wifi-densepose/vendor/ruvector/docs/research/sparql/EXAMPLES.md

SPARQL Query Examples for RuVector-Postgres

Project: RuVector-Postgres SPARQL Extension Date: December 2025

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Table of Contents

1. Basic Queries
2. Filtering and Constraints
3. Optional Patterns
4. Property Paths
5. Aggregation
6. Update Operations
7. Named Graphs
8. Hybrid Queries (SPARQL + Vector)
9. Advanced Patterns

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Basic Queries

Example 1: Simple SELECT

Find all people and their names:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?person ?name
WHERE {
  ?person foaf:name ?name .
}

Example 2: Multiple Patterns

Find people with both name and email:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?person ?name ?email
WHERE {
  ?person foaf:name ?name .
  ?person foaf:email ?email .
}

Example 3: ASK Query

Check if a specific person exists:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

ASK {
  ?person foaf:name "Alice" .
}

Example 4: CONSTRUCT Query

Build a new graph with simplified structure:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX ex: <http://example.org/>

CONSTRUCT {
  ?person ex:hasName ?name .
  ?person ex:contactEmail ?email .
}
WHERE {
  ?person foaf:name ?name .
  ?person foaf:email ?email .
}

Example 5: DESCRIBE Query

Get all information about a resource:

DESCRIBE <http://example.org/person/alice>

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Filtering and Constraints

Example 6: Numeric Comparison

Find people aged 18 or older:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?age
WHERE {
  ?person foaf:name ?name .
  ?person foaf:age ?age .
  FILTER(?age >= 18)
}

Example 7: String Matching

Find people with email addresses at example.com:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?email
WHERE {
  ?person foaf:name ?name .
  ?person foaf:email ?email .
  FILTER(CONTAINS(?email, "@example.com"))
}

Example 8: Regex Pattern Matching

Find people whose names start with 'A':

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name
WHERE {
  ?person foaf:name ?name .
  FILTER(REGEX(?name, "^A", "i"))
}

Example 9: Multiple Conditions

Find adults between 18 and 65:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?age
WHERE {
  ?person foaf:name ?name .
  ?person foaf:age ?age .
  FILTER(?age >= 18 && ?age < 65)
}

Example 10: Logical OR

Find people with either phone or email:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?contact
WHERE {
  ?person foaf:name ?name .
  {
    ?person foaf:phone ?contact .
  }
  UNION
  {
    ?person foaf:email ?contact .
  }
}

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Optional Patterns

Example 11: Simple OPTIONAL

Find all people, including email if available:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?email
WHERE {
  ?person foaf:name ?name .
  OPTIONAL { ?person foaf:email ?email }
}

Example 12: Multiple OPTIONAL

Find people with optional contact information:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?email ?phone ?homepage
WHERE {
  ?person foaf:name ?name .
  OPTIONAL { ?person foaf:email ?email }
  OPTIONAL { ?person foaf:phone ?phone }
  OPTIONAL { ?person foaf:homepage ?homepage }
}

Example 13: OPTIONAL with FILTER

Find people with optional business emails:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?businessEmail
WHERE {
  ?person foaf:name ?name .
  OPTIONAL {
    ?person foaf:email ?businessEmail .
    FILTER(!CONTAINS(?businessEmail, "@gmail.com"))
  }
}

Example 14: Nested OPTIONAL

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?friendName ?friendEmail
WHERE {
  ?person foaf:name ?name .
  OPTIONAL {
    ?person foaf:knows ?friend .
    ?friend foaf:name ?friendName .
    OPTIONAL { ?friend foaf:email ?friendEmail }
  }
}

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Property Paths

Example 15: Transitive Closure

Find all people someone knows (directly or indirectly):

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?friendName
WHERE {
  <http://example.org/alice> foaf:name ?name .
  <http://example.org/alice> foaf:knows+ ?friend .
  ?friend foaf:name ?friendName .
}

Example 16: Path Sequence

Find grandchildren:

PREFIX ex: <http://example.org/>

SELECT ?person ?grandchild
WHERE {
  ?person ex:hasChild / ex:hasChild ?grandchild .
}

Example 17: Alternative Paths

Find either name or label:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT ?person ?label
WHERE {
  ?person (foaf:name | rdfs:label) ?label .
}

