Deterministic and non-deterministic query optimization techniques in the cloud computing

摘要

Query optimization is considered as one of the main challenges of query processing phases inthe cloud environments. The query optimizer attempts to provide the most optimal executionplan by considering the possible query plans. Therefore, the execution cost of a query canbe affected by some factors, including communication costs, unavailability of resources, andaccess to large distributed data sets. In addition, it is known as NP-hard problem and manyresearchers are focused on this problem in recent years. Some techniques are proposed forsolving this problem. Deterministic and non-deterministic methods are two main categories tostudy these techniques. The deterministic and non-deterministic query optimization methodscan be further divided into three subcategories, cost-based query plan enumeration, multiplequery optimization, and adaptive query optimization methods. Moreover, this paper presentsthe advantages and disadvantages of the algorithms for solving the query optimization problemsin the cloud environments. Moreover, these techniques are compared in terms of optimization,time, cost, efficiency, and scalability. Finally, some key areas are offered to improve the cloudquery optimization mechanisms in the future.