Technical Article

Understanding and Controlling Parallel Query Processing in SQL Server

Data warehousing and general reporting applications tend to be CPU intensive because they need to read and process a large number of rows. To facilitate quick data processing for queries that touch a large amount of data, Microsoft SQL Server exploits the power of multiple logical processors to provide parallel query processing operations such as parallel scans. Through extensive testing, we have learned that, for most large queries that are executed in a parallel fashion, SQL Server can deliver linear or nearly linear response time speedup as the number of logical processors increases. However, some queries in high parallelism scenarios perform suboptimally. There are also some parallelism issues that can occur in a multi-user parallel query workload. This white paper describes parallel performance problems you might encounter when you run such queries and workloads, and it explains why these issues occur. In addition, it presents how data warehouse developers can detect these issues, and how they can work around them or mitigate them.

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Question of the Day

Using OPENJSON

I have some data in a table that looks like this: 

BeerID BeerName    brewer               beerdescription
1      Becks       Interbrew            Beck's is a German-style pilsner beer 
2      Fat Tire    New Belgium          Toasty malt, gentle sweetness, flash of fresh hop bitterness.
3      Mac n Jacks Mac & Jack's Brewery This beer erupts with a floral, hoppy taste
4      Alaskan Amber Alaskan Brewing     Alaskan Brewing Amber Ale is an "alt" style beer
8      Kirin       Kirin Brewing         Kirin Ichiban is a Lager-type beer
If I run this, what is returned? 
select t1.key
    from openjson((select t.* FROM Beer AS t for json path)) t1

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