bit of overhead. Because this feature is new, there isn’t much operational experience with it. So be a bit careful when you are experimenting and watch memory and disk space consumption and any extra time you are using. Keep in mind that:

• All data stored in stage 1 for use in stage 2 in your Lua script will use main memory.
• Keeping track of way ids marked in stage 1 needs some memory.
• To do the extra processing in stage 2, time is needed to get objects out of the object store and reprocess them.
• Osm2pgsql will create an id index on all way tables to look up ways that need to be deleted and re-created in stage 2.

Type Conversions

The insert() function will try its best to convert Lua values into corresponding PostgreSQL values. But not all conversions make sense. Here are the detailed rules:

1. Lua values of type function, userdata, or thread will always result in an error.
2. The Lua type nil is always converted to NULL.
3. If the result of a conversion is NULL and the column is defined as NOT NULL the data is not inserted, see above for details.
4. The Lua type table is converted to the PostgreSQL type hstore if and only if all keys and values in the table are string values.
5. For boolean columns: The number 0 is converted to false, all other numbers are true. Strings are converted as follows: "yes", "true", "1" are true; "no", "false", "0" are false, all others are NULL.
6. For integer columns (int2, int4, int8): Boolean true is converted to 1, false to 0. Numbers that are not integers or outside the range of the type result in NULL. Strings are converted to integers if possible otherwise the result is NULL.
7. For real columns: Booleans result in an error, all numbers are used as is, strings are converted to a number, if that is not possible the result is NULL.
8. For direction columns (stored as int2 in the database): Boolean true is converted to 1, false to 0. The number 0 results in 0, all positive numbers in 1, all negative numbers in -1. Strings "yes" and "1" will result in 1, "no" and "0" in 0, "-1" in -1. All other strings will result in NULL.
9. For json and jsonb columns string, number, and boolean values are converted to their JSON equivalent as you would expect. (The special floating point numbers NaN and Inf can not be represented in JSON and are converted to null). An empty table is converted to an (empty) JSON object, tables that only have consecutive integer keys starting from 1 are converted into JSON arrays. All other tables are converted into JSON objects. Mixed key types are not allowed. Osm2pgsql will detect loops in tables and return an error.
10. For text columns and any other not specially recognized column types, booleans result in an error and numbers are converted to strings.
11. Geometry objects are converted to their PostGIS counterparts. Null geometries are converted to database NULL. Geometries in WGS84 will automatically be transformed into the target column SRS if needed. Non-multi geometries will automatically be transformed into multi-geometries if the target column has a multi-geometry type.

If you want any other conversions, you have to do them yourself in your Lua code. Osm2pgsql provides some helper functions for other conversions, see the Lua helper library (Appendix B).

Geometry Objects in Lua

Lua geometry objects are created by calls such as object:as_point() or object:as_polygon() inside processing functions. It is not possible to create geometry objects from scratch, you always need an OSM object.

You can write geometry objects directly into geometry columns in the database using the table insert() function. But you can also transform geometries in multiple ways.

Geometry objects have the following functions. They are modelled after the PostGIS functions with equivalent names.

The Lua length operator (#) returns the number of geometries in the geometry object, it is synonymous to calling num_geometries().

Converting a geometry to a string (tostring(geom)) returns the geometry type (as with the geometry_type() function).

All geometry functions that return geometries will return a NULL geometry on error. All geometry functions handle NULL geometry on input in some way. So you can always chain geometry functions and if there is any problem on the way, the result will be a NULL geometry. Here is an example:

local area = object:as_polygon():transform(3857):area()
-- area will be 0.0 if not a polygon or transformation failed

To iterate over the members of a multi-geometry use the geometries() function:

local geom = object:as_multipolygon()
for g in geom:geometries() do
    landuse.insert({
        geom = g,
        ...
    })
end

In Lua you can not get at the actual contents of the geometries, i.e. the coordinates and such. This is intentional. Writing functions in Lua that do something with the coordinates will be much slower than writing those functions in C++, so Lua scripts should concern themselves only with the high-level control flow, not the details of the geometry. If you think you need some function to access the internals of a geometry, start a discussion on Github.

The Pgsql Output

The pgsql output is the original output osm2pgsql started with. It was designed for rendering OpenStreetMap data, principally with Mapnik. It is still widely used although it is much more limited than the more modern “flex” output in how the data can be represented in the database.

If you are starting a new project with osm2pgsql, we recommend you use the flex output instead. The pgsql output is marked as deprecated now and does not get any of the new features that the flex output has or will get in the future. The pgsql output will be removed at some point, so you should think about migrating your existing projects.

Database Layout

The pgsql output always creates a fixed list of four database tables shown below. The PREFIX can be set with the -p, --prefix option, the default is planet_osm. (Note that this option is also interpreted by the middle!)

All tables contain a geometry column named way (which is not the most intuitive name, but it can’t be changed now because of backwards compatibility).

