
---------------------------------------------
# RDF Triplestore Foreign Data Wrapper for PostgreSQL (rdf_fdw)

`rdf_fdw` is a PostgreSQL Foreign Data Wrapper that enables seamless integration with RDF triplestores via SPARQL endpoints. It supports querying RDF data using SQL, with advanced features including pushdown of SQL clauses (WHERE, LIMIT, ORDER BY, DISTINCT), data modification operations (INSERT, UPDATE, DELETE), and built-in implementations of SPARQL 1.1 functions. The extension introduces a custom `rdfnode` data type for native RDF term handling and provides tools for prefix management, making it easier to work with RDF vocabularies directly from PostgreSQL.

![CI](https://github.com/jimjonesbr/rdf_fdw/actions/workflows/ci.yml/badge.svg)

## Index

- [Requirements](#requirements)
- [Quick Start](#quick-start)
- [Update Extension](#update-extension)
- [Deploy with Docker](#deploy-with-docker)
- [Usage](#usage)
  - [CREATE USER MAPPING](#create-user-mapping)
  - [CREATE SERVER](#create-server)
  - [CREATE FOREIGN TABLE](#create-foreign-table)
    - [RDF Node Handling](#rdf-node-handling)
  - [ALTER FOREIGN TABLE and ALTER SERVER](#alter-foreign-table-and-alter-server)
  - [Pushdown](#pushdown)
  - [Prefix Management](#prefix-management)
  - [Data Modification](#data-modification)
    - [INSERT](#insert)
    - [UPDATE](#update)
    - [DELETE](#delete)
  - [rdf_fdw_version](#rdf_fdw_version)
  - [rdf_fdw_settings](#rdf_fdw_settings)    
  - [rdf_fdw_clone_table](#rdf_fdw_clone_table)    
  - [EXPLAIN and Diagnostics](#explain-and-diagnostics)
- [SPARQL Functions](#sparql-functions)
  - [Aggregates](#aggregates)
  - [Functional Forms](#functional-forms)
  - [Functions on RDF Terms](#functions-on-rdf-terms)
  - [Functions on Strings](#functions-on-strings)
  - [Functions on Numerics](#functions-on-numerics)
  - [Functions on Dates and Times](#functions-on-dates-and-times)
  - [Hash Functions](#hash-functions)
  - [Custom Functions](#custom-functions)
- [SPARQL Describe](#sparql-describe)
- [Import data into QGIS](#import-data-into-qgis)
- [For testers and developers](#for-testers-and-developers)
 
## [Requirements](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#requirements)

* [PostgreSQL](https://www.postgresql.org): version 9.5 or higher.
* [libxml2](http://www.xmlsoft.org/): version 2.5.0 or higher.
* [libcurl](https://curl.se/libcurl/): version 7.74.0 or higher.
* [pkg-config](https://linux.die.net/man/1/pkg-config): pkg-config 0.29.2 or higher.
* [gcc](https://gcc.gnu.org/) and [make](https://www.gnu.org/software/make/) to compile the code.

In an Ubuntu environment you can install all dependencies with the following command:

```shell
apt-get install -y make gcc postgresql-server-dev-18 libxml2-dev libcurl4-gnutls-dev pkg-config
```

> [!NOTE]  
> `postgresql-server-dev-18` only installs the libraries for PostgreSQL 18. Change it if you're using another PostgreSQL version.

## [Quick Start](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#quick-start)

Ensure [pg_config](https://www.postgresql.org/docs/current/app-pgconfig.html) is properly set before running `make`. This executable is typically found in your PostgreSQL installation's `bin` directory.

```bash
$ cd rdf_fdw
$ make
```

After compilation, install the Foreign Data Wrapper:

```bash
$ make install
```

Then, create the extension in PostgreSQL:

```sql
CREATE EXTENSION rdf_fdw;
```

To install a specific version, use:

```sql
CREATE EXTENSION rdf_fdw WITH VERSION '2.5';
```

To run the predefined regression tests: 

```bash
$ make PGUSER=postgres installcheck
```

> [!NOTE]  
> `rdf_fdw` loads all retrieved RDF data into memory before converting it for PostgreSQL. If you expect large data volumes, ensure that PostgreSQL has sufficient memory.


## [Update Extension](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#update-extension)

To update the extension's version you must first build and install the binaries and then run `ALTER EXTENSION`:

```sql
ALTER EXTENSION rdf_fdw UPDATE;
```

To update to an specific version use `UPDATE TO` and the full version number, e.g.

```sql
ALTER EXTENSION rdf_fdw UPDATE TO '2.5';
```

## [Deploy with Docker](#deploy-with-docker)

A convenient way to build and test `rdf_fdw` is to create a Docker image that bundles the extension with a matching PostgreSQL base image. The two common approaches are:

- Build an image that compiles and installs the extension (reproducible, good for CI).
- Mount the source into a container and run `make install` for iterative development (faster local iterations).

Minimal example Dockerfile for PostgreSQL 18:

```dockerfile
FROM postgres:18

RUN apt-get update && \
    apt-get install -y git make gcc postgresql-server-dev-18 libxml2-dev libcurl4-gnutls-dev pkg-config

RUN git clone --branch v2.5 https://github.com/jimjonesbr/rdf_fdw.git && \
    cd rdf_fdw && \
    make -j && \
    make install
```

Build and run the image:

```bash
docker build -t rdf_fdw_image .
docker run -d --name rdf_fdw_container -e POSTGRES_HOST_AUTH_METHOD=trust rdf_fdw_image
```

Create the extension inside the running container:

```bash
docker exec -u postgres rdf_fdw_container psql -d mydatabase -c "CREATE EXTENSION rdf_fdw;"
```

> [!NOTE] 
> Do not use `POSTGRES_HOST_AUTH_METHOD=trust` in production. Check for other `POSTGRES_HOST_AUTH_METHOD` in the PostgreSQL docker documentation.


## [Usage](#usage)

Set up a `SERVER` that points to a SPARQL endpoint, then declare `FOREIGN TABLE`s that contain the SPARQL query and map result variables to table columns. Keep foreign-table queries simple to maximise pushdown; see the [Pushdown](#pushdown) section for details and limitations.

### [CREATE SERVER](#create_server)

Use `CREATE SERVER` to register a remote SPARQL endpoint with PostgreSQL - the creator becomes the server owner. The `endpoint` option (the SPARQL endpoint URL) is required; you may also specify optional connection settings such as timeouts or proxy parameters, if applicable.

Example: register the DBpedia SPARQL endpoint

```sql
CREATE SERVER dbpedia
FOREIGN DATA WRAPPER rdf_fdw 
OPTIONS (endpoint 'https://dbpedia.org/sparql');
```


**Server Options**

| Server Option | Type | Description |
|---------------|------|-------------|
| `endpoint` | **required** | SPARQL endpoint URL (required). |
| `batch_size` | optional | Number of rows to accumulate per SPARQL UPDATE request for DML operations (default `50`). Larger batches reduce network overhead but may exceed endpoint limits. |
| `enable_pushdown` | optional | Enable translation of SQL clauses into SPARQL (default `true`). |
| `format` | optional | Expected SPARQL result MIME type (default `application/sparql-results+xml`). Set if your endpoint requires a different value. |
| `http_proxy` | optional | HTTP proxy URL (for authentication, specify `proxy_user` and `proxy_password` in `USER MAPPING`). |
| `connect_timeout` | optional | Connection timeout in seconds (default `300`). |
| `request_timeout` | optional | Maximum time in seconds allowed for a complete HTTP request (connect + transfer). `0` disables the limit (default). Unlike `connect_timeout`, this applies to the entire duration of the request, including data transfer. |
| `connect_retry` | optional | Number of retry attempts on failure (default `3`). |
| `request_redirect` | optional | Follow HTTP redirects (default `false`). |
| `request_max_redirect` | optional | Max redirects allowed; `0` = unlimited. |
| `custom` | optional | Triplestore-specific query parameters appended to the request URL (e.g. `signal_void=on`). |
| `query_param` | optional | HTTP parameter name that carries the SPARQL query (default `query`). |
| `prefix_context` | optional | Name of a prefix context whose `PREFIX` entries are prepended to generated SPARQL queries. |
| `enable_xml_huge` | optional | Enable libxml2's `XML_PARSE_HUGE` to process very large or deeply nested responses (dangerous; default `false`). Use only for trusted endpoints. |
| `readonly` | optional | Mark the server as read-only (default `false`). When `true`, all `INSERT`, `UPDATE`, and `DELETE` operations on any foreign table backed by this server are rejected before reaching the endpoint. Table-level `readonly` takes precedence over this setting. |

> [!NOTE]
> To view server options in `psql` use the meta-command `\des[+]`.

### [CREATE USER MAPPING](#create-user-mapping)

`CREATE USER MAPPING` associates a PostgreSQL user with credentials for a specific `SERVER`. Provide a mapping when the SPARQL endpoint requires authentication; omit it for anonymous access.

Example (map local `postgres` to remote `admin`):

```sql
CREATE SERVER graphdb
FOREIGN DATA WRAPPER rdf_fdw
OPTIONS (endpoint 'http://192.168.178.27:7200/repositories/myrepo');

CREATE USER MAPPING FOR postgres
SERVER graphdb OPTIONS (user 'admin', password 'secret');
```

**Proxy Authentication**

If the SPARQL endpoint must be accessed through an HTTP proxy, configure the proxy URL in the `SERVER` using the `http_proxy` option. When the proxy requires authentication, provide the proxy credentials (`proxy_user` and `proxy_password`) in the `USER MAPPING`.

Example with proxy authentication:

```sql
CREATE SERVER fuseki
FOREIGN DATA WRAPPER rdf_fdw
OPTIONS (
  endpoint 'http://fuseki:3030/sparql',
  http_proxy 'http://my.proxy.im:3128'
);

CREATE USER MAPPING FOR postgres
SERVER fuseki
OPTIONS (
  user 'admin',
  password 'secret',
  proxy_user 'proxyuser',
  proxy_password 'proxypass'
);
```

Options:

| Option | Type | Description |
|---|---:|---|
| `user` | **required** | Remote username for authentication. |
| `password` | optional | Remote user's password (if required by the endpoint). |
| `proxy_user` | optional | Proxy username (when `http_proxy` is set on the server). |
| `proxy_password` | optional | Proxy password (when `http_proxy` is set on the server). |

Authentication: when a `user` is supplied, `rdf_fdw` uses HTTP Basic Authentication. Other schemes (OAuth, client certificates, etc.) are not supported by this mapping.

> [!NOTE]
> To list mappings in `psql` use `\deu[+]` or query `pg_user_mappings`.

### [CREATE FOREIGN TABLE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#create_foreign_table)

Foreign tables act as a gateway to a SPARQL endpoint: the table's `sparql` option supplies the query and the SPARQL variables map to PostgreSQL columns. Keep foreign-table definitions focused and avoid embedding complex logic in SQL; simpler queries increase pushdown success and performance.

#### Table options

Table options:

| Option | Type | Description |
|--------|------|-------------|
| `sparql` | **required** | Raw SPARQL query executed for `SELECT` operations. |
| `log_sparql` | optional | Log the exact SPARQL sent to the endpoint (default `false`). |
| `enable_pushdown` | optional | Override server-level pushdown for this table (default: server value). |
| `update_url` | optional | URL used for SPARQL UPDATE requests when different from the SELECT endpoint (e.g. Fuseki). |
| `sparql_update_pattern` | optional | SPARQL triple pattern template used to build `INSERT DATA`, `DELETE DATA`, and `UPDATE` statements (required for DML). Each SPARQL variable in the pattern must be mapped to a table column. |
| `readonly` | optional | Mark this foreign table as read-only (default `false`). When `true`, `INSERT`, `UPDATE`, and `DELETE` are rejected for this table regardless of the server-level `readonly` setting. When `false`, explicitly overrides a server-level `readonly 'true'`, allowing writes on this table even when the server is read-only. |

#### Column types

Columns may be declared as `rdfnode` (**recommended**) or as standard PostgreSQL types. Use `rdfnode` when you need to preserve RDF semantics (IRIs, language tags, datatypes). Native types enable automatic casting of RDF literals into SQL types.

#### Column options

| Option | Type | Description |
|--------|------|-------------|
| `variable` | **required** | SPARQL variable mapped to this column (e.g. `?name`). In `OPTIONS` write the variable with a leading `?` or `$`, but those characters are not part of the stored name. |
| `expression` | optional | SPARQL expression to evaluate for this column (used with native types). |
| `language` | optional | Language tag to apply when comparing or formatting literals (e.g. `en`). Use `*` to ignore language. |
| `literal_type` | optional | Expected XSD datatype for the literal (e.g. `xsd:date`). Use `*` to ignore type. |
| `nodetype` | optional | Hint whether the value is `literal` or `iri` (default `literal`). |

#### Examples

Example (minimal `rdfnode` table):

```sql
CREATE FOREIGN TABLE hbf (
  p rdfnode OPTIONS (variable '?p'),
  o rdfnode OPTIONS (variable '?o')
)
SERVER linkedgeodata OPTIONS (
  sparql 
    'SELECT ?p ?o 
     WHERE {<http://linkedgeodata.org/triplify/node376142577> ?p ?o}');
```

Example (typed native columns):

```sql
CREATE FOREIGN TABLE film (
  film_id text    OPTIONS (variable '?film',     nodetype 'iri'),
  name text       OPTIONS (variable '?name',     nodetype 'literal', literal_type 'xsd:string'),
  released date   OPTIONS (variable '?released', nodetype 'literal', literal_type 'xsd:date'),
  runtime int     OPTIONS (variable '?runtime',  nodetype 'literal', literal_type 'xsd:integer'),
  abstract text   OPTIONS (variable '?abstract', nodetype 'literal', literal_type 'xsd:string')
)
SERVER dbpedia OPTIONS (
  sparql '
    PREFIX dbr: <http://dbpedia.org/resource/>
    PREFIX dbp: <http://dbpedia.org/property/>
    PREFIX dbo: <http://dbpedia.org/ontology/>

    SELECT DISTINCT ?film ?name ?released ?runtime ?abstract
    WHERE
    {
      ?film a dbo:Film ;
            rdfs:comment ?abstract ;
            dbp:name ?name ;
            dbp:released ?released ;
            dbp:runtime ?runtime .
      FILTER (LANG ( ?abstract ) = "en")
      FILTER (datatype(?released) = xsd:date)
      FILTER (datatype(?runtime) = xsd:integer)
     }
'); 
```

> [!NOTE]
> Use `\d[+]` or `\det[+]` in `psql` to view foreign table columns and options.

