An effective technique and practical utility for approximate query processing
Dr Raj Gopalan
Dr Aneesh Krishna
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Department of Computing
This dissertation studies efficient and effective approximate query processing for decision support systems. A novel method that enables fast query processing and reliable approximation even in highly selective queries is proposed and evaluated. Also, utility software that enables the implementation of the proposed method in databases and enables the execution of approximate query processing in SQL is developed as part of this research.
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Approximate Query Processing on High Dimensionality Database Tables Using Multidimensional Cluster Sampling ViewInoue, T.; Krishna, Aneesh; Gopalan, Raj (2016)Approximate query processing based on random sampling is one of the most useful methods for the efficient computation of large quantities of data kept in databases. However, small samples obtained through random sampling ...
Rudra, Amit; Gopalan, Raj; Achuthan, Narasimaha (2014)Sampling schemes for approximate processing of highly selective decision support queries need to retrieve sufficient number of records that can provide reliable results within acceptable error limits. The k-MDI tree is ...
Rudra, Amit; Gopalan, Raj; Achuthan, Narasimaha (2013)For highly selective queries, a simple random sample of records drawn from a large data warehouse may not contain sufficient number of records that satisfy the query conditions. Efficient sampling schemes for such queries ...