Style File

Some aspects of how the pgsql output converts OSM data into PostgreSQL tables can be configured via a style file. The default style file that is usually installed with osm2pgsql is suitable for rendering many styles. It contains some documentation of the style syntax and works well as an example or starting point for your own changes. With a custom style file, you can control how different object types and tags map to different columns and data types in the database.

The style file is a plain text file containing four columns separated by spaces. As each OSM object is processed it is checked against conditions specified in the first two columns. If they match, processing options from the third and fourth columns are applied.

Possible values for the flags are:

Closed ways with tag area=yes and relations with type=multipolygon or type=boundary will be imported as polygons even if no polygon flag is set. Non-closed ways and closed ways with area=no will always be imported as lines.

Nodes are always placed in the “point” table, never in the “line” or “polygon” table.

Usually only objects which result in at least one of the columns declared in the style file being not NULL will be added to the database. But see below in the Use of Hstore section.

The style file may also contain comments. Any text between a # and the end of the line will be ignored.

Special ‘Tags’

There are several special values that can be used in the tag column (second column) of the style file for creating additional fields in the database which contain things other than tag values.

To use these, you must use the command line option --extra-attributes.

If importing with both --hstore and --extra-attributes the meta-data will end up in the tags hstore column regardless of the style file.

Schemas and Tablespaces

Usually all tables, indexes and functions that the pgsql output creates are in the default schema and use the default tablespace.

You can use the command line option --output-pgsql-schema=SCHEMA to tell osm2pgsql that it should use the specified schema to create the tables, indexes, and functions in. Note that you have to create the schema before running osm2pgsql and make sure the database user was granted the rights to create tables, indexes, and functions in this schema. Read more about schemas in the PostgreSQL documentation. By default the public schema is used.

Sometimes you want to create special PostgreSQL tablespaces and put some tables or indexes into them. Having often used indexes on fast SSD drives, for instance, can speed up processing a lot. There are three command line options that the pgsql output interprets: To set the tablespace for output tables and indexes, use the --tablespace-main-data=TABLESPC and --tablespace-main-index=TABLESPC options, respectively. You can also use the -i, --tablespace-index=TABLESPC option which will set the index tablespace for the pgsql output as well as for the middle! Note that it is your job to create the tablespaces before calling osm2pgsql and making sure the disk behind it is large enough.

Coastline Processing

The natural=coastline tag is suppressed by default, even if you import the natural=* key. Many maps get the coastlines from a different source, so it does not need to import them from the input file. You can use the --keep-coastlines parameter to change this behavior if you want coastlines in your database. See the OSM wiki for more information on coastline processing.

Use of Hstore

Hstore is a PostgreSQL data type that allows storing arbitrary key-value pairs in a single column. It needs to be installed on the database with CREATE EXTENSION hstore;

Hstore is used to give more flexibility in using additional tags without reimporting the database, at the cost of less speed and more space.

By default, the pgsql output will not generate hstore columns. The following options are used to add hstore columns of one type or another:

• --hstore or -k adds any tags not already in a conventional column to a hstore column called tags. With the default stylesheet this would result in tags like highway appearing in a conventional column while tags not in the style like name:en or lanes:forward would appear only in the hstore column.

• --hstore-all or -j adds all tags to a hstore column called tags, even if they’re already stored in a conventional column. With the standard stylesheet this would result in tags like highway appearing in conventional column and the hstore column while tags not in the style like name:en or lanes:forward would appear only in the hstore column.

• --hstore-column or -z, which adds an additional column for tags starting with a specified string, e.g. --hstore-column 'name:' produces a hstore column that contains all name:xx tags. This option can be used multiple times.

You can not use both --hstore and --hstore-all together.

The following options can be used to modify the behaviour of the hstore columns:

• --hstore-match-only modifies the above options and prevents objects from being added if they only have tags in the hstore column and no tags in the non-hstore columns. If neither of the above options is specified, this option is ignored.

• --hstore-add-index adds indexes to all hstore columns. This option is ignored if there are no hstore columns. Using indexes can speed up arbitrary queries, but for most purposes partial indexes will be faster. You have to create those yourself.

Either --hstore or --hstore-all when combined with --hstore-match-only should give the same rows as no hstore, just with the additional hstore column.

Note that when you are using the --extra-attributes option, all your nodes, ways, and relations essentially get a few extra tags. Together with the hstore options above, the object attributes might end up in your hstore column(s) possibly using quite a lot of space. This is especially true for the majority of nodes that have no tags at all, which means they would normally not appear in your output tables. You might want to use --hstore-match-only in that case.

Lua Tag Transformations

The pgsql output supports Lua scripts to rewrite tags before they enter the database. Use the command line option --tag-transform-script=SCRIPT to enable this.

There is inevitably a performance hit with any extra processing. The Lua tag transformation is a little slower than the C++-based default, but this will probably not matter much in practice. But Lua pre-processing may save you further processing later. The Lua transformations allow you, for instance, to unify disparate tagging (for example, highway=path; foot=yes and highway=footway) and perform complex queries, potentially more efficiently than writing them as rules in your stylesheet which are executed at rendering time.

Note that this is a totally different mechanism than the Lua scripts used in the flex output.