#### [RDF Node Handling](#rdf-node-handling)
The `rdf_fdw` extension introduces a custom data type called `rdfnode` that represents full RDF nodes exactly as they appear in a triplestore. It supports:

- **IRIs** (e.g., `<http://example.org/resource>`)
- **Plain literals** (e.g., `"42"`)
- **Literals with language tags** (e.g., `"foo"@es`)
- **Typed literals** (e.g., `"42"^^xsd:integer`)

This type is useful when you want to inspect or preserve the full structure of RDF terms—including their language tags or datatypes—rather than just working with their values.

**Casting Between `rdfnode` and Native PostgreSQL Types**

Although `rdfnode` preserves the full RDF term, you can cast it to standard PostgreSQL types like `text`, `int`, or `date` when you only care about the literal value. Likewise, native PostgreSQL values can be cast into `rdfnode`, with appropriate RDF serialization.

From `rdfnode` to PostgreSQL:

```sql
SELECT CAST('"42"^^<http://www.w3.org/2001/XMLSchema#int>'::rdfnode AS int);
 int4 
------
   42
(1 row)

SELECT CAST('"42.73"^^<http://www.w3.org/2001/XMLSchema#float>'::rdfnode AS numeric);
 numeric 
---------
   42.73
(1 row)

SELECT CAST('"2025-05-16"^^<http://www.w3.org/2001/XMLSchema#date>'::rdfnode AS date);
    date    
------------
 2025-05-16
(1 row)

SELECT CAST('"2025-05-16T06:41:50"^^<http://www.w3.org/2001/XMLSchema#dateTime>'::rdfnode AS timestamp);
      timestamp      
---------------------
 2025-05-16 06:41:50
(1 row)
```
From PostgreSQL to `rdfnode`:

```sql
SELECT CAST('"foo"^^xsd:string' AS rdfnode);
                     rdfnode                      
--------------------------------------------------
 "foo"^^<http://www.w3.org/2001/XMLSchema#string>
(1 row)

SELECT CAST(42.73 AS rdfnode);
                       rdfnode                       
-----------------------------------------------------
 "42.73"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)

SELECT CAST(422892987223 AS rdfnode);
                         rdfnode                         
---------------------------------------------------------
 "422892987223"^^<http://www.w3.org/2001/XMLSchema#long>
(1 row)

SELECT CAST(CURRENT_DATE AS rdfnode);
                     current_date                      
-------------------------------------------------------
 "2025-05-16"^^<http://www.w3.org/2001/XMLSchema#date>
(1 row)

SELECT CAST(CURRENT_TIMESTAMP AS rdfnode);
                             current_timestamp                              
----------------------------------------------------------------------------
 "2025-05-16T06:41:50.221129Z"^^<http://www.w3.org/2001/XMLSchema#dateTime>
(1 row)
```

**Choosing Between rdfnode and Native PostgreSQL Types**

You can define foreign table columns using either:

* `rdfnode` **(recommended)** — Use this when you want to preserve the full RDF term, including language tags, datatypes, and IRIs. This is also required if you want to use SPARQL functions, which do not support native PostgreSQL types.

* PostgreSQL native types (e.g., `text`, `int`, `date`) — Use these when you prefer automatic type coercion and simpler SQL filtering, treating RDF values more like regular PostgreSQL data.

**Comparison of `rdfnode` with Native PostgreSQL Types**

`rdfnode` supports standard comparison operators like `=`, `!=`, `<`, `<=`, `>`, `>=` — just like in SPARQL. Comparisons follow SPARQL 1.1 [RDFterm-equal](https://www.w3.org/TR/sparql11-query/#func-RDFterm-equal) rules.

Examples: `rdfnode` vs `rdfnode`

```sql
SELECT '"foo"@en'::rdfnode = '"foo"@fr'::rdfnode;
 ?column? 
----------
 f
(1 row)

SELECT '"foo"^^xsd:string'::rdfnode > '"foobar"^^xsd:string'::rdfnode;
 ?column? 
----------
 f
(1 row)

SELECT '"foo"^^xsd:string'::rdfnode < '"foobar"^^xsd:string'::rdfnode;
 ?column? 
----------
 t
(1 row)

 SELECT '"42"^^xsd:int'::rdfnode = '"42"^^xsd:short'::rdfnode;
 ?column? 
----------
 t
(1 row)

 SELECT '"73.42"^^xsd:float'::rdfnode < '"100"^^xsd:short'::rdfnode;
 ?column? 
----------
 t
(1 row)
```

The `rdfnode` data type also allow comparisons with PostgreSQL native data types, such as `int`, `date`, `numeric`, etc.

Examples: `rdfnode` vs PostgreSQL types

```sql
SELECT '"42"^^xsd:int'::rdfnode = 42;
 ?column? 
----------
 t
(1 row)

SELECT '"2010-01-08"^^xsd:date'::rdfnode < '2020-12-30'::date;
 ?column? 
----------
 t
(1 row)

SELECT '"42.73"^^xsd:decimal'::rdfnode > 42;
 ?column? 
----------
 t
(1 row)

SELECT '"42.73"^^xsd:decimal'::rdfnode < 42.99;
 ?column? 
----------
 t
(1 row)

SELECT '"2025-05-19T10:45:42Z"^^xsd:dateTime'::rdfnode = '2025-05-19 10:45:42'::timestamp;
 ?column? 
----------
 t
(1 row)
```

## [ALTER FOREIGN TABLE and ALTER SERVER](#alter-foreign-table-and-alter-server)

Use `ALTER FOREIGN TABLE` and `ALTER SERVER` to add, change, or remove options on a foreign table or server. Changes take effect for subsequent queries.

Add options

```sql
ALTER FOREIGN TABLE film
  OPTIONS (ADD enable_pushdown 'false', ADD log_sparql 'true');

ALTER SERVER dbpedia
  OPTIONS (ADD enable_pushdown 'false');
```

Change existing options

```sql
ALTER FOREIGN TABLE film
  OPTIONS (SET enable_pushdown 'false');

ALTER SERVER dbpedia
  OPTIONS (SET enable_pushdown 'true');
```

Remove options

```sql
ALTER FOREIGN TABLE film
  OPTIONS (DROP enable_pushdown, DROP log_sparql);

ALTER SERVER dbpedia
  OPTIONS (DROP enable_pushdown);
```

Privileges: You must own the object or be a superuser to alter a `SERVER` or `FOREIGN TABLE`.

## [Pushdown](#pushdown)

Pushdown means translating SQL so that operations like filtering, sorting and limiting are executed by the remote triplestore (SPARQL endpoint) rather than in PostgreSQL. Running these operations remotely reduces the amount of data transferred and can greatly improve performance.

If a clause such as `LIMIT` is not pushed down, the triplestore may produce the full result set and send it to PostgreSQL, which then applies the limit — causing unnecessary work and network traffic. `rdf_fdw` tries to convert SQL into SPARQL where possible, but SQL and SPARQL differ in expressive power and semantics, so not every construct can be pushed down.

To maximize pushdown and performance, keep queries against foreign tables simple. `rdf_fdw` supports pushdown for most [SPARQL 1.1 built-in functions](https://www.w3.org/TR/sparql11-query/#funcs) and for several PostgreSQL constructs (for example, `DISTINCT`, `LIMIT` and `IN`/`NOT IN`).

> [!NOTE]  
> Aggregate pushdown is currently **not** supported. While aggregate functions (such as `sparql.sum`, `sparql.avg`, `sparql.min`, `sparql.max`, `sparql.group_concat`, `sparql.sample`, etc.) are implemented and usable in SQL queries, they are always evaluated locally by PostgreSQL. The SPARQL endpoint does not perform aggregation for these queries! If you need remote aggregation, you must embed the aggregate in the foreign table's SPARQL option or run the query directly against the endpoint.

### [LIMIT](#limit)

`LIMIT` clauses are pushed down only if the SQL query does not contain aggregates and when all conditions in the `WHERE` clause can be translated to SPARQL.
 
| SQL | SPARQL|
| -- | --- |
| `LIMIT x`| `LIMIT x` 
| `FETCH FIRST x ROWS` | `LIMIT x` |
| `FETCH FIRST ROW ONLY` | `LIMIT 1` |

> [!NOTE]
> `OFFSET` pushdown is **not** supported, meaning that `OFFSET` filters will be applied **locally** in PostgreSQL.

Example:

```sql
SELECT p, o FROM rdbms
WHERE 
  p = sparql.iri('http://www.w3.org/2000/01/rdf-schema#label') AND
  sparql.lang(o) = 'pt'
FETCH FIRST 5 ROWS ONLY;

INFO:  SPARQL query sent to 'wikidata':

SELECT ?p ?o 
{
      ?s wdt:P31 wd:Q3932296 .
	  ?s ?p ?o
	 
 ## rdf_fdw pushdown conditions ##
 FILTER(?p = <http://www.w3.org/2000/01/rdf-schema#label>)
 FILTER(LANG(?o) = "pt")
}
LIMIT 5

INFO:  SPARQL returned 5 records.

                      p                       |             o             
----------------------------------------------+---------------------------
 <http://www.w3.org/2000/01/rdf-schema#label> | "Ingres"@pt
 <http://www.w3.org/2000/01/rdf-schema#label> | "Vectorwise"@pt
 <http://www.w3.org/2000/01/rdf-schema#label> | "PostgreSQL"@pt
 <http://www.w3.org/2000/01/rdf-schema#label> | "Microsoft SQL Server"@pt
 <http://www.w3.org/2000/01/rdf-schema#label> | "Firebird"@pt
(5 rows)
```

* `WHERE` expressions and `FETCH FIRST 5 ROWS ONLY` was pushed (as `LIMIT 5` in the SPARQL query).

### [ORDER BY](#order-by)

`ORDER BY` is pushed down when the involved expressions can be represented in SPARQL. `rdf_fdw` translates common SQL orderings to SPARQL `ORDER BY` using `ASC()` and `DESC()`.

| SQL | SPARQL |
|-----|--------|
| `ORDER BY x` or `ORDER BY x ASC` | `ORDER BY ASC(x)` |
| `ORDER BY x DESC` | `ORDER BY DESC(x)` |

Ordering across multiple columns is preserved when each expression is pushdown-capable. If an expression cannot be translated, ordering is applied locally in PostgreSQL.

Example (pushdown):

```sql
SELECT o FROM rdbms
WHERE 
  p = '<http://www.w3.org/2000/01/rdf-schema#label>' AND
  sparql.langmatches(sparql.lang(o), 'es')
ORDER BY p ASC, o DESC
FETCH FIRST 5 ROWS ONLY;

INFO:  SPARQL query sent to 'wikidata':

SELECT ?p ?o 
{
      ?s wdt:P31 wd:Q3932296 .
	  ?s ?p ?o
	 
 ## rdf_fdw pushdown conditions ##
 FILTER(?p = <http://www.w3.org/2000/01/rdf-schema#label>)
 FILTER(LANGMATCHES(LANG(?o), "es"))
}
ORDER BY  ASC (?p)  DESC (?o)
LIMIT 5

INFO:  SPARQL returned 5 records.

        o        
-----------------
 "Xeround"@es
 "WxSQLite3"@es
 "Vectorwise"@es
 "TimesTen"@es
 "Tibero"@es
(5 rows)
```

* All `WHERE`, `ORDER BY`, and `LIMIT` expressions were pushed down.


### [DISTINCT](#distinct)

`DISTINCT` is pushed down to the SPARQL `SELECT` when possible. If the foreign table's `sparql` option already contains `DISTINCT` or `REDUCED`, rdf_fdw will not push SQL `DISTINCT` again. There is no SPARQL equivalent of `DISTINCT ON`, so that PostgreSQL feature is always evaluated locally.

