Abstract: Methods, information handling systems and computer readable media are disclosed for detection and repair of fragmentation in databases. In one embodiment, a method includes obtaining log data reflecting transactions in a database, where the log data is generated during operation of the database. The method continues with applying a machine learning classification model to at least a portion of the log data to obtain a first prediction, where the first prediction indicates whether defragmentation of the database should be scheduled. In this embodiment the method also includes using a machine learning time series forecasting model to obtain a second prediction, where the second prediction identifies a future time interval of low relative database utilization, and scheduling a defragmentation procedure for performance during the future time interval of low relative database utilization.

Abstract: Methods, information handling systems and computer readable media are disclosed for detection and repair of fragmentation in databases. In one embodiment, a method includes obtaining log data reflecting transactions in a database, where the log data is generated during operation of the database. The method continues with applying a machine learning classification model to at least a portion of the log data to obtain a first prediction, where the first prediction indicates whether defragmentation of the database should be scheduled. In this embodiment the method also includes using a machine learning time series forecasting model to obtain a second prediction, where the second prediction identifies a future time interval of low relative database utilization, and scheduling a defragmentation procedure for performance during the future time interval of low relative database utilization.