The Lua script needs to implement the following functions:

function filter_tags_node(tags, num_tags)
return filter, tags

function filter_tags_way(tags, num_tags)
return filter, tags, polygon, roads

function filter_basic_tags_rel(tags, num_tags)
return filter, tags

These take a set of tags as a Lua key-value table, and an integer which is the number of tags supplied.

The first return value is filter, a flag which you should set to 1 if the way/node/relation should be filtered out and not added to the database, 0 otherwise. (They will still end up in the slim mode tables, but not in the rendering tables.)

The second return value is tags, a transformed (or unchanged) set of tags, which will be written to the database.

filter_tags_way returns two additional flags:

• poly should be 1 if the way should be treated as a polygon, or 0 if it is to be treated as a line.
• roads should be 1 if the way should be added to the roads table, 0 otherwise.

function filter_tags_relation_member(tags, member_tags, roles, num_members)
return filter, tags, member_superseded, boundary, polygon, roads

The function filter_tags_relation_member is more complex and can handle more advanced relation tagging, such as multipolygons that take their tags from the member ways.

This function is called with the tags from the relation; a set of tags for each of the member ways (member relations and nodes are ignored); the set of roles for each of the member ways; and the number of members. The tag and role sets are both arrays (indexed tables).

As with the other functions, it should return a filter flag, and a transformed set of tags to be applied to the relation in later processing. The third return value, member_superseded, is obsolete and will be ignored. The fourth and fifth return values, boundary and polygon, are flags that specify if the relation should be processed as a line, a polygon, or both (e.g. administrative boundaries). Set the final return value, roads, to 1 if the geometry should be added to the roads table.

There is a sample tag transform Lua script in the repository as an example, which (nearly) replicates the built-in transformations and can be used as a template for one’s own scripts.

Test your Lua script with small excerpts before applying it to a whole country or even the planet. Be aware that the Lua tagtransform allows to run arbitrary code on your system. Only run scripts from trusted sources!

Pgsql Output Command Line Options

These are all the command line options interpreted by the pgsql output:

Middle

The middle keeps track of all OSM objects read by osm2pgsql and the relationships between those objects. It knows, for instance, which nodes are used by which ways, or which members a relation has. It also keeps track of all node locations. This information is necessary to build way geometries from way nodes and relation geometries from members and it is necessary when updating data, because OSM change files only contain changed objects themselves and not all the related objects needed for creating an object’s geometry.

The Properties Table

Osm2pgsql stores some properties into a database table. This table is always called osm2pgsql_properties. It will be created in the schema set with the --middle-schema option, or the public schema by default.

The properties table tracks some settings derived from the command line options and from the input file(s). It allows osm2pgsql to make sure that updates are run with compatible options.

The osm2pgsql_properties table contains two columns: The property column contains the name of a property and the value column its value. Properties are always stored as strings, for boolean properties the strings true and false are used.

The following properties are currently defined:

When updating an existing database that has an osm2pgsql_properties table, osm2pgsql will check that the command line options used are compatible and will complain if they are not. Options that are not set on the command line will automatically be set if needed. So for instance if you import a database without -x but then use -x on updates, osm2pgsql will fail with an error message. If you use -x both on import and on update everything is fine. And if you use -x on import but not on update, osm2pgsql will detect that you used that option on import and also use it on update.

The name of the flat node and style files specified on the command line are converted to absolute file names and stored in the flat_node_file and style property, respectively. That means that osm2pgsql will find the files again even if you start it from a different current working directory. If you need to move the flat node or style file somewhere else, you can do that. The next time you run osm2pgsql, add the -F, --flat-nodes or -S, --style option again with the new file name and osm2pgsql will use the new name and update the properties table accordingly.

The current_timestamp and import_timestamp properties are not set if the input file(s) don’t contain timestamps on the OSM objects. (Timestamps in OSM files are optional, but most OSM files have them.)

The replication_* properties reflect the setting of the respective header fields in the input file on import and are used by osm2pgsql-replication to automatically update the database. That program will also update those fields. If you import multiple files, these properties will not be set.

The contents of the osm2pgsql_properties table are internal to osm2pgsql and you should never change them. There is one exception: You can add your own properties for anything you need, but make sure to start the property names with an underscore (_). this way the property names will never clash with any names that osm2pgsql might introduce in the future.

Database Structure

The middle stores its data in the database in the following tables. The PREFIX can be set with the -p, --prefix option, the default is planet_osm. (Note that this option is also interpreted by the pgsql output!)

If a flat node file is used (see below) the PREFIX_nodes table might be missing or empty, because nodes are stored in the flat node file instead. The users table is only used when the -x, --extra-attributes command line option is set (see below).