Example:

```sql
SELECT DISTINCT p, o FROM rdbms
WHERE 
  p = '<http://www.w3.org/2000/01/rdf-schema#label>' AND
  sparql.langmatches(sparql.lang(o), 'de');
INFO:  SPARQL query sent to 'wikidata':

SELECT DISTINCT ?p ?o 
{wd:Q192490 ?p ?o
 ## rdf_fdw pushdown conditions ##
 FILTER(?p = <http://www.w3.org/2000/01/rdf-schema#label>)
 FILTER(LANGMATCHES(LANG(?o), "de"))
}
ORDER BY  ASC (?p)  ASC (?o)

INFO:  SPARQL returned 1 record.

                      p                       |        o        
----------------------------------------------+-----------------
 <http://www.w3.org/2000/01/rdf-schema#label> | "PostgreSQL"@de
(1 row)
```

### [WHERE](d#where)

The `rdf_fdw` extension supports pushdown of many SQL expressions in the `WHERE` clause. When applicable, these expressions are translated into SPARQL `FILTER` clauses, allowing filtering to occur directly at the RDF data source. 

The following expressions in the `WHERE` clause are eligible for pushdown:

* Comparisons involving PostgreSQL data types (e.g., `integer`, `text`, `boolean`) or the custom type `rdfnode`, when used with the supported operators:

  **Supported Data Types and Operators**

  | Data type                                                  | Operators                             |
  |------------------------------------------------------------|---------------------------------------|
  | `rdfnode`                                                  | `=`, `!=`,`<>`, `>`, `>=`, `<`, `<=`  |
  | `text`, `char`, `varchar`, `name`                          | `=`, `<>`, `!=`, `~~`, `!~~`, `~~*`,`!~~*`                       |
  | `date`, `timestamp`, `timestamp with time zone`            | `=`, `<>`, `!=`, `>`, `>=`, `<`, `<=` |
  | `smallint`, `int`, `bigint`, `numeric`, `double precision` | `=`, `<>`, `!=`, `>`, `>=`, `<`, `<=` |
  | `boolean`                                                  | `IS`, `IS NOT`                        |

* `IN`/`NOT IN` and `ANY` constructs with constant lists.
  
  SQL `IN`  and `ANY` constructs are translated into the SPARQL [`IN` operator](https://www.w3.org/TR/2013/REC-sparql11-query-20130321/#func-in), which will be placed in a [`FILTER` evaluation](https://www.w3.org/TR/2013/REC-sparql11-query-20130321/#evaluation), as long as the list has the supported data types.

* Nearly all supported [SPARQL functions](#sparql-functions) are pushdown-capable, including:
  * `LANG()`, `DATATYPE()`, `STR()`, `isBLANK()`, `isIRI()`, etc.
  * Numeric, string, and datetime functions such as `ROUND()`, `STRLEN()`, `YEAR()`, and others.
  
> [!NOTE]  
> Due to their volatile nature, the SPARQL functions `sparql.rand()` and `sparql.now()` cannot be pushed down. Because their results cannot be reproduced consistently by PostgreSQL, any rows returned from the endpoint would be filtered out locally during re-evaluation.

**Conditions That Prevent Pushdown**

A `WHERE` condition will not be pushed down if:

* The option `enable_pushdown` is set to `false`.
* The underlying SPARQL query includes:
  * a `GROUP BY` clause
  * solution modifiers like `OFFSET`, `ORDER BY`, `LIMIT`, `DISTINCT`, or `REDUCED`
  * subqueries or federated queries
* The condition includes an unsupported data type or operator.
* The condition contains `OR` logical operators (not yet supported).

#### Pushdown Examples

For the examples in this section consider this `SERVER` and `FOREIGN TABLE` setting (Wikidata):

```sql
CREATE SERVER wikidata
FOREIGN DATA WRAPPER rdf_fdw 
OPTIONS (endpoint 'https://query.wikidata.org/sparql');

CREATE FOREIGN TABLE rdbms (
  s rdfnode OPTIONS (variable '?s'),
  p rdfnode OPTIONS (variable '?p'),
  o rdfnode OPTIONS (variable '?o')
)
SERVER wikidata OPTIONS (
  sparql 
    'SELECT * {
      ?s wdt:P31 wd:Q3932296 .
	  ?s ?p ?o
	 }'
);
```

1. Pusdown of `WHERE` conditions involving `rdfnode` values and `=` and `!=` operators. All conditions are pushed as `FILTER` expressions.

```sql
SELECT s, o FROM rdbms
WHERE 
  o = '"PostgreSQL"@es' AND
  o <> '"Oracle"@es';
INFO:  SPARQL query sent to 'wikidata':

SELECT ?s ?o 
{
      ?s wdt:P31 wd:Q3932296 .
	  ?s ?p ?o
	 
 ## rdf_fdw pushdown conditions ##
 FILTER(?o = "PostgreSQL"@es)
 FILTER(?o != "Oracle"@es)
}

INFO:  SPARQL returned 1 record.

                    s                     |        o        
------------------------------------------+-----------------
 <http://www.wikidata.org/entity/Q192490> | "PostgreSQL"@es
(1 row)
```

2. Pusdown of `WHERE` conditions involving `rdfnode` values and `=`, `>`, and `<` operators. All conditions are pushed down as `FILTER` expressions. Note that the `timestamp` values are automatically cast to the correspondent XSD data type.

```sql
SELECT s, o FROM rdbms
WHERE 
  p = '<http://www.wikidata.org/prop/direct/P577>' AND
  o > '1996-01-01'::timestamp AND o < '1996-12-31'::timestamp;
INFO:  SPARQL query sent to 'wikidata':

SELECT ?s ?p ?o 
{
      ?s wdt:P31 wd:Q3932296 .
	  ?s ?p ?o
	 
 ## rdf_fdw pushdown conditions ##
 FILTER(?p = <http://www.wikidata.org/prop/direct/P577>)
 FILTER(?o > "1996-01-01T00:00:00"^^<http://www.w3.org/2001/XMLSchema#dateTime>)
 FILTER(?o < "1996-12-31T00:00:00"^^<http://www.w3.org/2001/XMLSchema#dateTime>)
}

INFO:  SPARQL returned 1 record.

                    s                     |                                  o                                  
------------------------------------------+---------------------------------------------------------------------
 <http://www.wikidata.org/entity/Q192490> | "1996-07-08T00:00:00Z"^^<http://www.w3.org/2001/XMLSchema#dateTime>
(1 row)
```

3. Pusdown of `WHERE` conditions with `IN` and `ANY` constructs. All conditions are pushed down as `FILTER` expressions.

```sql
SELECT p, o FROM rdbms
WHERE 
  p = '<http://www.w3.org/2000/01/rdf-schema#label>' AND
  o IN ('"PostgreSQL"@en', '"IBM Db2"@fr', '"MySQL"@es');
INFO:  SPARQL query sent to 'wikidata':

SELECT ?p ?o 
{
      ?s wdt:P31 wd:Q3932296 .
	  ?s ?p ?o
	 
 ## rdf_fdw pushdown conditions ##
 FILTER(?p = <http://www.w3.org/2000/01/rdf-schema#label>)
 FILTER(?o IN ("PostgreSQL"@en, "IBM Db2"@fr, "MySQL"@es))
}

INFO:  SPARQL returned 2 records.

                      p                       |        o        
----------------------------------------------+-----------------
 <http://www.w3.org/2000/01/rdf-schema#label> | "PostgreSQL"@en
 <http://www.w3.org/2000/01/rdf-schema#label> | "IBM Db2"@fr
(2 rows)
```

```sql
SELECT p, o FROM rdbms
WHERE 
  p = '<http://www.w3.org/2000/01/rdf-schema#label>' AND
  o = ANY(ARRAY['"PostgreSQL"@en'::rdfnode,'"IBM Db2"@fr'::rdfnode,'"MySQL"@es'::rdfnode]);

INFO:  SPARQL query sent to 'wikidata':

SELECT ?p ?o 
{
      ?s wdt:P31 wd:Q3932296 .
	  ?s ?p ?o
	 
 ## rdf_fdw pushdown conditions ##
 FILTER(?p = <http://www.w3.org/2000/01/rdf-schema#label>)
 FILTER(?o IN ("PostgreSQL"@en, "IBM Db2"@fr, "MySQL"@es))
}

INFO:  SPARQL returned 2 records.

                      p                       |        o        
----------------------------------------------+-----------------
 <http://www.w3.org/2000/01/rdf-schema#label> | "PostgreSQL"@en
 <http://www.w3.org/2000/01/rdf-schema#label> | "IBM Db2"@fr
(2 rows)
```

4. Pusdown of `WHERE` conditions involving SPARQL functions. The function calls for `LANGMATCHES()`, `LANG()`, and `STRENDS()` are pushed down in `FILTER` expressions.

```sql
SELECT s, o FROM rdbms
WHERE 
  p = sparql.iri('http://www.w3.org/2000/01/rdf-schema#label') AND
  sparql.langmatches(sparql.lang(o), 'de') AND
  sparql.strends(o, sparql.strlang('SQL','de'));

INFO:  SPARQL query sent to 'wikidata':

SELECT ?s ?p ?o 
{
      ?s wdt:P31 wd:Q3932296 .
	  ?s ?p ?o
	 
 ## rdf_fdw pushdown conditions ##
 FILTER(?p = <http://www.w3.org/2000/01/rdf-schema#label>)
 FILTER(LANGMATCHES(LANG(?o), "de"))
 FILTER(STRENDS(?o, "SQL"@de))
}

INFO:  SPARQL returned 3 records.

                     s                     |        o        
-------------------------------------------+-----------------
 <http://www.wikidata.org/entity/Q192490>  | "PostgreSQL"@de
 <http://www.wikidata.org/entity/Q5014224> | "CSQL"@de
 <http://www.wikidata.org/entity/Q6862049> | "Mimer SQL"@de
(3 rows)
```
### [Prefix Management](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#prefix-mangement)

To simplify the reuse and sharing of common SPARQL prefixes, `rdf_fdw` provides a prefix management system based on two catalog tables and a suite of helper functions.

This feature enables you to register prefix contexts (named groups of prefixes), and to associate specific prefix -> URI mappings under those contexts. This is especially useful when working with multiple RDF vocabularies or endpoint configurations.

#### [Prefix Context](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#context)

The prefix context is a named container for a set of SPARQL prefixes. It is represented by the table `sparql.prefix_contexts`:

| Column        | Type          | Description                          |
| ------------- | ------------- | ------------------------------------ |
| `context`     | `text`        | Primary key; name of the context.    |
| `description` | `text`        | Optional description of the context. |
| `modified_at` | `timestamptz` | Timestamp of the last update.        |

##### Prefix Context Functions

**Adding a new context**
```sql
sparql.add_context(context_name text, context_description text DEFAULT NULL, override boolean DEFAULT false)
```

Registers a new context. If override is set to `true` updates the context if it already exists, otherwise, raises an exception on conflict.

**Deleting an existing context**

```sql
sparql.drop_context(context_name text, cascade boolean DEFAULT false)
```
Deletes a context. If cascade is set to `true` deletes all associated prefixes, otherwise raises an exception if dependent prefixes exist.

#### [Prefix](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#prefix)

A prefix maps a shorthand identifier to a full URI within a context. These are stored in `sparql.prefixes`:

| Column        | Type          | Description                       |
| ------------- | ------------- | --------------------------------- |
| `prefix`      | `text`        | The SPARQL prefix label.          |
| `uri`         | `text`        | The fully qualified URI.          |
| `context`     | `text`        | Foreign key to `prefix_contexts`. |
| `modified_at` | `timestamptz` | Timestamp of the last update.     |

##### Prefix Functions

**Adding a new PREFIX**
```sql
sparql.add_prefix(context_name text, prefix_name text, uri text, override boolean DEFAULT false)
```
Adds a prefix to a context. If override is set to `true` updates the URI if the prefix already exists. Otherwise raises an exception on conflict.

**Deleting an existing PREFIX**

```sql
sparql.drop_prefix(context_name text, prefix_name text)
```
Removes a prefix from a context. Raises an exception if the prefix does not exist.

**Examples**

```sql
-- Create a context
SELECT sparql.add_context('default', 'Default SPARQL prefix context');

-- Add prefixes to it
SELECT sparql.add_prefix('default', 'rdf',  'http://www.w3.org/1999/02/22-rdf-syntax-ns#');
SELECT sparql.add_prefix('default', 'rdfs', 'http://www.w3.org/2000/01/rdf-schema#');
SELECT sparql.add_prefix('default', 'owl',  'http://www.w3.org/2002/07/owl#');
SELECT sparql.add_prefix('default', 'xsd',  'http://www.w3.org/2001/XMLSchema#');
```
Once registered, these prefixes can be automatically included in generated SPARQL queries for any `rdf_fdw` foreign server that references the associated context.

## [Data Modification](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#data-modification)

The `rdf_fdw` extension supports data modification operations (`INSERT`, `UPDATE`, `DELETE`) on foreign tables connected to RDF triplestores. These operations allow you to add, modify, or remove RDF triples directly through SQL statements.

> [!NOTE]  
> Data modification operations require the `sparql_update_pattern` option to be set on the `FOREIGN TABLE`. This option specifies a SPARQL triple pattern template that defines how rows from PostgreSQL are converted into SPARQL UPDATE statements.

### General Requirements

To use data modification operations, your `FOREIGN TABLE` must:

1. **Define the `sparql_update_pattern` option** - A template specifying the RDF triple pattern(s) to be modified.
2. **Map all required columns** - Each variable used in `sparql_update_pattern` must be mapped to an existing table column via the column's OPTIONS (e.g., `OPTIONS (variable '?s')`).
3. **Use `rdfnode` columns** - Data modification operations only support `rdfnode` type columns; PostgreSQL native types are **not supported**.

