Challenges of Index Recommendation for Databases
نویسنده
چکیده
One important aspect of physical database design is the selection of a proper set of indexes for a workload. Creation of indexes in a database system is subject to storage constraints. It is also affected by the ratio of update operations in the workload. Therefore, the cost and benefit of each set of indexes should be evaluated by a proper optimization method. The large number of index sets that must be assessed and the iterative nature of such optimization methods impose an additional load on the database system. Therefore, an efficient algorithm is needed to develop a practical framework for automating index recommendation. Furthermore, due to the fundamental differences between data models and query languages of NoSQL databases to each other and the relational databases, evaluation of such index recommendation system for NoSQL databases faces many challenges. This paper reviews the challenges and my proposed solutions for developing a self-tuning index recommendation system, especially for a document-based NoSQL database instance.
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