Estimating aggregates in time-constrained approximate queries in Oracle

The concept of time-constrained SQL queries was introduced to address the problem of long-running SQL queries. A key approach adopted for supporting time-constrained SQL queries is to use sampling to reduce the amount of data that needs to be processed, thereby allowing completion of the query in the specified time constraint. However, sampling does make the query results approximate and hence requires the system to estimate the values of the expressions (especially aggregates) occurring in the select list. Thus, coming up with estimates for aggregates is crucial for time-constrained approximate SQL queries to be useful, which is the focus of this paper. Specifically, we address the problem of estimating commonly occurring aggregates (namely, SUM, COUNT, AVG, MEDIAN, MIN, and MAX) in timeconstrained approximate queries. We give both point and interval estimates for SUM, COUNT, AVG, and MEDIAN using Bernoulli sampling for various type of queries, including join processing with cross pr...

• Type: Conference
• Year: 2009
• Where: EDBT
• Authors: Ying Hu, Seema Sundara, Jagannathan Srinivasan
• Keywords: EDBT 2009, Long-running Sql Queries, SQL Queries, Time-constrained Sql Queries