> [!IMPORTANT]  
> **SPARQL endpoints do not support PostgreSQL transactions.** Each operation is sent immediately to the triplestore and committed there, regardless of PostgreSQL's transaction state (BEGIN/COMMIT/ROLLBACK).

### NULL Value Handling

* **NULL values are not allowed** - Any attempt to insert or update a triple with a NULL component will raise an error. This prevents incomplete or invalid triples from being written to the triplestore.

### [INSERT](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#insert)

The `INSERT` statement allows you to add new RDF triples to a triplestore. Each row inserted into a `FOREIGN TABLE` is converted into a SPARQL `INSERT DATA` statement and sent to the remote SPARQL endpoint.

### Usage:

```sql
INSERT INTO ft (subject, predicate, object) VALUES
  ('<https://www.uni-muenster.de>',
  '<http://www.w3.org/2000/01/rdf-schema#label>',
  '"Westfälische Wilhelms-Universität Münster"@de');
```

### [UPDATE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#update-sql)

The `UPDATE` statement allows you to modify existing RDF triples in a triplestore. Since SPARQL does not have a direct UPDATE syntax, each row update is implemented as a combination of `DELETE DATA` (removing old triples) followed by `INSERT DATA` (adding new triples).

### Usage:

```sql
UPDATE ft SET
  object = '"University of Münster"@en'
WHERE subject = '<https://www.uni-muenster.de>'
  AND predicate = '<http://www.w3.org/2000/01/rdf-schema#label>';
```

### [DELETE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#delete)

The `DELETE` statement allows you to remove RDF triples from a triplestore. Each row deleted from a `FOREIGN TABLE` is converted into a SPARQL `DELETE DATA` statement and sent to the remote SPARQL endpoint.

#### Usage:

```sql
DELETE FROM ft 
WHERE object = '"Westfälische Wilhelms-Universität Münster"@de'::rdfnode;
```
### [Update Examples](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#update-examples)

```sql
CREATE SERVER fuseki
FOREIGN DATA WRAPPER rdf_fdw 
OPTIONS (
  endpoint   'http://fuseki:3030/dt/sparql',
  update_url 'http://fuseki:3030/dt/update');

CREATE FOREIGN TABLE ft (
  subject   rdfnode OPTIONS (variable '?s'),
  predicate rdfnode OPTIONS (variable '?p'),
  object    rdfnode OPTIONS (variable '?o') 
)
SERVER fuseki OPTIONS (
  log_sparql 'false',
  sparql 
    $$
     SELECT * 
     WHERE {
       ?s ?p ?o .
       ?s <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <https://dbpedia.org/resource/University>      
     }
    $$,
  sparql_update_pattern 
    $$
      ?s ?p ?o .
      ?s <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <https://dbpedia.org/resource/University>
    $$
);

CREATE USER MAPPING FOR postgres
SERVER fuseki OPTIONS (user 'admin', password 'secret');

INSERT INTO ft (subject, predicate, object)
VALUES  ('<https://www.uni-muenster.de>', '<http://www.w3.org/2000/01/rdf-schema#label>', '"University of Münster"@en');

SELECT * FROM ft;
            subject            |                     predicate                     |                  object                   
-------------------------------+---------------------------------------------------+-------------------------------------------
 <https://www.uni-muenster.de> | <http://www.w3.org/2000/01/rdf-schema#label>      | "University of Münster"@en
 <https://www.uni-muenster.de> | <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> | <https://dbpedia.org/resource/University>
(2 rows)

UPDATE ft SET
  object = '"Westfälische Wilhelms-Universität Münster"@de'
WHERE subject = '<https://www.uni-muenster.de>'
  AND predicate = '<http://www.w3.org/2000/01/rdf-schema#label>';

SELECT * FROM ft;
            subject            |                     predicate                     |                     object                     
-------------------------------+---------------------------------------------------+------------------------------------------------
 <https://www.uni-muenster.de> | <http://www.w3.org/2000/01/rdf-schema#label>      | "Westfälische Wilhelms-Universität Münster"@de
 <https://www.uni-muenster.de> | <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> | <https://dbpedia.org/resource/University>
(2 rows)

DELETE FROM ft
WHERE subject = '<https://www.uni-muenster.de>';

SELECT * FROM ft;
 subject | predicate | object 
---------+-----------+--------
(0 rows)
```
### [rdf_fdw_version](#rdf_fdw_version)

```sql
text rdf_fdw_version();
```

**Description**

Returns version information for `rdf_fdw`, PostgreSQL, compiler, and all dependencies (libxml, libcurl) in a single formatted string.

-------

**Usage**

```sql
SELECT rdf_fdw_version();
                                            rdf_fdw_version                                             
--------------------------------------------------------------------------------------------------------
 rdf_fdw 2.5 (PostgreSQL 18.1 (Debian 18.1-1.pgdg13+2), compiled by gcc, libxml 2.9.14, libcurl 8.14.1)
(1 row)
```

### [rdf_fdw_settings](#rdf_fdw_settings)

```sql
VIEW rdf_fdw_settings(component text, version text);
```

**Description**

A system view that provides detailed version information for `rdf_fdw` and all its dependencies, including core libraries (PostgreSQL, libxml, libcurl) and optional components (SSL, zlib, libSSH, nghttp2), along with compiler and build information. Returns individual component names and their corresponding versions for convenient programmatic access.

-------

**Usage**

```sql
SELECT * FROM rdf_fdw_settings;
 component  |            version            
------------+-------------------------------
 rdf_fdw    | 2.5
 PostgreSQL | 18.1 (Debian 18.1-1.pgdg13+2)
 libxml     | 2.9.14
 libcurl    | 8.14.1
 ssl        | GnuTLS/3.8.9
 zlib       | 1.3.1
 libSSH     | libssh2/1.11.1
 nghttp2    | 1.64.0
 compiler   | gcc
 built      | 2026-04-19 17:50:09 UTC
(10 rows)
```

### [rdf_fdw_clone_table](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#rdf_fdw_clone_table)

```sql
void rdf_fdw_clone_table(
  foreign_table text,
  target_table text,
  begin_offset int,
  fetch_size int,
  max_records int,
  orderby_column text,
  sort_order text,
  create_table boolean,
  verbose boolean,
  commit_page boolean
)
```

* PostgreSQL 11+ only

**Description**

This procedure is designed to copy data from a `FOREIGN TABLE` to an ordinary `TABLE`. It provides the possibility to retrieve the data set in batches, so that known issues related to triplestore limits and client's memory don't bother too much. 

**Parameters**

`foreign_table` **(required)**:  `FOREIGN TABLE` from where the data has to be copied.

`target_table` **(required)**: heap `TABLE` where the data from the `FOREIGN TABLE` is copied to.

`begin_offset`: starting point in the SPARQL query pagination. Default `0`.

`fetch_size`: size of the page fetched from the triplestore. Default is the value set at `fetch_size` in either `SERVER` or `FOREIGN TABLE`. In case `SERVER` and `FOREIGN TABLE` do not set `fetch_size`, the default will be set to `100`.

`max_records`: maximum number of records that should be retrieved from the `FOREIGN TABLE`. Default `0`, which means no limit. 

`orderby_column`: ordering column used for the pagination - just like in SQL `ORDER BY`. Default `''`, which means that the function will chose a column to use in the `ORDER BY` clause on its own. That is, the procedure will try to set the first column with the option `nodetype` set to `iri`. If the table has no `iri` typed `nodetype`, the first column will be chosen as ordering column. If you do not wish to have an `ORDER BY` clause at all, set this parameter to `NULL`.

`sort_order`: `ASC` or `DESC` to sort the data returned in ascending or descending order, respectively. Default `ASC`.

`create_table`: creates the table set in `target_table` before harvesting the `FOREIGN TABLE`. Default `false`.

`verbose`: prints debugging messages in the standard output. Default `false`.

`commit_page`: commits the inserted records immediately or only after the transaction is finished. Useful for those who want records to be discarded in case of an error - following the principle of *everything or nothing*. Default `true`, which means that all inserts will be committed immediately.

-------

**Usage Example**

```sql
CREATE SERVER dbpedia
FOREIGN DATA WRAPPER rdf_fdw 
OPTIONS (endpoint 'https://dbpedia.org/sparql');

CREATE FOREIGN TABLE public.dbpedia_cities (
  uri text           OPTIONS (variable '?city', nodetype 'iri'),
  city_name text     OPTIONS (variable '?name', nodetype 'literal', literal_type 'xsd:string'),
  elevation numeric  OPTIONS (variable '?elevation', nodetype 'literal', literal_type 'xsd:integer')
)
SERVER dbpedia OPTIONS (
  sparql '
    PREFIX dbo:  <http://dbpedia.org/ontology/>
    PREFIX foaf: <http://xmlns.com/foaf/0.1/>
    PREFIX dbr:  <http://dbpedia.org/resource/>
    SELECT *
    {?city a dbo:City ;
      foaf:name ?name ;
      dbo:federalState dbr:North_Rhine-Westphalia ;
      dbo:elevation ?elevation
    }
');

/*
 * Materialize all records from the FOREIGN TABLE 'public.dbpedia_cities' in 
 * the table 'public.t1_local'. 
 */ 
CALL rdf_fdw_clone_table(
      foreign_table => 'dbpedia_cities',
      target_table  => 't1_local',
      create_table => true);

SELECT * FROM t1_local;
                            uri                            |      city_name      | elevation 
-----------------------------------------------------------+---------------------+-----------
 http://dbpedia.org/resource/Aachen                        | Aachen              |     173.0
 http://dbpedia.org/resource/Bielefeld                     | Bielefeld           |     118.0
 http://dbpedia.org/resource/Dortmund                      | Dortmund            |      86.0
 http://dbpedia.org/resource/Düsseldorf                    | Düsseldorf          |      38.0
 http://dbpedia.org/resource/Gelsenkirchen                 | Gelsenkirchen       |      60.0
 http://dbpedia.org/resource/Hagen                         | Hagen               |     106.0
 http://dbpedia.org/resource/Hamm                          | Hamm                |      37.7
 http://dbpedia.org/resource/Herne,_North_Rhine-Westphalia | Herne               |      65.0
 http://dbpedia.org/resource/Krefeld                       | Krefeld             |      39.0
 http://dbpedia.org/resource/Mönchengladbach               | Mönchengladbach     |      70.0
 http://dbpedia.org/resource/Mülheim                       | Mülheim an der Ruhr |      26.0
 http://dbpedia.org/resource/Münster                       | Münster             |      60.0
 http://dbpedia.org/resource/Remscheid                     | Remscheid           |     365.0
(13 rows)
```
### [EXPLAIN and Diagnostics](#explain-and-diagnostics)

The `rdf_fdw` extension provides detailed diagnostics in PostgreSQL [EXPLAIN](https://www.postgresql.org/docs/current/sql-explain.html) output to help users understand which SQL clauses are pushed down to the remote SPARQL endpoint.

The plan output includes FDW-specific lines for each Foreign Scan node:
* `Foreign Server:` shows the foreign server related to the queried foreign table.
* `Pushdown: enabled` or `Pushdown: disabled`
* `Remote Filter:` shows the SPARQL FILTER expression(s) generated from SQL WHERE clauses.  
  If the WHERE clause cannot be translated to SPARQL FILTER expressions, the plan will display `Remote Filter: not pushable` to indicate that filtering is performed locally in PostgreSQL.
* `Remote Sort Key:` shows the SPARQL ORDER BY clause if sorting is pushed down.
* `Remote Limit:` shows the SPARQL LIMIT clause if limiting is pushed down.
* `Remote Select:` shows the SPARQL SELECT clause generated for the query.

**Example:**
```sql
EXPLAIN (ANALYSE, COSTS OFF)
SELECT p, o FROM ft
WHERE sparql.isnumeric(o) AND o > 42
ORDER BY o DESC
FETCH FIRST 3 ROWS ONLY;
                                 QUERY PLAN                                  
-----------------------------------------------------------------------------
 Limit (actual time=0.072..0.073 rows=3.00 loops=1)
   ->  Sort (actual time=0.071..0.072 rows=3.00 loops=1)
         Sort Key: o DESC
         Sort Method: quicksort  Memory: 25kB
         ->  Foreign Scan on ft (actual time=0.039..0.063 rows=3.00 loops=1)
               Foreign Server: wikidata
               Pushdown: enabled
               Remote Select: ?p ?o 
               Remote Filter: ((ISNUMERIC(?o)) && (?o > 42))
               Remote Sort Key:   DESC (?o)
               Remote Limit: LIMIT 3
 Planning:
   Buffers: shared hit=4
 Planning Time: 0.115 ms
 Execution Time: 182.551 ms
(15 rows)
```

## [SPARQL Functions](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#sparql-functions)

`rdf_fdw` implements most of the [SPARQL 1.1 built-in functions](https://www.w3.org/TR/sparql11-query/#funcs), exposing them as SQL-callable functions under the dedicated `sparql` schema. This avoids conflicts with similarly named built-in PostgreSQL functions such as `round`, `replace`, or `ceil`. These functions operate on RDF values retrieved through `FOREIGN TABLEs` and can be used in SQL queries or as part of pushdown expressions. They adhere closely to SPARQL semantics, including handling of RDF literals, language tags, datatypes, and null propagation rules, enabling expressive and standards-compliant RDF querying directly inside PostgreSQL.

