One way to improve SQL Server performance is to use as few resources as possible. In this post Rahul Mehta demonstrates how you can do this by disconnecting queries post-execution with a simple change in SSMS.
Azure SQL Data Warehouse is a cloud-based, scale-out database capable of processing massive volumes of data, both relational and non-relational. Built on our massively parallel processing (MPP) architecture, SQL Data Warehouse can handle your enterprise workload.
This article shows how to reduce the periodic spikes in the CPU that are caused by the periodic-executing jobs. There is a good reason to make some changes for dismissing them.
We don't test software well enough. Obviously we don't write high enough quality software, but testing should catch more issues. Steve Jones talks about how you can perform better T-SQL testing.
Even a database development framework like Sql Server Data Tools (SSDT) doesn't get it right all the time, and there are ten deployment 'gotchas' in particular that can cause some head-scratching amongst developers to get right. From his unique perspective of creating a tool to make such deployments in SSDT less stressful, Dan Nolan discusses each pitfall and how to avoid it, whether you have ReadyRoll or not.
The way we write code impacts our users, but it can also impact our wallet, especially in cloud computing. Steve Jones wonders how many people bother to profile and test their code.
This article shows a few techniques that help in capturing deleted records.
Phil Factor ponders the use of toolchains in automation, and wonders if there might not be a better way.
Sometimes, it's necessary to have different versions of a database running in production. But how do you establish a single source of truth in source control? Alex Yates from DLM Consultants shows how to use object filters in SQL Compare to build multiple database versions from the same source.
During the development cycle, indexes will be placed on SQL Server tables to speed up performance when searching for records. Lots of thought probably has gone into creating just the right mix of indexes based on how developers think customers will use the system. But how do you tell if all the indexes are being used once your database has been implemented into production?
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I have this data in a table called dbo.NFLTeams
TeamID TeamName City YearEstablished ------ -------- ---- --------------- 1 Cowboys Dallas 1960 2 Eagles Philadelphia 1933 3 Packers Green Bay 1919 4 Chiefs Kansas City 1960 5 49ers San Francisco 1946 6 Broncos Denver 1960 7 Seahawks Seattle 1976 8 Patriots New England 1960If I run this code, how many rows are returned?
SELECT TOP 2
json_objectagg('Team' : TeamName)
FROM dbo.NFLTeams;
See possible answers