The tables have the following structure:

You can create a PostGIS geometry from the lat and lon columns like this:

SELECT id, ST_SetSRID(ST_MakePoint(lon / 10000000.0, lat / 10000000.0), 4326) AS geom FROM planet_osm_nodes;

The members Column

The members column contains a JSON array of JSON objects. For each member the JSON object contains the following fields:

A function planet_osm_member_ids(members int8[], type char(1)) is provided. (The prefix is the same as the tables, here planet_osm.) The function returns all ids in members of type type (‘N’, ‘W’, or ‘R’) as an array of int8. To get the ids of all way members of relation 17, for instance, you can use it like this:

SELECT planet_osm_member_ids(members, 'W') AS way_ids
    FROM planet_osm_rels WHERE id = 17;

Extra Attributes

The following extra columns are stored when osm2pgsql is run with the -x, --extra-attributes command line option (all columns can be NULL if the respective fields were not set in the input data):

In addition the PREFIX_users table is created with the following structure:

Indexes

PostgreSQL will automatically create BTREE indexes for primary keys on all middle tables. In addition there are the following indexes:

An GIN index on the nodes column of the ways table allows you to find all ways referencing a give node. You need to access this index with a query like this (which finds all ways referencing node 123):

SELECT * FROM planet_osm_ways
    WHERE nodes && ARRAY[123::int8]
    AND planet_osm_index_bucket(nodes) && planet_osm_index_bucket(ARRAY[123::int8]);

Note the extra condition using the planet_osm_index_bucket() function which makes sure the index can be used. The function will have the same prefix as your tables (by default planet_osm).

To find the relations referencing specific nodes or ways use the planet_osm_member_ids() function described above. There are indexes for members of type node and way (but not members of type relation) provided which use this function. Use a query like this:

SELECT * FROM planet_osm_rels
    WHERE planet_osm_member_ids(members, 'W'::char(1)) && ARRAY[456::int8];

Make sure to use the right casts (::char(1) for the type, ::int8 for the ids), without them PostgreSQL sometimes is not able to match the queries to the right functions and indexes.

By default there is no index on the tags column. If you need this, you can create it with

CREATE INDEX ON planet_osm_nodes USING gin (tags) WHERE tags IS NOT NULL;

Such an index will support queries like

SELECT id FROM planet_osm_nodes WHERE tags ? 'amenity'; -- check for keys
SELECT id FROM planet_osm_nodes WHERE tags @> '{"amenity":"post_box"}'::jsonb; -- check for tags

Reserved Names and Compatibility

For compatibility with older and future versions of osm2pgsql you should never create tables, indexes, functions or any other objects in the database with names that start with osm2pgsql_ or with the PREFIX you have configured (planet_osm_ by default). This way your objects will not clash with any objects that osm2pgsql creates.

Always read the release notes before upgrading in case osm2pgsql changes the format or functionality of any tables, indexes, functions or other objects in the database that you might be using.

Flat Node Store

-F or --flat-nodes specifies that instead of a table in PostgreSQL, a binary file is used as a database of node locations. This should only be used on full planet imports or very large extracts (e.g. Europe) but in those situations offers significant space savings and speed increases, particularly on mechanical drives.

The file will need approximately 8 bytes * maximum node ID, regardless of the size of the extract. With current OSM data (in 2024) that’s about 100 GB. As a good rule of thumb you can look at the current PBF planet file on planet.osm.org, the flat node file will probably be somewhat larger than that.

If you are using the --drop option, the flat node file will be deleted after import.

Caching

In slim-mode, i.e. when using the database middle, you can use the -C, --cache option to specify how much memory (in MBytes) to allocate for caching data. Generally more cache means your import will be faster. But keep in mind that other parts of osm2pgsql and the database will also need memory.

To decide how much cache to allocate, the rule of thumb is as follows: use the size of the PBF file you are trying to import or about 75% of RAM, whatever is smaller. Make sure there is enough RAM left for PostgreSQL. It needs at least the amount of shared_buffers given in its configuration.

You may also set --cache to 0 to disable caching completely to save memory. If you use a flat node store you should disable the cache, it will usually not help in that situation.

In non-slim mode, i.e. when using the RAM middle, the --cache setting is ignored. All data is stored in RAM and uses however much memory it needs.

Bucket Index for Slim Mode

Osm2pgsql can use an index for way node lookups in slim mode that needs a lot less disk space than earlier versions did. For a planet the savings can be about 200 GB! Because the index is so much smaller, imports are faster, too. Lookup times are slightly slower, but this shouldn’t be an issue for most people.

If you are not using slim mode and/or not doing updates of your database, this does not apply to you.

Middle Command Line Options

Expire

When osm2pgsql is processing OSM changes, it can create a list of (Web Mercator) tiles that are affected by those changes. This list can later be used to delete or re-render any changed tiles you might have cached. Osm2pgsql only creates this list. How to actually expire the tiles is outside the scope of osm2pgsql. Expire only makes sense in append mode.

Tile expiry will probably only work when creating Web Mercator (EPSG:3857) geometries. When using other output projections osm2pgsql can still generate expire files, but it is unclear how useful they are. The flex output will only allow you to enable expire on Web Mercator geometry columns.

There are two ways to configure tile expiry. The old way (and the only way if you are using the pgsql output) is to use the -e, --expire-tiles, -o, --expire-output, and --expire-bbox-size command line options. This allows only a single expire output to be defined (and it has to go to a file).

