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Month: July 2017

Scale-able Windows Aggregate Functions With Row Store Objects

  • by datatake
  • Posted on July 24, 2017July 26, 2017
  • Uncategorized

In this post I will demonstrate how a neat trick brought to my attention by Niko Neugebauer can turn the processing of windowing functions from “Anti-scale” to scale-ability. First of all we need to create […]

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Creating Continuous Integration Build Pipelines With Jenkins, Docker and SQL Server

  • by datatake
  • Posted on July 18, 2017July 20, 2017
  • Uncategorized

In the world of continuous integration and delivery where we might want to perform numerous builds a day. Docker is ideally suited for spinning up environments and then tearing them down afterwards in use cases […]

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In-Memory Engine DURABILITY = SCHEMA_ONLY And Transaction Rollback

  • by datatake
  • Posted on July 17, 2017
  • Uncategorized

I was fortunate enough to be selected to speak at SQL Saturday Dublin, the talk I gave was on leveraging the in-memory engine, the basic flow of the presentation is thus: I ask the audience […]

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The Fundamentals Of Processing A SQL Server Workload In A Scale-able Manner

  • by datatake
  • Posted on July 16, 2017October 18, 2017
  • Uncategorized

In this blog post I wanted to distill down the most fundamental points to consider when attempting to process a SQL Server workload in a scale-able manner. However, many of the principles I will outline […]

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Ring Buffer Shock Absorb-er Pattern and SQL Server

  • by datatake
  • Posted on July 16, 2017July 17, 2017
  • Uncategorized

This post continues my work on the LMax disrupt or pattern, I’ve already covered this already, what I have not covered is: Spinlock profiling Wait statistic profiling How the in-memory engine now behaves with SQL […]

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