On saying “Enough already!” in SQL

Abstract

In this paper we study a simple SQL extension that enables query writers to explicitly limit the cardinali~of a query result.We examine its impact on the query optimization and run-time execution components of a relational DBMS, presenting two apprwachesConservalive approach and an Aggressive appraactio exploiting cat-dinality limits in relational query plans. Results obtained fmm ml empirical study conducted using DB2 demonstrate the benefits of the SQL extension and illuslrafe the tradeofs between our two approaches to implementing it.

On Real-Time Top k Querying for Mobile Services

“…Areas like web-based information services, enterprise information systems or content-based media retrieval already make intensive use of this new paradigm. A variety of applications in relational databases [CK97], multi-media databases [OR+98] or recent approaches in location-based services [DGS00] also show that top k queries are essential for advanced database retrieval.…”

Processing top-N relational queries by learning

“…He emphasized the need to support approximate and ranked matches in a database query language, and introduced vague predicates. Carey and Kossmann (1997;1998) proposed techniques to optimize top-N queries when the scoring is done through the SQL "Order By" clause by reducing the size of intermediate results. Donjerkovic and Ramakrishnan (1999) use a probabilistic approach to optimize top-N queries and the ranking condition involves a single attribute.…”

Limiting Result Cardinalities for Multidatabase Queries Using Histograms

“…Thus, a special query operator is required which can be placed in the query execution plan and 'cuts' the tuple stream after the desired cardinality. Following the operator introduced in [CK97], we added an operator stop to our query engine, which implements the iterator model [Gra93] and passes a given number of tuples from the input stream. At physical level the stop operator has several implementations: a simple pipelined scan-stop operation for unordered limitations and a blocking sort-stop operation, that collects the top or bottom Ò tuples from the input stream in a sorted heap and produces the result set after processing the whole input.…”

“…In [CK97] two placement strategies are discussed. With the conservative policy, the stop operator is inserted at a point in the query plan where no tuple is discarded that might be part of the final result.…”

“…e.g. [CK97,TGO99]). In contrast to these approaches we have to deal with the problem that in a multidatabase environment there are usually legacy systems acting as local data sources.…”