Abstract-Extraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization, and insertion into a data warehouse. In this paper, we delve into the logical optimization of ETL processes, modeling it as a state-space search problem. We consider each ETL workflow as a state and fabricate the state space through a set of correct state transitions. Moreover, we provide an exhaustive and two heuristic algorithms toward the minimization of the execution cost of an ETL workflow. The heuristic algorithm with greedy characteristics significantly outperforms the other two algorithms for a large set of experimental cases.
In REF , the authors consider ETL workflows as states and use transitions to generate new states in order to navigate through the state space.
State-space optimization of ETL workflows
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Computer Science