SmartIndex: An Index Advisor with Learned Cost Estimator
Jianling Gao, Nan Zhao, Ning Wang, Shuang Hao · Proceedings of the 31st ACM International Conference on Information & Knowledge Management · 2022
As an important part of database optimization, index selection problem remains a hot topic. Existing methods tend to use the cost estimated by the DBMS optimizer to measure the benefit of an index. However, due to the limitations of the cost estimation model in database management system (DBMS), these methods may not find the optimal index configuration. To address this problem, we present SmartIndex, an index advisor for relational database with learned cost estimator. We first design a graph convolutional network (GCN) based cost estimation model to predict a query's execution time on certain indexes. After that, we use a greedy method for index selection under certain constraints including number of indexes and storage cost of indexes, which can find better solutions for a given workload.