Using SQL Service Broker for asynchronous external script (R / Python) execution in OLTP systems

Authored by Arvind Shyamsundar (Microsoft) Credits: Prasad Wagle, Srinivasa Babu Valluri, Arun Jayapal, Ranga Bondada, Anand Joseph (members of the Sayint by Zen3 team) Reviewers: Nellie Gustafsson, Umachandar Jayachandran, Dimitri Furman (Microsoft) This blog post was inspired our recent work with the Sayint dev team, who are a part of Zen3 Infosolutions. SQLCAT has been… Read more

Performance implications of using multi-Statement TVFs with optional parameters

Authored by Arvind Shyamsundar (Microsoft) Credits: Prasad Wagle, Srinivasa Babu Valluri, Arun Jayapal, Ranga Bondada, Anand Joseph (members of the Sayint by Zen3 team) Reviewers: Rajesh Setlem, Joe Sack, Dimitri Furman, Denzil Ribeiro (Microsoft) This blog post was inspired our recent work with the Sayint dev team, who are a part of Zen3 Infosolutions. SQLCAT… Read more

Collecting performance data with PSSDIAG for SQL Server on Linux

Reviewed by: Suresh Kandoth,Rajesh Setlem, Steven Schneider, Mike Weiner, Dimitri Furman When analyzing SQL Server performance related issues, customers often have their tools of choice, which can be a feature within the product, a third-party performance monitoring tool, or a home-grown tool that assists in monitoring live performance. For live monitoring, in the SQLCAT lab… Read more

How the SQLCAT Customer Lab is Monitoring SQL on Linux

Reviewed By: Denzil Ribeiro, Dimitri Furman, Mike Weiner, Rajesh Setlem, Murshed Zaman Background SQLCAT often works with early adopter customers, bring them into our lab, and run their workloads. With SQL Server now available on Linux, we needed a way to visualize performance and PerfMon, being a Windows only tool, was no longer an option…. Read more

Performance impact of memory grants on data loads into Columnstore tables

Reviewed by: Dimitri Furman, Sanjay Mishra, Mike Weiner, Arvind Shyamsundar, Kun Cheng, Suresh Kandoth, John Hoang Background Some of the best practices when bulk inserting into a clustered Columnstore table are: Specifying a batch size close to 1048576 rows, or at least greater than 102400 rows, so that they land into compressed row groups directly…. Read more

Build a recommendation system with the support for graph data in SQL Server 2017 and Azure SQL DB

Authored by Arvind Shyamsundar and Shreya Verma Reviewed by Dimitri Furman, Joe Sack, Sanjay Mishra, Denzil Ribeiro, Mike Weiner, Rajesh Setlem Graphs are a very common way to represent networks and relationships between objects. Historically, it is not easy to represent such data structures in relational databases like SQL Server and Azure SQL DB. To… Read more