The new way, which is only available with the flex output, allows you to define any number of expire outputs (and they can go to files or to database tables).

Expire Outputs

Each expire output has a minimum and maximum zoom level. For each geometry that needs to be expired, the coordinates of the affected tiles are determined and stored. When osm2pgsql is finished with its run, it writes the tile coordinates for all zoom levels between minimum and maximum zoom level to the output.

There is a somewhat special case: If you don’t define a zoom level for the expire output, zoom level 0 is assumed for the minimum and maximum zoom level. That means that any change will result in an expire entry for tile 0/0/0. You can use this to trigger some processing for any and all changes in a certain table for instance.

Memory requirements for osm2pgsql rise with the maximum zoom level used and the number of changes processed. This is usually no problem for zoom level 12 or 14 tiles, but might be an issue if you expire on zoom level 18 and have lots of changes to process.

The output can be written to a file or a table:

Expire File

The generated expire file is a text file that contains one tile coordinate per line in the format ZOOM/X/Y. Tiles appear only once in the file even if multiple geometry changes are affecting the same tile.

The file is written to in append mode, i.e. new tiles are added to the end of the file. You have to clear the file after processing the tiles.

Expire Table

The expire table has five columns zoom, x, y, first, and last. A primary key constraints on the first three columns makes sure that there is no duplicate data. The first and last columns contain the timestamp of the first time this tile was marked as expired and the last time, respectively. These two timestamps can be used to implement various expiry strategies.

You have to delete entries from this file after expiry is run.

Details of the Expire Calculations

To figure out which tiles need to be expired, osm2pgsql looks at the old and new geometry of each changed feature and marks all tiles as expired that are touched by either or both of those geometries. For new features, there is only the new geometry, of course. For deleted features only the old geometry is used.

If the geometry of a feature didn’t change but the tags changed in some way that will always trigger the expiry mechanism. It might well be that the tag change does not result in any visible change to the map, but osm2pgsql can’t know that, so it always marks the tiles for expiry.

Which tiles are marked to be expired depends on the geometry type generated:

• For point geometries, the tile which contains this point is marked as expired.
• For line geometries (linestring or multilinestring) all tiles intersected by the line are marked as expired.
• For (multi)polygons there are several expire modes: In full-area mode all tiles in the bounding box of the polygon are marked as expired. In boundary-only mode only the lines along the boundary of the polygon are expired. In hybrid mode either can happen depending on the area of the polygon. Polygons with an area larger than full_area_limit are expired as if boundary-only is set, smaller areas in full-area mode. When using the flex output, you can set the mode and full_area_limit as needed for each geometry column. For the pgsql output the expire output always works in hybrid mode, use the --expire-bbox-size option to set the full_area_limit (default is 20000).

In each case neighboring tiles might also be marked as expired if the feature is within a buffer of the tile boundary. This is so that larger icons, thick lines, labels etc. which are rendered just at a tile boundary which “overflow” into the next tile are handled correctly. By default that buffer is set at 10% of the tile size, in the flex output it is possible to change it using the buffer setting.

Expire Command Line Options

These are the command line options to configure expiry. Use them with the pgsql or flex output.

When using the flex output it is recommended you switch to the new way of defining the expire output explained in Defining and Using Expire Outputs.

Generalization

Experimental Osm2pgsql has some limited support for generalization. See the generalization project page for some background and details. This work is experimental and everything described here might change without notice.

For the generalization functionality the separate program osm2pgsql-gen is provided. In the future this functionality might be integrated into osm2pgsql itself. The same Lua configuration file that is used for osm2pgsql is also used to configure the generalization. Generalization will only work together with the flex output.

The documentation in this chapter is incomplete. We are working on it…

Overview

Generalization is the process by which detailed map data is selected, simplified, or changed into something suitable for rendering on smaller scale maps (or smaller zoom levels). In osm2pgsql this is done with a separate program after an import or update finished. Data is processed in the database and/or read out of the database and processed in osm2pgsql and then written back.

The end result is that in addition to the usual tables created and filled by osm2pgsql you have a set of additional tables with the generalized data.

Generalization is currently only supported for Web Mercator (EPSG 3857). This is by far the most common use case, we can look at extending this later if needed.

Osm2pgsql supports several different strategies for generalization which use different algorithms suitable for different types of data. Each strategy has several configuration options. See the next section for general options used by most strategies and the section after that for all the details about the strategies.

Configuration

All tables needed for generalized data have to be configured just like any table in osm2pgsql. Currently there are some restrictions on the tables:

• The input and output tables must use the same schema.
• The geometry column used must have the same name as the geometry column in the table used as input for a generalizer.
• Output tables for tile-based generalizers must have ids set to tile, which automatically ceates x and y columns for the tile coordinates. An index will also be created on those columns after generalization.

To add generalization to your config, add a callback function osm2pgsql.process_gen() and run generalizers in there:

function osm2pgsql.process_gen()
    osm2pgsql.run_gen(STRATEGY, { ... })
end

Replace STRATEGY with the strategy (see below) and add all parameters to the Lua table.

