SPARQL Query Azure Function

This Azure Function executes federated SPARQL queries over one or more remote RDF/TTL sources using Comunica's file query engine with automatic multi-source optimization.

Function Endpoints

• POST /api/FedQuery: Execute a SPARQL query with specified RDF sources.
• GET /api/FedQuery: Displays Azure Function documentation.

How to Use

You can use CURL, Postman, or make a POST request programmatically to call this function.

1. Using curl

curl -X POST "<AZURE_FUNCTION_URL>/api/FedQuery" \
     -H "Content-Type: application/json" \
     -d '{
           "sparql": "SELECT * WHERE { ?s ?p ?o } LIMIT 100",
           "sources": [
               "https://solidserver.bovi-analytics.com/decide_lab1/Horizontal/HorizontalLab1.ttl",
               "https://solidserver.bovi-analytics.com/decide_lab2/Horizontal/HorizontalLab2.ttl"
           ]
         }'

2. Using Postman

1. Set the HTTP method to POST.
2. Enter the URL for the Azure Function endpoint: <AZURE_FUNCTION_URL>/api/FedQuery.
3. Set the headers: Content-Type = application/json.
4. In the body, select "raw" and enter the JSON query:

{
    "sparql": "SELECT * WHERE { ?s ?p ?o } LIMIT 100",
    "sources": [
        "https://solidserver.bovi-analytics.com/decide_lab1/Horizontal/HorizontalLab1.ttl",
        "https://solidserver.bovi-analytics.com/decide_lab2/Horizontal/HorizontalLab2.ttl"
    ]
}

3. Programmatically

Node.js Example

const query = {
    sparql: "SELECT * WHERE { ?s ?p ?o } LIMIT 100",
    sources: [
        "https://solidserver.bovi-analytics.com/decide_lab1/Horizontal/HorizontalLab1.ttl",
        "https://solidserver.bovi-analytics.com/decide_lab2/Horizontal/HorizontalLab2.ttl"
    ]
};

fetch('<AZURE_FUNCTION_URL>/api/FedQuery', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify(query)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));

Python Example

import requests

url = "<AZURE_FUNCTION_URL>/api/FedQuery"
query = {
    "sparql": "SELECT * WHERE { ?s ?p ?o } LIMIT 100",
    "sources": [
        "https://solidserver.bovi-analytics.com/decide_lab1/Horizontal/HorizontalLab1.ttl",
        "https://solidserver.bovi-analytics.com/decide_lab2/Horizontal/HorizontalLab2.ttl"
    ]
}

response = requests.post(url, json=query, headers={'Content-Type': 'application/json'})
print(response.json())

Request Body

The POST request requires a JSON body with the following structure:

{
    "sparql": "SELECT * WHERE { ?s ?p ?o }",
    "sources": [
        "https://solidserver.bovi-analytics.com/decide_lab1/Horizontal/HorizontalLab1.ttl",
        "https://solidserver.bovi-analytics.com/decide_lab2/Horizontal/HorizontalLab2.ttl"
    ],
    "limit": 5000,
    "timeout": 180000
}

Field	Required	Default	Description
sparql	Yes	—	SPARQL SELECT query string
sources	Yes	—	Array of remote TTL file URLs
limit	No	5000	Max rows to return (capped at 10,000)
timeout	No	300000	Timeout in ms (capped at 300,000)

Response Format

{
    "data": [
        { "s": "http://example.org/subject", "p": "http://example.org/predicate", "o": "value" }
    ],
    "count": 100,
    "hasMore": false,
    "timedOut": false,
    "timeMs": 22500,
    "queryTimeMs": 22500
}

Field	Description
data	Array of result objects (variable name → value)
count	Number of rows returned
hasMore	Whether more results exist beyond the limit
timedOut	Whether the query was aborted due to timeout
timeMs	Total execution time in milliseconds
queryTimeMs	Time spent fetching sources and executing the query

Responses

• 200 OK: Query results in JSON format.
• 400 Bad Request: Invalid JSON or missing fields.
• 500 Internal Server Error: An internal error occurred.

Performance

Benchmarked against Solid-hosted TTL sources (5–12 sources, up to 12 pods):

Experiment	Mean time
Q1 simple — 5 cattle pods	~22 s
Q2 UNION — 12 vertical species pods	~23 s
Q2 UNION — 6 horizontal pods	~23 s

Architecture

Component	Description
Engine	@comunica/query-sparql-file v5.2.0
Strategy	Comunica fetches and parses TTL sources internally; the group-file-sources optimizer automatically merges multiple file sources into a single in-memory store before querying
Singleton	Engine instance is reused across requests to avoid startup overhead
Timeout	AbortController with custom fetch ensures HTTP fetches are cancelled on timeout

Credits

This function is built on Comunica, a highly modular and flexible meta query engine for the Web. Performance improvements in v5.2.0 are made possible by PR #1681.

Taelman, R., Van Herwegen, J., Vander Sande, M., & Verborgh, R. (2018).
Comunica: a Modular SPARQL Query Engine for the Web.
In Proceedings of the 17th International Semantic Web Conference (ISWC).
https://doi.org/10.1007/978-3-030-00671-6_15

Notes

• Replace <AZURE_FUNCTION_URL> with the actual URL of your Azure Function.
• Ensure that the RDF sources you provide are accessible and properly formatted.
• The function processes SPARQL queries and returns results in JSON format.