Matches in Ruben’s data for { ?s ?p "Recently, Triple Pattern Fragments (TPFs) were introduced as an alternative to reduce server load when high numbers of clients need to evaluate SPARQL queries. This is achieved by moving part of the query execution to the client, at the cost of elevated query times. Since the TPF interface purposely does not support complex constructs such as SPARQL filters, queries that use them need to be executed mostly on the client, resulting in long execution times. We therefore investigated the impact of adding literal substring matching to the interface, with the goal of improving query performance while maintaining low server cost. In this paper, we discuss the client/server setup and compare performance of SPARQL queries on multiple implementations with existing solutions, including Elastic Search and case-insensitive FM-index. Our evaluations indicate that these improvements allow for faster query execution without significantly increasing the load on the server. Offering these additions on TPF servers allows users to obtain faster responses for filter-based SPARQL queries. Furthermore, substring matching can be used to support other filters such as complete regular expressions or range queries."@en }
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- publication abstract "Recently, Triple Pattern Fragments (TPFs) were introduced as an alternative to reduce server load when high numbers of clients need to evaluate SPARQL queries. This is achieved by moving part of the query execution to the client, at the cost of elevated query times. Since the TPF interface purposely does not support complex constructs such as SPARQL filters, queries that use them need to be executed mostly on the client, resulting in long execution times. We therefore investigated the impact of adding literal substring matching to the interface, with the goal of improving query performance while maintaining low server cost. In this paper, we discuss the client/server setup and compare performance of SPARQL queries on multiple implementations with existing solutions, including Elastic Search and case-insensitive FM-index. Our evaluations indicate that these improvements allow for faster query execution without significantly increasing the load on the server. Offering these additions on TPF servers allows users to obtain faster responses for filter-based SPARQL queries. Furthermore, substring matching can be used to support other filters such as complete regular expressions or range queries.".