> [!WARNING]  
> While most RDF triplestores claim SPARQL 1.1 compliance, their behavior often diverges from the standard—particularly in how they handle literals with language tags or datatypes. For example, the following query may produce different results depending on the backend:
>
>```sparql
>SELECT (REPLACE("foo"@en, "o"@de, "xx"@fr) AS ?str) {}
>```
>* Virtuoso &rarr; `"fxxxx"`
>* Blazegraph &rarr; **Unknown error**: *incompatible operand for REPLACE: "o"@de*
>* GraphDB &rarr; `"fxxxx"@en`
>
>Such inconsistencies can lead to unexpected or confusing results. To avoid surprises:
>* Always test how your target triplestore handles tagged or typed literals.
>* Consider simpler (less performant) alternatives like [`STR`](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#str) when working with language-tagged values.
>* Verify the accuracy of results, compare the number of records returned by the SPARQL endpoint with those stored in PostgreSQL. You can do this by analyzing the [EXPLAIN and Diagnostics](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#explain-and-diagnostics) output or by reviewing the SPARQL query logs generated using the `log_sparql` table option. If the SPARQL query yields more records than are displayed on the client side, it may indicate that some records were filtered out locally due to inconsistencies in pushdown function evaluation.

### [Aggregates](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#aggregates)


> [!NOTE]  
> **Aggregate semantics and NULL/UNDEF handling**
>
> SPARQL 1.1 aggregates operate over multisets after excluding unbound (UNDEF) and error results. If, after exclusion, no values remain:
> - GROUP_CONCAT → empty string
> - SUM, AVG, MIN, MAX → unbound (NULL)
>
> See: SPARQL 1.1 Query — Aggregates (§18), SUM/AVG/MIN/MAX (§18.5.1.3–§18.5.1.6), ORDER BY semantics (§15.1).
> 
> `rdf_fdw` treats SQL NULLs as SPARQL UNDEF. During aggregation, UNDEF values are excluded (skipped). Example:
>
> ```sql
> WITH j (val) AS (
>    VALUES
>        ('"10"^^<http://www.w3.org/2001/XMLSchema#integer>'::rdfnode),
>        (NULL::rdfnode),
>        ('"30"^^<http://www.w3.org/2001/XMLSchema#integer>'::rdfnode)
>)
>SELECT sparql.sum(val), sparql.avg(val) FROM j;
>                       sum                        |                        avg                         
>--------------------------------------------------+----------------------------------------------------
> "40"^^<http://www.w3.org/2001/XMLSchema#integer> | "20.0"^^<http://www.w3.org/2001/XMLSchema#decimal>
>(1 row)
>```

#### [SUM](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#sum)

```sql
sparql.sum(value rdfnode) → rdfnode
```

Computes the sum of numeric `rdfnode` values with XSD type promotion according to SPARQL 1.1 specification ([section 18.5.1.3](https://www.w3.org/TR/sparql11-query/#aggregates)). The function follows XPath type promotion rules where numeric types are promoted in the hierarchy: `xsd:integer` < `xsd:decimal` < `xsd:float` < `xsd:double`. The result type is determined by the highest type encountered during aggregation.

Examples:

```sql
-- Sum of integers returns integer
SELECT sparql.sum(val) 
FROM (VALUES ('"10"^^xsd:integer'::rdfnode),
             ('"20"^^xsd:integer'::rdfnode),
             ('"30"^^xsd:integer'::rdfnode)) AS t(val);
                       sum                        
--------------------------------------------------
 "60"^^<http://www.w3.org/2001/XMLSchema#integer>
(1 row)

-- Mixing integer and decimal promotes to decimal
SELECT sparql.sum(val)
FROM (VALUES ('"10"^^xsd:integer'::rdfnode), 
             ('"20.5"^^xsd:decimal'::rdfnode),
             ('"30"^^xsd:integer'::rdfnode)) AS t(val);
                        sum                         
----------------------------------------------------
 "60.5"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)

-- Mixing with float promotes to float
SELECT sparql.sum(val)
FROM (VALUES ('"10.5"^^xsd:decimal'::rdfnode),
             ('"20.3"^^xsd:decimal'::rdfnode),
             ('"5"^^xsd:float'::rdfnode)) AS t(val);
                       sum                        
--------------------------------------------------
 "35.8"^^<http://www.w3.org/2001/XMLSchema#float>
(1 row)
```

> [!NOTE]  
> The `SUM` aggregate follows SPARQL 1.1 semantics ([section 18.5.1.3](https://www.w3.org/TR/sparql11-query/#aggregates)):
>* NULL values (unbound variables) are skipped during aggregation
>* Returns `"0"^^xsd:integer` for empty sets or when all values are NULL (per spec: "The sum of no bindings is 0")
>* Non-numeric values cause type errors and are excluded from the aggregate (similar to NULL)
>* Returns SQL NULL if all values are non-numeric (no numeric values to sum)
>* Type promotion ensures precision is maintained (e.g., integer → decimal → float → double)
>* All XSD integer subtypes (`xsd:int`, `xsd:long`, `xsd:short`, `xsd:byte`, etc.) are treated as `xsd:integer`

#### [AVG](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#avg)

```sql
sparql.avg(value rdfnode) → rdfnode
```

Computes the average (arithmetic mean) of numeric `rdfnode` values with XSD type promotion according to SPARQL 1.1 specification ([section 18.5.1.4](https://www.w3.org/TR/sparql11-query/#aggregates)). Like `SUM`, the function follows XPath type promotion rules: `xsd:integer` < `xsd:decimal` < `xsd:float` < `xsd:double`. The result type is determined by the highest type encountered during aggregation.

Examples:

```sql
-- Average of integers returns decimal
SELECT sparql.avg(val)
FROM (VALUES ('"10"^^xsd:integer'::rdfnode),
             ('"20"^^xsd:integer'::rdfnode),
             ('"30"^^xsd:integer'::rdfnode)) AS t(val);
                        avg                         
----------------------------------------------------
 "20.0"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)

SELECT sparql.avg(val)
FROM (VALUES ('"10"^^xsd:integer'::rdfnode),
             ('"20.5"^^xsd:decimal'::rdfnode),
             ('"30"^^xsd:integer'::rdfnode)) AS t(val);
                                avg                                
-------------------------------------------------------------------
 "20.1666666666666667"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)

-- NULL values are skipped
SELECT sparql.avg(val)
FROM (VALUES ('"10"^^xsd:integer'::rdfnode),
             (NULL::rdfnode),
             ('"30"^^xsd:integer'::rdfnode)) AS t(val);
                        avg                         
----------------------------------------------------
 "20.0"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)
```

#### [MIN](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#min)

```sql
sparql.min(value rdfnode) → rdfnode
```

Returns the minimum numeric `rdfnode` value according to SPARQL 1.1 specification ([section 18.5.1.5](https://www.w3.org/TR/sparql11-query/#aggregates)). The function preserves the XSD datatype of the minimum value found. When comparing values of different numeric types, they are promoted to a common type following XPath rules before comparison.

Examples:

```sql
-- Minimum of integers
SELECT sparql.min(val)
FROM (VALUES ('"30"^^xsd:integer'::rdfnode),
             ('"10"^^xsd:integer'::rdfnode),
             ('"20"^^xsd:integer'::rdfnode)) AS t(val);
                       min                        
--------------------------------------------------
 "10"^^<http://www.w3.org/2001/XMLSchema#integer>
(1 row)

-- Minimum with negative values
SELECT sparql.min(val)
FROM (VALUES ('"10"^^xsd:integer'::rdfnode),
             ('"-5"^^xsd:integer'::rdfnode),
             ('"3"^^xsd:integer'::rdfnode)) AS t(val);
                       min                        
--------------------------------------------------
 "-5"^^<http://www.w3.org/2001/XMLSchema#integer>
(1 row)

-- NULL values skipped
SELECT sparql.min(val)
FROM (VALUES ('"10"^^xsd:integer'::rdfnode),
             (NULL::rdfnode),
             ('"3"^^xsd:integer'::rdfnode)) AS t(val);
                       min                       
-------------------------------------------------
 "3"^^<http://www.w3.org/2001/XMLSchema#integer>
(1 row)
```


#### [MAX](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#max)

```sql
sparql.max(value rdfnode) → rdfnode
```

Returns the maximum numeric `rdfnode` value according to SPARQL 1.1 specification ([section 18.5.1.6](https://www.w3.org/TR/sparql11-query/#aggregates)). The function preserves the XSD datatype of the maximum value found. When comparing values of different numeric types, they are promoted to a common type following XPath rules before comparison.

Examples:

```sql
-- Maximum of integers
SELECT sparql.max(val)
FROM (VALUES ('"30"^^xsd:integer'::rdfnode),
             ('"10"^^xsd:integer'::rdfnode),
             ('"20"^^xsd:integer'::rdfnode)) AS t(val);
                       max                        
--------------------------------------------------
 "30"^^<http://www.w3.org/2001/XMLSchema#integer>
(1 row)

-- Maximum with negative values
SELECT sparql.max(val)
FROM (VALUES ('"-10"^^xsd:integer'::rdfnode),
             ('"-5"^^xsd:integer'::rdfnode),
             ('"-20"^^xsd:integer'::rdfnode)) AS t(val);
                       max                        
--------------------------------------------------
 "-5"^^<http://www.w3.org/2001/XMLSchema#integer>
(1 row)

-- NULL value skipped
SELECT sparql.max(val)
FROM (VALUES ('"10"^^xsd:integer'::rdfnode),
             (NULL::rdfnode),
             ('"3"^^xsd:integer'::rdfnode)) AS t(val);
                       max                        
--------------------------------------------------
 "10"^^<http://www.w3.org/2001/XMLSchema#integer>
(1 row)
```

#### [GROUP_CONCAT](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#group_concat)

```sql
sparql.group_concat(value rdfnode, separator text) → rdfnode
```

Concatenates string representations of RDF terms into a single `xsd:string` literal according to SPARQL 1.1 specification ([section 18.5.1.7](https://www.w3.org/TR/sparql11-query/#aggregates)). The function extracts lexical values from all RDF term types (literals, IRIs, typed values) and joins them using the specified separator. Unlike PostgreSQL's `string_agg`, the separator parameter is required.

RDF term serialization rules:
* **Typed literals**: Extract lexical value only (strip `^^datatype`)
* **Language-tagged literals**: Extract lexical value only (strip `@lang`)
* **IRIs**: Extract URI string (strip angle brackets `< >`)
* **Plain literals**: Use as-is

Examples:

```sql
-- Concatenate strings with default space separator
SELECT sparql.group_concat(val, ' ')
FROM (VALUES ('"apple"^^xsd:string'::rdfnode),
             ('"banana"^^xsd:string'::rdfnode),
             ('"cherry"^^xsd:string'::rdfnode)) AS t(val);
     group_concat      
-----------------------
 "apple banana cherry"
(1 row)

-- Concatenate with custom separator
SELECT sparql.group_concat(val, ', ')
FROM (VALUES ('"apple"^^xsd:string'::rdfnode),
             ('"banana"^^xsd:string'::rdfnode),
             ('"cherry"^^xsd:string'::rdfnode)) AS t(val);
      group_concat       
-------------------------
 "apple, banana, cherry"
(1 row)

-- Mixed RDF types (integers, strings, floats)
SELECT sparql.group_concat(val, ' | ')
FROM (VALUES ('"42"^^xsd:integer'::rdfnode),
             ('"hello"^^xsd:string'::rdfnode),
             ('"3.14"^^xsd:float'::rdfnode)) AS t(val);
    group_concat     
---------------------
 "42 | hello | 3.14"
(1 row)

-- IRIs extract URI without angle brackets
SELECT sparql.group_concat(val, '; ')
FROM (VALUES ('<http://example.org/resource1>'::rdfnode),
             ('<http://example.org/resource2>'::rdfnode)) AS t(val);
                         group_concat                         
--------------------------------------------------------------
 "http://example.org/resource1; http://example.org/resource2"
(1 row)

-- Language-tagged strings extract lexical value
SELECT sparql.group_concat(val, ', ')
FROM (VALUES ('"hello"@en'::rdfnode),
             ('"bonjour"@fr'::rdfnode),
             ('"hola"@es'::rdfnode)) AS t(val);
      group_concat      
------------------------
 "hello, bonjour, hola"
(1 row)

-- NULL value skipped
SELECT sparql.group_concat(val, ' ')
FROM (VALUES ('"apple"^^xsd:string'::rdfnode),
             (NULL::rdfnode),
             ('"cherry"^^xsd:string'::rdfnode)) AS t(val);
  group_concat  
----------------
 "apple cherry"
(1 row)
```

#### [SAMPLE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#sample)

```sql
sparql.sample(value rdfnode) → rdfnode
```

Returns an arbitrary value from the aggregate group. This implements the SPARQL 1.1 `SAMPLE` aggregate function ([section 18.5.1.8](https://www.w3.org/TR/sparql11-query/#aggregates)), which is useful for selecting a representative value when you don't care which specific value is chosen.