The following parameters are used by most generalizers:

For more specific parameters see below.

You can also run any SQL command in the process_gen() callback with the run_sql() function:

osm2pgsql.run_sql({
    description = 'Descriptive name for this command for logging',
    sql = "UPDATE foo SET bar = 'x'"
})

The following fields are available in the run_sql() command:

Generalization Strategies

There are currently two types of strategies: Some strategies always work on all data in the input table(s). If there are changes in the input data, the processing has to restart from scratch. If you work with updates, you will usually only run these strategies once a day or once a week or so. In general those strategies make only sense for data that doesn’t change that often (or where changes are usually small) and if it doesn’t matter that data in smaller zoom levels are only updated occasionally.

The other type of strategy uses a tile-based approach. Whenever something changes, all tiles intersecting with the change will be re-processed. Osm2pgsql uses the existing expire mechanism to keep track of what to change.

Strategy builtup

This strategy derives builtup areas from landuse polygons, roads and building outlines. It is intended to show roughly were there are urban areas. Because it uses input data of several diverse types, it works reasonably well in different areas of the world even if the landuse tagging is incomplete.

This strategy is tile-based. Internally it uses a similar approach as the raster-union strategy but can work with several input tables.

Parameters used by this strategy (see below for some additional general parameters):

See this blog post for some background.

Strategy discrete-isolation

When rendering a map with many point features like cities or mountain peaks it is often useful to only put the most important features on the map. Importance can be something like the number of people living in a city or the height of a peak. But if only the absolute importance is used, some areas on the map will get filled with many features, while others stay empty. The Discrete Isolation algorithm can be used to calculate a more relative measure of importance which tends to create a more evenly filled map.

This strategy always processes all features in a table.

Parameters used by this strategy (see below for some additional general parameters):

The src_table and dest_table have always to be the same.

You must have an index on the id column, otherwise this will be very slow! Set create_index = 'always' in your source table configuration.

You must have the following columns in your table. This is currently not configurable:

Use these column definitions in your config file to add them:

{ column = 'discr_iso', type = 'real', create_only = true },
{ column = 'irank', type = 'int', create_only = true },
{ column = 'dirank', type = 'int', create_only = true },

See this blog post for some background.

Strategy raster-union

This strategy merges and simplifies polygons using a raster intermediate. It is intended for polygon layers such as landcover where many smaller features should be aggregated into larger ones. It does a very similar job as the vector-union strategy, but is faster.

This strategy is tile-based.

Parameters used by this strategy (see below for some additional general parameters):

Actual image extent used will be image_extent + 2 * margin * image_extent. margin * image_extent is rounded to nearest multiple of 64.

The img_path parameters can be set to help with debugging. Set img_path to something like this: some/dir/path/img. Resulting images will be in the directory some/dir/path and are named img-X-Y-TYPE-[io].png for input (i) or output (o) images. The TYPE is the value from the group_by_column.

See this blog post for some background.

Strategy rivers

This strategy is intended to find larger rivers with their width and aggregate them into longer linestrings. The implementation is incomplete and not usable at the moment.

This strategy always processes all features in a table.

Parameters used by this strategy (see below for some additional general parameters):

See this blog post for some background.

Strategy vector-union

This strategy merges and simplifies polygons using vector calculations. It is intended for polygon layers such as landcover where many smaller features should be aggregated into larger ones. It does a very similar job as the raster-union strategy, but is slower.

This strategy is tile-based.

Parameters used by this strategy (see below for some additional general parameters):

Strategy tile-sql

Run some SQL code for each tile. Use {ZOOM}, {X}, and {Y} in the SQL command to set the zoom level and tile coordinates.

This strategy is tile-based.

Parameters used by this strategy (see below for some additional general parameters):

Running osmp2gsql-gen

Here are the most important command line options:

Some strategies can run many jobs in parallel, speeding up processing a lot. Use the -j, --jobs option to set the maximum number of threads. If nothing else is running in parallel, try setting this to the number of available CPU cores.

To specify which database to work on osm2pgsql-gen uses the same command line options as osm2pgsql:

Advanced Topics

Notes on Memory Usage

Importing an OSM file into the database is very demanding in terms of RAM usage. Osm2pgsql and PostgreSQL are running in parallel at this point and both need memory. You also need enough memory for general file system cache managed by the operating system, otherwise all IO will become too slow.

PostgreSQL blocks at least the part of RAM that has been configured with the shared_buffers parameter during PostgreSQL tuning and needs some memory on top of that. (See Tuning the PostgreSQL Server). Note that the PostgreSQL manual recommends setting shared_buffers to 25% of the memory in your system, but this is for a dedicated database server. When you are running osm2pgsql on the same host as the database, this is usually way too much.

Osm2pgsql needs at least 2GB of RAM for its internal data structures, potentially more when it has to process very large relations. In addition it needs to maintain a cache for node locations. The size of this cache can be configured with the parameter --cache.

