2004/06/13 by Jarek Gryz, Junjie Guo, Linqi Liu +1 · 1 citation
Computer Science · #Advanced Database Systems and Queries #Data Management and Algorithms #Semantic Web and Ontologies #Computer science #SQL #Operator (biology) #Sampling (signal processing) #IBM #Database #Query by Example #Data mining #Information retrieval #Web search query #Search engine #Filter (signal processing)
paper · doi:10.1145/1007568.1007664
openalex publication_date 2004/06/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
Executing ad hoc queries against large databases can be prohibitively expensive. Exploratory analysis of data may not require exact answers to queries, however: results based on sampling the data are often satisfactory. Supporting sampling as a primitive SQL operator turns out to be difficult because sampling does not commute with many SQL operators.In this paper, we describe an implementation in IBM® DB2® Universal Database (UDB) of a sampling operator that commutes with some SQL operators. As a result, the query with the sampling operator always returns a random sample of the answers and in many cases runs faster than it would have without such an operator.