Examples:

```sql
-- Sample from multiple integers (returns first non-NULL value)
SELECT sparql.sample(val)
FROM (VALUES ('"10"^^<http://www.w3.org/2001/XMLSchema#integer>'::rdfnode),
             ('"20"^^<http://www.w3.org/2001/XMLSchema#integer>'::rdfnode),
             ('"30"^^<http://www.w3.org/2001/XMLSchema#integer>'::rdfnode)) AS t(val);
                      sample                      
--------------------------------------------------
 "10"^^<http://www.w3.org/2001/XMLSchema#integer>
(1 row)

-- Sample with mixed types (preserves original type)
SELECT sparql.sample(val)
FROM (VALUES ('<http://example.org/resource1>'::rdfnode),
             ('"some text"'::rdfnode),
             ('"42"^^<http://www.w3.org/2001/XMLSchema#integer>'::rdfnode)) AS t(val);
             sample             
--------------------------------
 <http://example.org/resource1>
(1 row)

-- Sample with language-tagged strings (preserves language tag)
SELECT sparql.sample(val)
FROM (VALUES ('"hello"@en'::rdfnode),
             ('"bonjour"@fr'::rdfnode),
             ('"hola"@es'::rdfnode)) AS t(val);
   sample   
------------
 "hello"@en
(1 row)
```

### [Functional Forms](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#functional-forms)

#### [BOUND](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#bound)

```sql
sparql.bound(value rdfnode) → boolean
```

Returns `true` if the RDF node is *bound* to a value, and `false` otherwise. Values like `NaN` or `INF` are considered bound.

Example:
```sql
SELECT sparql.bound(NULL), sparql.bound('"NaN"^^xsd:double');
 bound | bound 
-------+-------
 f     | t
(1 row)
```

#### [COALESCE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#coalesce)

```sql
sparql.coalesce(value1 rdfnode, value2 rdfnode, ... ) → rdfnode
```

Returns the **first bound** RDF node from the argument list. If none of the inputs are bound (i.e., all are `NULL`), returns `NULL`. The behavior mimics the SPARQL 1.1 `COALESCE()` function, valuating arguments from left to right. This is useful when working with optional data where fallback values are needed.

Example:

```sql
 SELECT sparql.coalesce(NULL, NULL, '"foo"^^xsd:string');
                     coalesce                     
--------------------------------------------------
 "foo"^^<http://www.w3.org/2001/XMLSchema#string>
(1 row)
```

#### [SAMETERM](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#sameterm)

```sql
sparql.sameTerm(a rdfnode, b rdfnode) → boolean
```

Returns `true` if the two RDF nodes are exactly the same term, and `false` otherwise. This comparison is strict and includes datatype, language tag, and node type (e.g., literal vs IRI). The behavior follows SPARQL 1.1's [sameTerm functional form](https://www.w3.org/TR/sparql11-query/#func-sameTerm), which does not allow coercion or implicit casting — unlike `=` or `IS NOT DISTINCT FROM`.

Examples:

```sql
SELECT sparql.sameterm('"42"^^xsd:int', '"42"^^xsd:long');
 sameterm 
----------
 f
(1 row)

SELECT sparql.sameterm('"foo"@en', '"foo"@en');
 sameterm 
----------
 t
(1 row)

SELECT sparql.sameterm('"foo"@en', '"foo"@fr');
 sameterm 
----------
 f
(1 row)
```

> [!NOTE]  
> Use `sameterm` when you need exact RDF identity, including type and language tag. For value-based comparison with implicit coercion, use `=` instead.

### [Functions on RDF Terms](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#functions-on-rdf-terms)

#### [isIRI](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#isiri)

```sql
sparql.isiri(value rdfnode) → boolean
```
Returns `true` if the given RDF node is an IRI, and `false` otherwise. This function implements the SPARQL 1.1 [isIRI()](https://www.w3.org/TR/sparql11-query/#func-isIRI) test, which checks whether the term is an IRI—not a literal, blank node, or unbound value.

Examples:

```sql
SELECT sparql.isIRI('<https://foo.bar/>'); 
 isiri 
-------
 t
(1 row)

SELECT sparql.isIRI('"foo"^^xsd:string');
 isiri 
-------
 f
(1 row)

SELECT sparql.isIRI('_:bnode42');
 isiri 
-------
 f
(1 row)

SELECT sparql.isIRI(NULL);
 isiri 
-------
 f
(1 row)
```

> [!NOTE]  
> isURI is an alternate spelling for the isIRI function.

#### [isBLANK](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#isblank)
```sql
sparql.isblank(value rdfnode) → boolean
```

Returns `true` if the given RDF node is a blank node, and `false` otherwise. This function implements the SPARQL 1.1 [isBlank()](https://www.w3.org/TR/sparql11-query/#func-isBlank) function, which is used to detect anonymous resources (blank nodes) in RDF graphs.

```sql
SELECT sparql.isblank('_:bnode42');
 isblank 
---------
 t
(1 row)

SELECT sparql.isblank('"foo"^^xsd:string');
 isblank 
---------
 f
(1 row)
```

#### [isLITERAL](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#isliteral)

```sql
sparql.isliteral(value rdfnode) → boolean
```

Returns `true` if the given RDF node is a literal, and `false` otherwise. This function implements the SPARQL 1.1 [isLiteral()](https://www.w3.org/TR/sparql11-query/#func-isLiteral) test. It returns `false` for IRIs, blank nodes, and unbound (`NULL`) values.

Examples:

```sql
SELECT sparql.isliteral('"foo"^^xsd:string');
 isliteral 
-----------
 t
(1 row)

SELECT sparql.isliteral('"foo"^^@es');
 isliteral 
-----------
 t
(1 row)

SELECT sparql.isliteral('_:bnode42');
 isliteral 
-----------
 f
(1 row)

SELECT sparql.isliteral('<http://foo.bar>');
 isliteral 
-----------
 f
(1 row)

SELECT sparql.isliteral(NULL);
 isliteral 
-----------
 f
(1 row)
```

#### [isNUMERIC](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#isnumeric)

```sql
sparql.isnumeric(term rdfnode) → boolean
```

Returns `true` if the RDF node is a literal with a numeric datatype (such as `xsd:int`, `xsd:dateTime`, etc.), and `false` otherwise. See the SPARQL 1.1 section on [Operand Data Types](https://www.w3.org/TR/sparql11-query/#operandDataTypes) for more details.

Examples:

```sql
SELECT sparql.isnumeric('"42"^^xsd:integer');
 isnumeric 
-----------
 t
(1 row)

SELECT sparql.isnumeric('"42.73"^^xsd:decimal');
 isnumeric 
-----------
 t
(1 row)

SELECT sparql.isnumeric('"42.73"^^xsd:string');
 isnumeric 
-----------
 f
(1 row)

SELECT sparql.isnumeric(NULL);
 isnumeric 
-----------
 f
(1 row)
```

#### [STR](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#str)

```sql
sparql.str(value rdfnode) → rdfnode
```
Returns the **lexical form** (the string content) of the RDF node, as described at This implements the SPARQL 1.1 [str()](https://www.w3.org/TR/sparql11-query/#func-str) specification. For literals, this means stripping away the language tag or datatype. For IRIs, it returns the IRI string. For blank nodes, returns their label.

Examples:

```sql
SELECT sparql.str('"foo"@en');
  str  
-------
 "foo"
(1 row)

SELECT sparql.str('"foo"^^xsd:string');
  str  
-------
 "foo"
(1 row)

SELECT sparql.str('<http://foo.bar>');
       str        
------------------
 "http://foo.bar"
(1 row)
```

#### [LANG](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#lang)

```sql
sparql.str(value rdfnode) → rdfnode
```

Returns the language tag of the literal, or an empty string if none exists. Implements the SPARQL 1.1 [LANG()](https://www.w3.org/TR/sparql11-query/#func-lang) function. All other RDF nodes — including IRIs, blank nodes, and typed literals — return an empty string.

```sql
SELECT sparql.lang('"foo"@es');
 lang 
------
 es
(1 row)

SELECT sparql.lang('"foo"');
 lang 
------
 
(1 row)

SELECT sparql.lang('"foo"^^xsd:string');
 lang 
------
 
(1 row)
```

#### [DATATYPE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#datatype)

```sql
sparql.datatype(value rdfnode) → rdfnode
```

Returns the **datatype IRI** of a literal RDF node.

* For typed literals, returns the declared datatype (e.g., `xsd:int`, `xsd:dateTime`, etc.).
* For plain (untyped) literals, returns `xsd:string`.
* For language-tagged literals, returns `rdf:langString`.
* For non-literals (IRIs, blank nodes), returns `NULL`.

This behavior complies with both SPARQL 1.1 and RDF 1.1.

Examples:

```sql
SELECT sparql.datatype('"42"^^xsd:int');
                datatype                
----------------------------------------
 <http://www.w3.org/2001/XMLSchema#int>
(1 row)

SELECT sparql.datatype('"foo"');
                 datatype                  
-------------------------------------------
 <http://www.w3.org/2001/XMLSchema#string>
(1 row)

SELECT sparql.datatype('"foo"@de');
                        datatype                         
---------------------------------------------------------
 <http://www.w3.org/1999/02/22-rdf-syntax-ns#langString>
(1 row)

SELECT sparql.datatype('<http://foo.bar>');
 datatype 
----------
 NULL
(1 row)

SELECT sparql.datatype('_:bnode42');
 datatype 
----------
 NULL
(1 row)
```

> [!NOTE]  
> Keep in mind that some triplestores (like Virtuoso) return `xsd:anyURI` for IRIs, but this behaviour is not defined in SPARQL 1.1 and is not standard-compliant.

#### [IRI](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#iri)

```sql
sparql.iri(value rdfnode) → rdfnode
```

Constructs an RDF IRI from a string. Implements the SPARQL 1.1 [IRI()](https://www.w3.org/TR/sparql11-query/#func-iri) function. If the input is not a valid IRI, the function still wraps it as-is into an RDF IRI. No validation is performed.

Examples:

```sql
SELECT sparql.iri('http://foo.bar');
       iri        
------------------
 <http://foo.bar>
(1 row)
```

#### [BNODE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#bnode)

```sql
sparql.bnode(value rdfnode DEFAULT NULL) → rdfnode
```
Constructs a blank node. If a string is provided, it's used as the label. If called with no argument, generates an automatically scoped blank node identifier. Implements the SPARQL 1.1 [BNODE()](https://www.w3.org/TR/sparql11-query/#func-bnode) function.

Examples:

```sql
SELECT sparql.bnode('foo');
 bnode 
-------
 _:foo
(1 row)

SELECT sparql.bnode('"foo"^^xsd:string');
 bnode 
-------
 _:foo
(1 row)

SELECT sparql.bnode();
       bnode        
--------------------
 _:b800704569809508
(1 row)
```

#### [STRDT](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#strdt)

```sql
sparql.strdt(lexical rdfnode, datatype_iri rdfnode) → rdfnode
```

Constructs a typed literal from a lexical string and a datatype IRI. Implements the SPARQL 1.1 [STRDT()](https://www.w3.org/TR/sparql11-query/#func-strdt) function. This function can also be used to change the datatype of an existing literal by extracting its lexical form (e.g., with `sparql.str()`) and applying a new datatype.

Examples:

```sql
SELECT sparql.strdt('42','xsd:int');
                    strdt                     
----------------------------------------------
 "42"^^<http://www.w3.org/2001/XMLSchema#int>
(1 row)

SELECT sparql.strdt('2025-01-01', 'http://www.w3.org/2001/XMLSchema#date');
                         strdt                         
-------------------------------------------------------
 "2025-01-01"^^<http://www.w3.org/2001/XMLSchema#date>
(1 row)

SELECT sparql.strdt('"2025-01-01"^^xsd:string', 'http://www.w3.org/2001/XMLSchema#date');
                         strdt                         
-------------------------------------------------------
 "2025-01-01"^^<http://www.w3.org/2001/XMLSchema#date>
(1 row)
```

#### [STLANG](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#strlang)

```sql
sparql.strlang(lexical rdfnode, lang_tag rdfnode) → rdfnode
```
Constructs a language-tagged literal from a string and a language code. Implements the SPARQL 1.1 [STRLANG()](https://www.w3.org/TR/sparql11-query/#func-strlang) function. You can also use this function to re-tag an existing literal by extracting its lexical form and assigning a new language tag.

Examples:

```sql
SELECT sparql.strlang('foo','pt');
 strlang  
----------
 "foo"@pt
(1 row)

SELECT sparql.strlang('"foo"@pt','es');
 strlang  
----------
 "foo"@es
(1 row)
```

#### [UUID](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#uuid)

```sql
sparql.uuid() → rdfnode
```

Generates a fresh, globally unique IRI. Implements the SPARQL 1.1 [UUID()](https://www.w3.org/TR/sparql11-query/#func-uuid) function.

Example:

```sql
SELECT sparql.uuid();
                      uuid                       
-------------------------------------------------
 <urn:uuid:1beda602-2e35-4d13-a907-071454d2fce7>
(1 row)
```

#### [STRUUID](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#struuid)

```sql
sparql.struuid() → rdfnode
```

Generates a fresh, random UUID as a plain literal string. Implements the SPARQL 1.1 [STRUUID()](https://www.w3.org/TR/sparql11-query/#func-struuid) function. Each call returns a unique string literal containing the UUID. This is useful when you want to store or display the UUID as text rather than an IRI.

Example:

```sql
SELECT sparql.struuid();
                struuid                 
----------------------------------------
 "25a55e10-f789-4aab-bb7f-05f2ba495fd2"
(1 row)
```

### [Functions on Strings](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#functions-on-strings)

#### [STRLEN](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#strlen)

```sql
sparql.strlen(value rdfnode) → int
```

Returns the number of characters in the **lexical form** of the RDF node. Implements the SPARQL 1.1 [STRLEN()](https://www.w3.org/TR/sparql11-query/#func-strlen) function.