When importing with a flatnode file (option --flat-nodes), it is best to disable the node cache completely (--cache=0) and leave the memory for the system cache to speed up accessing the flatnode file.

For imports without a flatnode file, set --cache approximately to the size of the OSM pbf file you are importing. (Note that the --cache setting is in MByte). Make sure you leave enough RAM for PostgreSQL and osm2pgsql as mentioned above. If the system starts swapping or you are getting out-of-memory errors, reduce the cache size or consider using a flatnode file.

When you are running out of memory you’ll sometimes get a bad_alloc error message. But more often osm2pgsql will simply crash without any useful message. This is, unfortunately, something we can not do much about. The operating system is not telling us that there is no memory available, it simply ends the program. This is due to something called “overcommit”: The operating system will allow the program to allocate more memory than there is actually available because it is unlikely that all programs will actually need this memory and at the same time. Unfortunately when programs do, there isn’t anything that can be done except crash the program. Memory intensive programs like osm2pgsql tend to run into these problems and it is difficult to predict what will happen with any given set of options and input files. It might run fine one day and crash on another when the input is only slightly different.

Note also that memory usage numbers reported by osm2pgsql itself or tools such as ps and top are often confusing and difficult to interpret. If it looks like you are running out of memory, try a smaller extract, or, if you can, use more memory, before reporting a problem.

Parallel Processing

Some parts of the osm2pgsql processing can run in parallel. Depending on the hardware resources of you machine, this can make things faster or slower or even overwhelm your system when too many things happen in parallel and your memory runs out. For normal operation the defaults should work, but you can fine-tune the behaviour using some command line options.

Osm2pgsql will do some of its processing in parallel. Usually it will use however many threads your CPUs support, but no more than 4. For most use cases this should work well, but you can tune the number of threads used with the --number-processes command line option. (Note that the option is a bit of a misnomer, because this sets the number of threads used, they are all in a single process.) If disks are fast enough e.g. if you have an SSD, then this can greatly increase speed of the “going over pending ways” and “going over pending relations” stages on a multi-core server. Past 8 threads or so this will probably not gain you any speed advantage.

By default osm2pgsql starts the clustering and index building on all tables in parallel to increase performance. This can be a disadvantage on slow disks, or if you don’t have enough RAM for PostgreSQL to do the parallel index building. PostgreSQL potentially needs the amount of memory set in the maintenance_work_mem config setting for each index it builds. With 7 or more indexes being built in parallel this can mean quite a lot of memory is needed. Use the --disable-parallel-indexing option to build the indexes one after the other.

Using Database While Updating

To improve performance osm2pgsql uses several parallel threads to import or update the OSM data. This means that there is no transaction around all the updates. If you are querying the database while osm2pgsql is running, you might be able to see some updates but not others. While an import is running you should not query the data. For updates it depends a bit on your use case.

In most cases this is not a huge problem, because OSM objects are mostly independent of one another. If you are

• writing OSM objects into multiple tables,
• using two-stage processing in the Flex output, or
• doing complex queries joining several tables

you might see some inconsistent data, although this is still rather unlikely. If you are concerned by this, you should stop any other use of the database while osm2pgsql is running. This is something that needs to be done outside osm2pgsql, because osm2pgsql doesn’t know what else is running and whether and how it might interact with osm2pgsql.

Note that even if you are seeing inconsistent data at some point, the moment osm2pgsql is finished, the data will be consistent again. If you are running a tile server and using the expire functionality, you will, at that point, re-render all tiles that might be affected making your tiles consistent again.

Handling Failed Imports or Updates

If a database import with osm2pgsql fails for any reason you have to start from the beginning. Fix the problem that caused the failure and run osm2pgsql again. You might want to re-initialize the database before that or remove some leftover tables and indexes, but you don’t have to.

If a database update with osm2pgsql fails for any reason just do the update again (after fixing the cause of the failure). As descibed in the previous section, you might have inconsistent map data until you run that update to completion. If you are running multiple updates and don’t know which one failed you can always apply all updates again from the beginning. If you are using osm2pgsql-replication simply re-run it after fixing the problem, it will figure out from where to restart the updates.

Clustering by Geometry

Typical use cases for a database created by osm2pgsql require querying the database by geometry. To speed up this kind of query osm2pgsql will by default cluster the data in the output tables by geometry which means that features which are in reality near to each other will also be near to each other on the disk and access will be faster.

If a table has multiple geometry columns, clustering will always be by the first geometry column.

This clustering is achieved by ordering and copying each whole table after the import. This will take some time and it means you will temporarily need twice the disk space.

When you are using the flex output, you can disable clustering by setting the cluster table option to no (see the Advanced Table Definition section).

Logging and Monitoring SQL Commands

The --log-sql option allows you to see what SQL commands are issued by osm2pgsql. Each log line starts with the date and time and SQL:, after that you see the connection number (C3) and the log information, usually an SQL command exactly as it was sent to the database.

For new connections the database backend process id is logged.

New connections also show the “context” which specifies which part of osm2pgsql has created this connection. The context and connection number will also appear in the application_name used for this connection which can be seen in the pg_stat_activity table from inside the database.

