October 9, 2019: Query Optimization Statistics – The Driving Force Behind Query Performance

1515 SW 5th Ave. Suite 900, Portland, OR
6:00PM – 6:30PM social | 6:30PM – 8:30PM meeting

Vern Rabe
Query Optimization Statistics – The Driving Force Behind Query Performance
Download the presentation material here.

When the SQL Server optimizer evaluates a query to determine how best to execute it, the statistics are quite possibly the most important information at its disposal. But SQL Server statistics objects aren’t perfect because they only contain estimated summary information. In this session, we’ll start with an overview of what the statistics objects are, how the optimizer uses them, and some general guidelines for their maintenance. Then we’ll look at some of the issues, how to find them, and how to solve them, that can arise due to their imperfection: ascending keys (the most prevalent statistics based performance killer?), skewed distribution, or downright bad summary information. There’ll be many examples, and even a stored procedure to help you find ascending keys. By applying the techniques we’ll discuss, you WILL see improved query performance.

Vern RabeVern is an independent SQL Server consultant and contract trainer in Portland, OR, and leader of the OregonSQL user group. He has attained MCSE, MCITP (both Administration and Development), and MCT certifications, among others. Vern has been passionate about databases since 1992 and has worked with SQL Server since version 4.21a. He provides broad technical SQL Server knowledge gained from the mixture of academic and practical experiences acquired from his classroom instructing and varied consulting contracts.


ServerLogic


Michael Curry
Theory Driven Data Science: Cybersecurity Improvement using SQL, R and machine learning

Data science seeks to uncover actionable data relationships to solve pressing organizational needs e.g. improved cyber security behavior, and this talk presents three steps for doing just that. The goal is a clear picture on how to leverage those actionable data relationships, e.g. how effective was a cyber security training program? The aim of this presentation is to provide an exemplary theory driven approach to building evidence of being better prepared against a cybersecurity threat.

Michael CurryDr. Michael Curry is a Cyber security behavioral researcher utilizing data science methodologies to develop actionable data relationships to solve pressing organizational needs e.g. improved cyber security behavior. He is part of the OregonSQL Leadership and also an instructor for Oregon State University.


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Refreshments graciously provided by ServerLogic.


We wish to acknowledge the OSHU Information Technology Group for supporting Oregon SQL by generously providing the meeting venue.


 

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