Examples:

```sql
SELECT sparql.strlen('"foo"');
 strlen 
--------
      3
(1 row)

SELECT sparql.strlen('"foo"@de');
 strlen 
--------
      3
(1 row)

SELECT sparql.strlen('"foo"^^xsd:string');
 strlen 
--------
      3
(1 row)

SELECT sparql.strlen('"42"^^xsd:int');
 strlen 
--------
      2
(1 row)

SELECT sparql.strlen('"🐘"@en');
 strlen 
--------
      1
(1 row)
```
> [!WARNING]  
> Some RDF triplestores implement `STRLEN` to count the number of bytes in a literal instead of the number of characters, which can lead to confusion when working with Unicode characters. For instance, in GraphDB, `STRLEN("🐘"@en)` returns 2 because it counts the bytes of the emoji, whereas in Fuseki or Virtuoso, the same function call returns 1, as they count the actual characters. Keep this behavior in mind when using `sparql.strlen`, especially with literals containing Unicode characters.

#### [SUBSTR](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#substr)

```sql
sparql.substr(value rdfnode, start int, length int DEFAULT NULL) → rdfnode
```

Extracts a substring from the lexical form of the RDF node. Implements the SPARQL 1.1 [SUBSTR()](https://www.w3.org/TR/sparql11-query/#func-substr) function.

* The start index is 1-based.
* If length is omitted, returns everything to the end of the string.
* returns `NULL` if any of the arguments is `NULL`

Examples:

```sql
SELECT sparql.substr('"foobar"', 1, 3);
 substr 
--------
 "foo"
(1 row)

SELECT sparql.substr('"foobar"', 4);
 substr 
--------
 "bar"
(1 row)
```

#### [UCASE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#ucase)

```sql
sparql.ucase(value rdfnode) → rdfnode
```

Converts the **lexical form** of the literal to uppercase. Implements the SPARQL 1.1 [UCASE()](https://www.w3.org/TR/sparql11-query/#func-ucase) function.

Examples:

```sql
SELECT sparql.ucase('"foo"');
 ucase 
-------
 "FOO"
(1 row)

SELECT sparql.ucase('"foo"@en');
  ucase   
----------
 "FOO"@en
(1 row)

SELECT sparql.ucase('"foo"^^xsd:string');
                      ucase                       
--------------------------------------------------
 "FOO"^^<http://www.w3.org/2001/XMLSchema#string>
(1 row)
```

#### [LCASE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#lcase)

```sql
sparql.lcase(value rdfnode) → rdfnode
```

Converts the **lexical form** of the literal to lowercase. Implements the SPARQL 1.1 [LCASE()](https://www.w3.org/TR/sparql11-query/#func-lcase) function.

Examples:

```sql
SELECT sparql.lcase('"FOO"');
 lcase 
-------
 "foo"
(1 row)

SELECT sparql.lcase('"FOO"@en');
  lcase   
----------
 "foo"@en
(1 row)

SELECT sparql.lcase('"FOO"^^xsd:string');
                      lcase                       
--------------------------------------------------
 "foo"^^<http://www.w3.org/2001/XMLSchema#string>
(1 row)
```

#### [STRSTARTS](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#strstarts)

```sql
sparql.strstarts(value rdfnode, prefix rdfnode) → boolean
```

Returns `true` if the **lexical form** of the RDF node starts with the given string. Implements the SPARQL 1.1 [STRSTARTS()](https://www.w3.org/TR/sparql11-query/#func-strstarts) function.

Examples:

```sql
SELECT sparql.strstarts('"foobar"^^xsd:string', '"foo"^^xsd:string');
 strstarts 
-----------
 t
(1 row)

SELECT sparql.strstarts('"foobar"@en', '"foo"^^xsd:string');
 strstarts 
-----------
 t
(1 row)
```

#### [STRENDS](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#strends)

```sql
sparql.strends(value rdfnode, suffix rdfnode) → boolean
```

Returns `true` if the **lexical form** of the RDF node ends with the given string. Implements the SPARQL 1.1 [STRENDS() ](https://www.w3.org/TR/sparql11-query/#func-strends)function.

Examples:

```sql
SELECT sparql.strends('"foobar"^^xsd:string', '"bar"^^xsd:string');
 strends 
---------
 t
(1 row)

SELECT sparql.strends('"foobar"@en', '"bar"^^xsd:string');
 strends 
---------
 t
(1 row)
```

#### [CONTAINS](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#contains)

```sql
sparql.contains(value rdfnode, substring rdfnode) → boolean
```

Returns `true` if the **lexical form** of the RDF node contains the given substring. Implements the SPARQL 1.1 [CONTAINS()](https://www.w3.org/TR/sparql11-query/#func-contains) function.

Examples:

```sql
SELECT sparql.contains('"_foobar_"^^xsd:string', '"foo"');
 contains 
----------
 t
(1 row)

SELECT sparql.contains('"_foobar_"^^xsd:string', '"foo"@en');
 contains 
----------
 t
(1 row)
```

#### [STRBEFORE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#strbefore)

```sql
sparql.strbefore(value rdfnode, delimiter rdfnode) → rdfnode
```

Returns the substring before the first occurrence of the delimiter in the **lexical form**. If the delimiter is not found, returns an empty string. Implements the SPARQL 1.1 [STRBEFORE()](https://www.w3.org/TR/sparql11-query/#func-strbefore) function.

Examples:

```sql
SELECT sparql.strbefore('"foobar"^^xsd:string','"bar"^^xsd:string');
                    strbefore                     
--------------------------------------------------
 "foo"^^<http://www.w3.org/2001/XMLSchema#string>
(1 row)

SELECT sparql.strbefore('"foobar"@en','"bar"^^xsd:string');
 strbefore 
-----------
 "foo"@en
(1 row)

SELECT sparql.strbefore('"foobar"','"bar"^^xsd:string');
 strbefore 
-----------
 "foo"
(1 row)

SELECT sparql.strbefore('"foobar"','"bar"');
 strbefore 
-----------
 "foo"
(1 row)
```

#### [STRAFTER](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#strafter)

```sql
sparql.strafter(value rdfnode, delimiter rdfnode) → rdfnode
```

Returns the substring after the first occurrence of the delimiter in the **lexical form**. If the delimiter is not found, returns an empty string. Implements the SPARQL 1.1 [STRAFTER()](https://www.w3.org/TR/sparql11-query/#func-strafter) function.

Examples:

```sql
SELECT sparql.strafter('"foobar"^^xsd:string','"foo"^^xsd:string');
                     strafter                     
--------------------------------------------------
 "bar"^^<http://www.w3.org/2001/XMLSchema#string>
(1 row)

SELECT sparql.strafter('"foobar"@en','"foo"^^xsd:string');
 strafter 
----------
 "bar"@en
(1 row)

SELECT sparql.strafter('"foobar"','"foo"^^xsd:string');
 strafter 
----------
 "bar"
(1 row)

SELECT sparql.strafter('"foobar"','"foo"');
 strafter 
----------
 "bar"
(1 row)
```

#### [ENCODE_FOR_URI](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#encode_for_uri)

```sql
sparql.encode_for_uri(value rdfnode) → rdfnode
```

Returns a URI-safe version of the lexical form by percent-encoding special characters. Implements the SPARQL 1.1 [ENCODE_FOR_URI()](https://www.w3.org/TR/sparql11-query/#func-encode) function.

```sql
SELECT sparql.encode_for_uri('"foo&bar!"');
 encode_for_uri 
----------------
 "foo%26bar%21"
(1 row)
```

#### [CONCAT](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#concat)

```sql
sparql.concat(value1 rdfnode, value2 rdfnode, ...) → rdfnode
```

Concatenates all input strings into one. Implements the SPARQL 1.1 [CONCAT()](https://www.w3.org/TR/sparql11-query/#func-concat) function.


```sql
SELECT sparql.concat('"foo"@en','"&"@en', '"bar"@en');
    concat    
--------------
 "foo&bar"@en
(1 row)

SELECT sparql.concat('"foo"^^xsd:string','"&"^^xsd:string', '"bar"^^xsd:string');
                        concat                        
------------------------------------------------------
 "foo&bar"^^<http://www.w3.org/2001/XMLSchema#string>
(1 row)

SELECT sparql.concat('"foo"','"&"', '"bar"');
  concat   
-----------
 "foo&bar"
(1 row)
```

#### [LANGMATCHES](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#langmatches)

```sql
sparql.langmatches(lang_tag rdfnode, pattern rdfnode) → boolean
```

Checks whether a language tag matches a language pattern (e.g., `en` matches `en-US`).
Implements the SPARQL 1.1 [LANGMATCHES()](https://www.w3.org/TR/sparql11-query/#func-langMatches) function.

Example:

```sql
SELECT sparql.langmatches('en', 'en');
 langmatches 
-------------
 t
(1 row)

SELECT sparql.langmatches('en-US', 'en');
 langmatches 
-------------
 t
(1 row)

SELECT sparql.langmatches('en', 'de');
 langmatches 
-------------
 f
(1 row)

SELECT sparql.langmatches('en', '*');
 langmatches 
-------------
 t
(1 row)
```

#### [REPLACE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#replace)

```sql
sparql.replace(value rdfnode, pattern rdfnode, replacement rdfnode, flags rdfnode DEFAULT '') → rdfnode

```

Replaces parts of the **lexical form** using a regular expression. Implements the SPARQL 1.1 [REPLACE()](https://www.w3.org/TR/sparql11-query/#func-replace) function.

* Supports `i`, `m`, and `g` flags.

```sql
SELECT sparql.replace('"foo bar foo"', 'foo', 'baz', 'g');
    replace    
---------------
 "baz bar baz"
(1 row)
```
### [Functions on Numerics](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#functions-on-numerics)

#### [ABS](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#abs)

```sql
sparql.abs(value rdfnode) → numeric
```

Returns the absolute value of a numeric literal. Implements the SPARQL 1.1 [ABS()](https://www.w3.org/TR/sparql11-query/#func-abs) function.

Examples:

```sql
SELECT sparql.abs('"-42"^^xsd:int');
                     abs                      
----------------------------------------------
 "42"^^<http://www.w3.org/2001/XMLSchema#int>
(1 row)

SELECT sparql.abs('"3.14"^^xsd:decimal');
                        abs                         
----------------------------------------------------
 "3.14"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)
```

#### [ROUND](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#round)

```sql
sparql.round(value rdfnode) → numeric
```

Rounds the numeric literal to the nearest integer. Implements the SPARQL 1.1 [ROUND()](https://www.w3.org/TR/sparql11-query/#func-round) function.

Examples:

```sql
SELECT sparql.round('"2.5"^^xsd:decimal');
                      round                      
-------------------------------------------------
 "3"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)

SELECT sparql.round('"-2.5"^^xsd:float');
                     round                      
------------------------------------------------
 "-2"^^<http://www.w3.org/2001/XMLSchema#float>
(1 row)
```

#### [CEIL](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#ceil)

```sql
sparql.ceil(value rdfnode) → numeric
```
Returns the smallest integer greater than or equal to the numeric value. Implements the SPARQL 1.1 [CEIL()](https://www.w3.org/TR/sparql11-query/#func-ceil) function.

Examples:

```sql
SELECT sparql.ceil('"3.14"^^xsd:decimal');
                      ceil                       
-------------------------------------------------
 "4"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)

SELECT sparql.ceil('"-2.1"^^xsd:float');
                      ceil                      
------------------------------------------------
 "-2"^^<http://www.w3.org/2001/XMLSchema#float>
(1 row)
```

#### [FLOOR](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#floor)

```sql
sparql.floor(value rdfnode) → numeric
```

Returns the greatest integer less than or equal to the numeric value. Implements the SPARQL 1.1 [FLOOR()](https://www.w3.org/TR/sparql11-query/#func-floor) function.

Examples:

```sql
SELECT sparql.floor('"3.9"^^xsd:decimal');
                      floor                      
-------------------------------------------------
 "3"^^<http://www.w3.org/2001/XMLSchema#decimal>
(1 row)

SELECT sparql.floor('"-2.1"^^xsd:float');
                     floor                      
------------------------------------------------
 "-3"^^<http://www.w3.org/2001/XMLSchema#float>
(1 row)
```

#### [RAND](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#rand)

```sql
sparql.rand() → rdfnode
```

Returns a random floating-point number between 0.0 and 1.0. Implements the SPARQL 1.1 [RAND()](https://www.w3.org/TR/sparql11-query/#idp2130040) function.

Examples:

```sql
SELECT sparql.rand();
                               rand                               
------------------------------------------------------------------
 "0.14079881274421657"^^<http://www.w3.org/2001/XMLSchema#double>
(1 row)
```

### [Functions on Dates and Times](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#functions-on-dates-and-times)

#### [YEAR](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#year)

```sql
sparql.year(value rdfnode) → int
```

Returns the year component of an `xsd:dateTime` or `xsd:date` literal. Implements the SPARQL 1.1 [YEAR()](https://www.w3.org/TR/sparql11-query/#func-year) function.

Example:

```sql
SELECT sparql.year('"2025-05-17T14:00:00Z"^^xsd:dateTime');
 year 
------
 2025
```

#### [MONTH](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#month)

```sql
sparql.month(value rdfnode) → int
```
Returns the month component (1–12) from a datetime or date. Implements the SPARQL 1.1 [MONTH()](https://www.w3.org/TR/sparql11-query/#func-month) function.

