Optimizer Statistics: The Key To Efficient, Scalable Databases and Applications

One of the more common reasons why SQL statements run inefficiently is due to poor execution plans as a result of optimizer segment statistics that are either missing, inaccurate, incomplete, misleading or potentially too accurate for its own good. In this presentation we examine a number scenarios where SQL execution plans are inefficient due to deficiencies in the underlining segment statistics, how they can be addressed with appropriate statistics gathering processes and how more recent statistics gathering features and capabilities such as adaptive statistics, real-time statistics and high frequency statistics gathering can assist in enabling a more stable and performant database environment.

One of the more common reasons why SQL statements run inefficiently is due to poor execution plans as a result of optimizer segment statistics that are either missing, inaccurate, incomplete, misleading or potentially too accurate for its own good. In this presentation we examine a number scenarios where SQL execution plans are inefficient due to deficiencies in the underlining segment statistics, how they can be addressed with appropriate statistics gathering processes and how more recent statistics gathering features and capabilities such as adaptive statistics, real-time statistics and high frequency statistics gathering can assist in enabling a more stable and performant database environment.