Tips & Tricks

The flex output allows a wide range of configuration options. Here are some extra tips & tricks.

Using create_only Columns for Postprocessed Data

Sometimes it is useful to have data in table rows that osm2pgsql can’t create. For instance you might want to store the center of polygons for faster rendering of a label.

To do this define your table as usual and add an additional column, marking it create_only. In our example case the type of the column should be the PostgreSQL type GEOMETRY(Point, 3857), because we don’t want osm2pgsql to do anything special here, just create the column with this type as is.

polygons_table = osm2pgsql.define_area_table('polygons', {
    { column = 'tags', type = 'hstore' },
    { column = 'geom', type = 'geometry' },
    { column = 'center', sql_type = 'GEOMETRY(Point, 3857)', create_only = true },
    { column = 'area', type = 'area' },
})

After running osm2pgsql as usual, run the following SQL command:

UPDATE polygons SET center = ST_Centroid(geom) WHERE center IS NULL;

If you are updating the data using osm2pgsql --append, you have to do this after each update. When osm2pgsql inserts new rows they will always have a NULL value in center, the WHERE condition makes sure that we only do this (possibly expensive) calculation once.

Creating GENERATED Columns

From version 12 on PostgreSQL supports GENERATED columns. You can use these from osm2pgsql with a trick, by adding some “magic” wording to the sql_type in a column definition.

We don’t promise that this trick will work forever. Putting anything into the sql_type but a PostgreSQL type is strictly experimental.

It is probably best explained with an example. With this config you create a polygon table with an additional column center that is automatically filled with the centroid of the polygon added:

local polygons = osm2pgsql.define_area_table('polygons', {
    { column = 'tags', type = 'jsonb' },
    { column = 'geom', type = 'polygon', not_null = true },
    { column = 'center', create_only = true, sql_type = 'geometry(point, 3857) GENERATED ALWAYS AS (ST_Centroid(geom)) STORED' },
})

function osm2pgsql.process_way(object)
    if object.is_closed then
        polygons:insert({
            tags = object.tags,
            geom = object:as_polygon()
        })
    end
end

You could do this specific case simpler and faster by using the centroid() function in Lua. But PostGIS has a lot more interesting functions that you can use this way. Be sure to read the PostgreSQL documentation about the syntax and functionality of the GENERATED columns.

Make sure you have the create_only = true option set on the column, otherwise this will not work.

Accessing Environment Variables from Lua

In Lua scripts you can access environment variables with os.getenv("VAR"). The Lua config scripts that osm2pgsql uses are normal Lua scripts, so you can do that there, too.

Logging Memory Use of Lua Scripts

Lua scripts can use quite a lot of memory if you are not careful. This is usually only a problem when using two-stage processing. To monitor how much memory is currently used, use this function:

function create_memory_reporter(filename, frequency)
    local counter = 0
    local file = io.open(filename, 'w')
    file:write('timestamp,counter,mbyte\n')

    return function()
        if counter % frequency == 0 then
            local mem = collectgarbage('count')
            local ts = os.date('%Y-%m-%dT%H:%M:%S,')
            file:write(ts .. counter .. ',' .. math.ceil(mem / 1024) .. '\n')
            file:flush()
        end
        counter = counter + 1
    end
end

Then use it to create one or more memory_reporters. The first argument is the output file name, the second specifies after how many process callbacks it should trigger the output. Make sure this number is not too small, otherwise processing will become quite slow.

Here is an example use for the process_node callback:

local mr = create_memory_reporter('/tmp/osm2pgsql-lua-memlog.csv', 10000)

function osm2pgsql.process_node(object)
    mr()
    ...
end

You can have one memory reporter for nodes, ways, and relations together or have separate ones.

Checking Lua Scripts

If you have the Lua compiler (luac) installed (it comes with the installation of the Lua interpreter), you can use it to syntax check your Lua scripts independently of osm2pgsql. Just run luac -p SCRIPT.lua.

A script that fails this check will not work with osm2pgsql. But it is only a syntax check, it doesn’t run your script, so the script can still fail when used in osm2pgsql. But it helps getting rid of the simple errors quickly.

There is also the luacheck linter program which does a lot more checks. Install with luarocks install luacheck, on Debian/Ubuntu you can use the lua-checks package. Then run luacheck SCRIPT.lua.

Lua Script Performance

A complex Lua flex configuration might mean that osm2pgsql spends quite some time running your Lua code. Optimizing that code will be important.

You can somewhat increase processing speed by using the LuaJIT compiler, but you have to compile osm2pgsql yourself, because pre-built osm2pgsql binaries usually don’t use it.

Here are some tips:

• Always use local variables which are cheap. It also makes your code more robust.
• Don’t do work more than once. Store intermediate results in local variables instead of recomputing it. For instance if you need the geometry of an OSM object several times, get it once and store it (local geom = object:as_polygon(); local center = geom:centroid()).

See Lua Performance Tips from the author of Lua for some in-depth tips on how to improve your Lua code. This stackoverflow question also has some great information.