How to write SPARQL query that efficiently matches string literals while ignoring case

Question

I am using Jena ARQ to write a SPARQL query against a large ontology being read from Jena TDB in order to find the types associated with concepts based on rdfs label:

SELECT DISTINCT ?type WHERE {
 ?x <http://www.w3.org/2000/01/rdf-schema#label> "aspirin" .
 ?x <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> ?type .
}

This works pretty well and is actually quite speedy (<1 second). Unfortunately, for some terms, I need to perform this query in a case-insensitive way. For instance, because the label "Tylenol" is in the ontology, but not "tylenol", the following query comes up empty:

SELECT DISTINCT ?type WHERE {
 ?x <http://www.w3.org/2000/01/rdf-schema#label> "tylenol" .
 ?x <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> ?type .
}

I can write a case-insensitive version of this query using FILTER syntax like so:

SELECT DISTINCT ?type WHERE {
 ?x <http://www.w3.org/2000/01/rdf-schema#label> ?term .
 ?x <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> ?type .
 FILTER ( regex (str(?term), "tylenol", "i") )
}

But now the query takes over a minute to complete! Is there any way to write the case-insensitive query in a more efficient manner?

Answer 1

The reason the query with the FILTER query runs slower is because ?term is unbound it requires scanning the PSO or POS index to find all statements with the rdfs:label predicate and filter them against the regex. When it was bound to a concrete resource (in your first example), it could use a OPS or POS index to scan over only statements with the rdfs:label predicate and the specified object resource, which would have a much lower cardinality.

The common solution to this type of text searching problem is to use an external text index. In this case, Jena provides a free text index called LARQ, which uses Lucene to perform the search and joins the results with the rest of the query.

Answer 2

From all the the possible string operators that you can use in SPARQL, regex is probably the most expensive one. Your query might run faster if you avoid regex and you use UCASE or LCASE on both sides of the test instead. Something like:

SELECT DISTINCT ?type WHERE {
 ?x <http://www.w3.org/2000/01/rdf-schema#label> ?term .
 ?x <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> ?type .
 FILTER (lcase(str(?term)) = "tylenol")
}

This might be faster but in general do not expect great performance for text search with any triple store. Triple stores are very good at graph matching and not so good at string matching.