SQL Query Dissembler –A Self Optimizing Autonomic System

Abstract

Current database workloads often consist of a mixture of short OnLine Transaction Processing (OLTP) queries and typical large
complex queries such as OnLine Analytical Processing (OLAP). OLAP queries usually involve multiple joins, arithmetic operations, nested
sub-queries, and other system or user-defined functions and they typically operate on large data sets. These resource intensive queries can
monopolize the database system resources and negatively impact the performance of smaller, possibly more important, queries. In this paper, we
present an approach to managing the execution of large queries that involves the decomposition of large queries into an equivalent set of smaller
queries and then scheduling the smaller queries so that the work is accomplished with less impact on other queries. Here we implement a SQL
disassembler that actually controls the impact of the execution of large queries that has the impact on the other workload classes in a Database
Management System. The approach involved divides a large query into an equivalent set of smaller queries and later schedules the execution of
these smaller queries.

Keywords: Query Optimization, DBMS, Dissembler