Example 18: Inverse Path

Find all children of a person:

PREFIX ex: <http://example.org/>

SELECT ?child
WHERE {
  <http://example.org/alice> ^ex:hasChild ?child .
}

Example 19: Zero or More

Find all connected people (including self):

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?connected
WHERE {
  <http://example.org/alice> foaf:knows* ?connected .
}

Example 20: Negated Property

Find relationships that aren't "knows":

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?x ?y
WHERE {
  ?x !foaf:knows ?y .
}

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Aggregation

Example 21: COUNT

Count employees per company:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?company (COUNT(?employee) AS ?employeeCount)
WHERE {
  ?employee foaf:workplaceHomepage ?company .
}
GROUP BY ?company

Example 22: AVG

Average salary by department:

PREFIX ex: <http://example.org/>

SELECT ?dept (AVG(?salary) AS ?avgSalary)
WHERE {
  ?employee ex:department ?dept .
  ?employee ex:salary ?salary .
}
GROUP BY ?dept

Example 23: MIN and MAX

Salary range by department:

PREFIX ex: <http://example.org/>

SELECT ?dept (MIN(?salary) AS ?minSalary) (MAX(?salary) AS ?maxSalary)
WHERE {
  ?employee ex:department ?dept .
  ?employee ex:salary ?salary .
}
GROUP BY ?dept

Example 24: GROUP_CONCAT

Concatenate skills per person:

PREFIX ex: <http://example.org/>

SELECT ?person (GROUP_CONCAT(?skill; SEPARATOR=", ") AS ?skills)
WHERE {
  ?person ex:hasSkill ?skill .
}
GROUP BY ?person

Example 25: HAVING

Find departments with more than 10 employees:

PREFIX ex: <http://example.org/>

SELECT ?dept (COUNT(?employee) AS ?count)
WHERE {
  ?employee ex:department ?dept .
}
GROUP BY ?dept
HAVING (COUNT(?employee) > 10)

Example 26: Multiple Aggregates

Comprehensive statistics per department:

PREFIX ex: <http://example.org/>

SELECT ?dept
       (COUNT(?employee) AS ?empCount)
       (AVG(?salary) AS ?avgSalary)
       (MIN(?salary) AS ?minSalary)
       (MAX(?salary) AS ?maxSalary)
       (SUM(?salary) AS ?totalSalary)
WHERE {
  ?employee ex:department ?dept .
  ?employee ex:salary ?salary .
}
GROUP BY ?dept
ORDER BY DESC(?avgSalary)

---

Update Operations

Example 27: INSERT DATA

Add new triples:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

INSERT DATA {
  <http://example.org/alice> foaf:name "Alice" .
  <http://example.org/alice> foaf:age 30 .
  <http://example.org/alice> foaf:email "alice@example.com" .
}

Example 28: DELETE DATA

Remove specific triples:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

DELETE DATA {
  <http://example.org/alice> foaf:email "old@example.com" .
}

Example 29: DELETE/INSERT

Update based on pattern:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

DELETE { ?person foaf:age ?oldAge }
INSERT { ?person foaf:age ?newAge }
WHERE {
  ?person foaf:name "Alice" .
  ?person foaf:age ?oldAge .
  BIND(?oldAge + 1 AS ?newAge)
}

Example 30: DELETE WHERE

Remove triples matching pattern:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

DELETE WHERE {
  ?person foaf:email ?email .
  FILTER(CONTAINS(?email, "@oldcompany.com"))
}

Example 31: LOAD

Load RDF data from URL:

LOAD <http://example.org/data.ttl> INTO GRAPH <http://example.org/graph1>

Example 32: CLEAR

Clear all triples from a graph:

CLEAR GRAPH <http://example.org/graph1>

Example 33: CREATE and DROP

Manage graphs:

CREATE GRAPH <http://example.org/newgraph>

-- later...