Example:

```sql
SELECT sparql.month('"2025-05-17T14:00:00Z"^^xsd:dateTime');
 month 
-------
     5
(1 row)
```

#### [DAY](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#day)

```sql
sparql.day(value rdfnode) → int
```

Returns the day of the month from a date or datetime literal. Implements the SPARQL 1.1 [DAY()](https://www.w3.org/TR/sparql11-query/#func-day) function.

Example:

```sql
SELECT sparql.day('"2025-05-17T14:00:00Z"^^xsd:dateTime');
 day 
-----
  17
(1 row)
```

#### [HOURS](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#hours)

```sql
sparql.hours(value rdfnode) → int
```

Extracts the hour (0–23) from a datetime literal. Implements the SPARQL 1.1 [HOURS()](https://www.w3.org/TR/sparql11-query/#func-hours) function.

Example:

```sql
SELECT sparql.hours('"2025-05-17T14:00:00Z"^^xsd:dateTime');
 hours 
-------
    14
(1 row)
```

#### [MINUTES](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#minutes)

```sql
sparql.minutes(value rdfnode) → int
```

Returns the minute component (0–59) of a datetime literal. Implements the SPARQL 1.1 [MINUTES()](https://www.w3.org/TR/sparql11-query/#func-minutes) function.

Example: 

```sql
SELECT sparql.minutes('"2025-05-17T14:42:37Z"^^xsd:dateTime');
 minutes 
---------
      42
(1 row)
```

#### [SECONDS](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#seconds)

```sql
sparql.seconds(value rdfnode) → int
```

Returns the seconds (including fractions) from a datetime literal. Implements the SPARQL 1.1 [SECONDS()](https://www.w3.org/TR/sparql11-query/#func-seconds) function.

Example:

```sql
SELECT sparql.seconds('"2025-05-17T14:42:37Z"^^xsd:dateTime');
 seconds 
---------
      37
(1 row)
```

#### [TIMEZONE](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#timezone)

```sql
sparql.timezone(datetime rdfnode) → rdfnode
```

Returns the timezone offset as a duration literal (e.g., "PT2H"), or NULL if none. Implements the SPARQL 1.1 [TIMEZONE()](https://www.w3.org/TR/sparql11-query/#func-timezone) function.

Example:

```sql
SELECT sparql.timezone('"2025-05-17T10:00:00+02:00"^^xsd:dateTime');
                          timezone                          
------------------------------------------------------------
 "PT2H"^^<http://www.w3.org/2001/XMLSchema#dayTimeDuration>
(1 row)
```

#### [TZ](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#tz)

```sql
sparql.tz(datetime rdfnode) → rdfnode
```

Returns the timezone offset as a string (e.g., `+02:00` or `Z`). Implements the SPARQL 1.1 [TZ()](https://www.w3.org/TR/sparql11-query/#func-tz) function.

Examples:

```sql
SELECT sparql.tz('"2025-05-17T10:00:00+02:00"^^xsd:dateTime');
    tz    
----------
 "+02:00"
(1 row)

SELECT sparql.tz('"2025-05-17T08:00:00Z"^^xsd:dateTime');
 tz  
-----
 "Z"
(1 row)
```

### [Hash Functions](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#hash-functions)

#### [MD5](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#md5)

```sql
sparql.md5(value rdfnode) → rdfnode
```

Returns the MD5 hash of the lexical form of the input RDF literal, encoded as a lowercase hexadecimal string. Implements the SPARQL 1.1 [MD5()](https://www.w3.org/TR/sparql11-query/#func-md5) function. The result is returned as a plain literal (xsd:string).

Examples:

```sql
SELECT sparql.md5('"foo"');
                md5                 
------------------------------------
 "acbd18db4cc2f85cedef654fccc4a4d8"
(1 row)

SELECT sparql.md5('42'::rdfnode);
                md5                 
------------------------------------
 "a1d0c6e83f027327d8461063f4ac58a6"
(1 row)
```

### [Custom Functions](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#custom-functions)

#### [LEX](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#lex)

```sql
sparql.lex(value rdfnode) → rdfnode
```

Extracts the lexical value of a given `rdfnode`. This is a convenience function that is not part of the SPARQL 1.1 standard.

Examples:

```sql
SELECT sparql.lex('"foo"^^xsd:string');
 lex 
-----
 foo
(1 row)

SELECT sparql.lex('"foo"@es');
 lex 
-----
 foo
(1 row)
```

## [SPARQL describe](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#sparql-describe)
```sql
sparql.describe(server text, query text, raw_literal boolean, base_uri text) → triple
```
**Description**

The `sparql.describe` function executes a SPARQL `DESCRIBE` query against a specified RDF triplestore `SERVER`. It retrieves RDF triples describing a resource (or resources) identified by the query and returns them as a table with three columns: subject, predicate, and object. This function is useful for exploring RDF data by fetching detailed descriptions of resources from a triplestore.

**Parameters**

`server` **(required)**: The name of the foreign server (defined via `CREATE SERVER`) that specifies the SPARQL endpoint to query. This must correspond to an existing `rdf_fdw` server configuration. Cannot be empty or `NULL`.

`describe_query` **(required)**: A valid SPARQL `DESCRIBE` query string (e.g., `DESCRIBE <http://example.org/resource>`). Cannot be empty or `NULL`.

`raw_literal`: Controls how literal values in the object column are formatted (default `true`):
* **true**: Preserves the full RDF literal syntax, including datatype (e.g., `"123"^^<http://www.w3.org/2001/XMLSchema#integer>`) or language tags (e.g., `"hello"@en`).
* **false**: Strips datatype and language tags, returning only the literal value (e.g., `"123"` or `"hello"`).

`base_uri`: The base URI used to resolve relative URIs in the `RDF/XML` response from the triplestore. If empty, defaults to "http://rdf_fdw.postgresql.org/". Useful for ensuring correct URI resolution in the parsed triples.


**Return Value**

Returns a table with the following `rdfnode` columns:
* `subject`: The subject of each RDF triple, typically a URI or blank node identifier.
* `predicate`: The predicate (*property*) of each RDF triple, always a URI.
* `object`: The object of each RDF triple, which may be a URI, blank node, or literal value.

**Usage Example**

```sql
CREATE SERVER wikidata
FOREIGN DATA WRAPPER rdf_fdw 
OPTIONS (endpoint 'https://query.wikidata.org/sparql');

SELECT subject, predicate, object
FROM rdf_fdw_describe('wikidata', 'DESCRIBE <http://www.wikidata.org/entity/Q61308849>', true);

INFO:  SPARQL query sent to 'https://query.wikidata.org/sparql':

DESCRIBE <http://www.wikidata.org/entity/Q61308849>


                 subject                  |                 predicate                  |                               object
------------------------------------------+--------------------------------------------+------------------------------------------------------------------------------
 http://www.wikidata.org/entity/Q61308849 | http://www.wikidata.org/prop/direct/P3999  | "2015-01-01T00:00:00Z"^^<http://www.w3.org/2001/XMLSchema#dateTime>
 http://www.wikidata.org/entity/Q61308849 | http://schema.org/dateModified             | "2024-05-01T21:36:41Z"^^<http://www.w3.org/2001/XMLSchema#dateTime>
 http://www.wikidata.org/entity/Q61308849 | http://schema.org/version                  | "2142303130"^^<http://www.w3.org/2001/XMLSchema#integer>
 http://www.wikidata.org/entity/Q61308849 | http://www.wikidata.org/prop/direct/P127   | http://www.wikidata.org/entity/Q349450
...
 http://www.wikidata.org/entity/Q61308849 | http://www.wikidata.org/prop/direct/P625   | "Point(-133.03 69.43)"^^<http://www.opengis.net/ont/geosparql#wktLiteral>
(37 rows)
```

## [Import data into QGIS](#import-data-into-qgis)

The `rdf_fdw` can also be used as a bridge between GIS (Geographic Information Systems) and RDF Triplestores. This example demonstrates how to retrieve geographic coordinates of all German public universities from DBpedia, create WKT (Well Known Text) literals, and import the data into [QGIS](https://qgis.org/) to visualize it on a map.

> [!NOTE]  
> This example requires the extension PostGIS.

```sql
CREATE SERVER dbpedia
FOREIGN DATA WRAPPER rdf_fdw 
OPTIONS (endpoint 'https://dbpedia.org/sparql');

CREATE FOREIGN TABLE german_public_universities (
  id text                   OPTIONS (variable '?uri', nodetype 'iri'),
  name text                 OPTIONS (variable '?name',nodetype 'literal'),
  lon numeric               OPTIONS (variable '?lon', nodetype 'literal'),
  lat numeric               OPTIONS (variable '?lat', nodetype 'literal'),
  geom geometry(point,4326) OPTIONS (variable '?wkt', nodetype 'literal',
                                    expression 'CONCAT("POINT(",?lon," ",?lat,")") AS ?wkt')
) SERVER dbpedia OPTIONS (
  sparql '
    PREFIX geo: <http://www.w3.org/2003/01/geo/wgs84_pos#>
    PREFIX dbp: <http://dbpedia.org/property/>
    PREFIX dbo: <http://dbpedia.org/ontology/>
    PREFIX dbr:  <http://dbpedia.org/resource/>
    SELECT ?uri ?name ?lon ?lat
    WHERE {
      ?uri dbo:type dbr:Public_university ;
        dbp:name ?name;
        geo:lat ?lat; 
        geo:long ?lon; 
        dbp:country dbr:Germany
      }
  ');
```
Now that we have our `FOREIGN TABLE` in place, we just need to create a [New PostGIS Connection in QGIS](https://docs.qgis.org/3.34/en/docs/user_manual/managing_data_source/opening_data.html#creating-a-stored-connection) and go to **Database > DB Manager ...**, select the table we just created and query the data using SQL:

```sql
SELECT id, name, geom
FROM german_public_universities
```
![unis](examples/img/qgis-query.png?raw=true)

Finally give the layer a name, select the geometry column and press **Load**.

![unis](examples/img/qgis-map.png?raw=true)
### [Publish FOREIGN TABLE as WFS layer in GeoServer](https://github.com/jimjonesbr/rdf_fdw/blob/master/README.md#publish-foreign-table-as-wfs-layer-in-geoserver)

Just like with an ordinary `TABLE` in PostgreSQL, it is possible to create and publish `FOREIGN TABLES` as WFS layers in GeoServer. 

First create the `FOREIGN TABLE`:

```sql
CREATE SERVER wikidata
FOREIGN DATA WRAPPER rdf_fdw 
OPTIONS (endpoint 'https://query.wikidata.org/sparql');

CREATE FOREIGN TABLE museums_brittany (
  id text                   OPTIONS (variable '?villeId', nodetype 'iri'),
  label text                OPTIONS (variable '?museumLabel',nodetype 'literal'),
  ville text                OPTIONS (variable '?villeIdLabel', nodetype 'literal'),
  geom geometry(point,4326) OPTIONS (variable '?coord', nodetype 'literal')
) SERVER wikidata OPTIONS (
  sparql '
    SELECT DISTINCT ?museumLabel ?villeId ?villeIdLabel ?coord
    WHERE
    {
      ?museum wdt:P539 ?museofile. # french museofile Id
      ?museum wdt:P131* wd:Q12130. # in Brittany
      ?museum wdt:P131 ?villeId.   # city of the museum
      ?museum wdt:P625 ?coord .    # wkt literal      
      SERVICE wikibase:label { bd:serviceParam wikibase:language "fr". } # french label
    }
  ');
```
Then set up the [Workspace](https://docs.geoserver.org/latest/en/user/data/webadmin/workspaces.html) and [Store](https://docs.geoserver.org/latest/en/user/data/webadmin/stores.html), go to  **Layers -> Add a new layer**, select the proper workspace and go to **Configure new SQL view...** to create a layer create a layer with a native **SQL statement**:

```sql
SELECT id, label, ville, geom
FROM museums_brittany
```

![geoserver](examples/img/geoserver-layer.png?raw=true)

After that set the geometry column and identifier, and hit **Save**. Finally, fill in the remaining layer attributes, such as Style, Bounding Boxes and Spatial Reference System, and click **Save** - see this [instructions](https://docs.geoserver.org/latest/en/user/data/webadmin/layers.html) for more details. After that you'll be able to reach your layer from a standard OGC WFS client, e.g. using [QGIS](https://docs.qgis.org/3.34/en/docs/server_manual/services/wfs.html).

![geoserver-wfs](examples/img/geoserver-wfs-client.png?raw=true)

![geoserver-wfs-map](examples/img/geoserver-wfs-map.png?raw=true)

## [For testers and developers](#for-testers-and-developers)

Think you're cool enough? Try compiling the latest commits from source!

Dockerfile


```dockerfile
FROM postgres:18

RUN apt-get update && \
    apt-get install -y git make gcc postgresql-server-dev-18 libxml2-dev libcurl4-gnutls-dev pkg-config

WORKDIR /

RUN git clone https://github.com/jimjonesbr/rdf_fdw.git && \
    cd rdf_fdw && \
    make -j && \
    make install
```
Deployment

```bash
 $ docker build -t rdf_fdw_image .
 $ docker run --name my_container -e POSTGRES_HOST_AUTH_METHOD=trust rdf_fdw_image
 $ docker exec -u postgres my_container psql -d mydatabase -c "CREATE EXTENSION rdf_fdw;"
```

If you've found a bug or have general comments, do not hesitate to open an issue. Any feedback is much appreciated!