DROP GRAPH <http://example.org/oldgraph>

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Named Graphs

Example 34: Query Specific Graph

Query data from a specific named graph:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name
FROM <http://example.org/graph1>
WHERE {
  ?person foaf:name ?name .
}

Example 35: GRAPH Keyword

Query with graph variable:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?graph
WHERE {
  GRAPH ?graph {
    ?person foaf:name ?name .
  }
}

Example 36: Query Multiple Graphs

Query data from multiple graphs:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name
FROM <http://example.org/graph1>
FROM <http://example.org/graph2>
WHERE {
  ?person foaf:name ?name .
}

Example 37: Insert into Named Graph

Add triples to specific graph:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

INSERT DATA {
  GRAPH <http://example.org/graph1> {
    <http://example.org/bob> foaf:name "Bob" .
  }
}

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Hybrid Queries (SPARQL + Vector)

Example 38: Semantic Search with Knowledge Graph

Find people similar to a query embedding:

-- Using RuVector-Postgres hybrid function
SELECT * FROM ruvector_sparql_vector_search(
  'SELECT ?person ?name ?bio
   WHERE {
     ?person foaf:name ?name .
     ?person ex:bio ?bio .
     ?person ex:embedding ?embedding .
   }',
  'http://example.org/embedding',
  '[0.15, 0.25, 0.35, ...]'::ruvector,  -- query vector
  0.8,  -- similarity threshold
  10    -- top K results
);

Example 39: Combine Graph Traversal and Vector Similarity

Find friends of friends who are similar:

WITH friends_of_friends AS (
  SELECT DISTINCT o.subject AS person
  FROM ruvector_rdf_triples t1
  JOIN ruvector_rdf_triples t2 ON t1.object = t2.subject
  WHERE t1.subject = 'http://example.org/alice'
    AND t1.predicate = 'http://xmlns.com/foaf/0.1/knows'
    AND t2.predicate = 'http://xmlns.com/foaf/0.1/knows'
)
SELECT
  f.person,
  r.object AS name,
  e.embedding <=> $1::ruvector AS similarity
FROM friends_of_friends f
JOIN ruvector_rdf_triples r
  ON f.person = r.subject
  AND r.predicate = 'http://xmlns.com/foaf/0.1/name'
JOIN person_embeddings e
  ON f.person = e.person_iri
WHERE e.embedding <=> $1::ruvector < 0.5
ORDER BY similarity
LIMIT 10;

Example 40: Hybrid Ranking

Combine SPARQL pattern matching with vector similarity:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX ex: <http://example.org/>

SELECT ?person ?name ?skills
       (ex:vectorSimilarity(?embedding, ?queryVector) AS ?similarity)
WHERE {
  ?person foaf:name ?name .
  ?person ex:skills ?skills .
  ?person ex:embedding ?embedding .

  # Pattern constraints
  FILTER(CONTAINS(?skills, "Python"))
  FILTER(ex:vectorSimilarity(?embedding, ?queryVector) > 0.7)
}
ORDER BY DESC(?similarity)
LIMIT 20

Example 41: Multi-Modal Search

Search using both text and semantic embeddings:

-- Combine full-text search with vector similarity
SELECT
  t.subject AS document,
  t_title.object AS title,
  ts_rank(to_tsvector('english', t_content.object), plainto_tsquery('machine learning')) AS text_score,
  e.embedding <=> $1::ruvector AS vector_score,
  0.4 * ts_rank(to_tsvector('english', t_content.object), plainto_tsquery('machine learning'))
    + 0.6 * (1.0 - (e.embedding <=> $1::ruvector)) AS combined_score
FROM ruvector_rdf_triples t
JOIN ruvector_rdf_triples t_title
  ON t.subject = t_title.subject
  AND t_title.predicate = 'http://purl.org/dc/terms/title'
JOIN ruvector_rdf_triples t_content
  ON t.subject = t_content.subject
  AND t_content.predicate = 'http://purl.org/dc/terms/content'
JOIN document_embeddings e
  ON t.subject = e.doc_iri
WHERE to_tsvector('english', t_content.object) @@ plainto_tsquery('machine learning')
  AND e.embedding <=> $1::ruvector < 0.8
ORDER BY combined_score DESC
LIMIT 50;

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Advanced Patterns

Example 42: Subquery

Find companies with above-average salaries:

PREFIX ex: <http://example.org/>

SELECT ?company ?avgSalary
WHERE {
  {
    SELECT ?company (AVG(?salary) AS ?avgSalary)
    WHERE {
      ?employee ex:worksAt ?company .
      ?employee ex:salary ?salary .
    }
    GROUP BY ?company
  }

  {
    SELECT (AVG(?salary) AS ?overallAvg)
    WHERE {
      ?employee ex:salary ?salary .
    }
  }

  FILTER(?avgSalary > ?overallAvg)
}
ORDER BY DESC(?avgSalary)

Example 43: VALUES

Query specific entities:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?person ?name ?age
WHERE {
  VALUES ?person {
    <http://example.org/alice>
    <http://example.org/bob>
    <http://example.org/charlie>
  }
  ?person foaf:name ?name .
  OPTIONAL { ?person foaf:age ?age }
}

Example 44: BIND

Compute new values:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?person ?fullName ?birthYear
WHERE {
  ?person foaf:givenName ?first .
  ?person foaf:familyName ?last .
  ?person foaf:age ?age .

  BIND(CONCAT(?first, " ", ?last) AS ?fullName)
  BIND(year(now()) - ?age AS ?birthYear)
}

Example 45: NOT EXISTS

Find people without email:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?person ?name
WHERE {
  ?person foaf:name ?name .
  FILTER NOT EXISTS { ?person foaf:email ?email }
}

Example 46: MINUS

Set difference - people who don't work at any company:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX ex: <http://example.org/>

SELECT ?person ?name
WHERE {
  ?person a foaf:Person .
  ?person foaf:name ?name .

  MINUS {
    ?person ex:worksAt ?company .
  }
}

Example 47: Complex Property Path

Find all organizational hierarchies:

PREFIX org: <http://www.w3.org/ns/org#>

SELECT ?person ?manager ?level
WHERE {
  ?person a foaf:Person .

  # Find manager at any level
  ?person (^org:reportsTo)* ?manager .

  # Calculate reporting level
  BIND(1 AS ?level)
}

Example 48: Conditional Logic

Categorize people by age:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?age ?category
WHERE {
  ?person foaf:name ?name .
  ?person foaf:age ?age .

  BIND(
    IF(?age < 18, "minor",
      IF(?age < 65, "adult", "senior")
    ) AS ?category
  )
}

Example 49: String Manipulation

Extract username and domain from email:

PREFIX foaf: <http://xmlns.com/foaf/0.1/>

SELECT ?name ?username ?domain
WHERE {
  ?person foaf:name ?name .
  ?person foaf:email ?email .

  BIND(STRBEFORE(?email, "@") AS ?username)
  BIND(STRAFTER(?email, "@") AS ?domain)
}

Example 50: Date/Time Operations

Find recent activities:

PREFIX ex: <http://example.org/>

SELECT ?person ?activity ?date
WHERE {
  ?person ex:activity ?activity .
  ?activity ex:date ?date .

  # Activities in last 30 days
  FILTER(?date > (now() - "P30D"^^xsd:duration))
}
ORDER BY DESC(?date)

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Performance Tips

Use Specific Predicates

Good:

?person foaf:name ?name .

Avoid:

?person ?p ?name .
FILTER(?p = foaf:name)

Order Patterns by Selectivity

Good (most selective first):

?person foaf:email "alice@example.com" .  # Very selective
?person foaf:name ?name .                  # Less selective
?person foaf:knows ?friend .               # Least selective

Use LIMIT

Always use LIMIT when exploring:

SELECT ?s ?p ?o
WHERE { ?s ?p ?o }
LIMIT 100

Avoid Cartesian Products

Bad:

?person1 foaf:name ?name1 .
?person2 foaf:name ?name2 .

Good:

?person1 foaf:name ?name1 .
?person1 foaf:knows ?person2 .
?person2 foaf:name ?name2 .

Use OPTIONAL Wisely

OPTIONAL can be expensive. Use only when necessary.

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Next Steps

1. Review the SPARQL Specification for complete syntax details
2. Check the Implementation Guide for architecture
3. Try examples in your PostgreSQL environment
4. Adapt queries for your specific use case

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References

• W3C SPARQL 1.1 Query Language
• W3C SPARQL 1.1 Update
• Apache Jena Tutorials
• RuVector PostgreSQL Extension