Last week I was speaking at SQLDay 2019 conference in Wroclaw, Poland. My session was about things you should focus on during work with Legacy Databases. One of the topics I discussed was concerning the database usage statistics collection and aggregation (mainly indexes and stored procedures).
After the session, one of the attendees came to me and ask me if I know that actions causing check of Foreign Keys and that use indexes underneath, don’t update index usage stats DMV. I was very surprised because, in my opinion, such behavior would be a huge SQL Server defect. So I decided to check it out…
Read on for Marek’s explanation and demo.
In this blog post, we will look at a detailed explanation of how to use SVM for complex decision boundaries and build Non-Linear Classifiers using SVM. The primary method for doing this is by using Kernels.
In linear SVM we find margin maximizing hyperplane with features Xi’s . Similarly, in Logistic regression, we also try to find the hyperplane which minimizes logistic loss with features Xi’s. Most often when we use both these techniques the results are the same. But linear SVM or for the same reason a logistic regression would fail where there is a need to have complex or non-linear decision boundaries. These types of boundaries are then achieved by SVM using Kernels. So let us understand how SVM creates non-linear boundaries using Kernels
Read on to see how it works.
We have just released two new free video lectures on vectors from a programmer’s point of view. I am experimenting with what ideas do programmers find interesting about vectors, what concepts do they consider safe starting points, and how to condense and present the material.
Click through for the links, one with Python examples and the other with R examples.
This table stores data for an application that has many different types of Pages. Each Page stores different types of data, but instead of creating a separate table for each type, we store all the different data in the varchar
DataValuecolumn and maintain the original data type in the
This structure reduces the complexity required for maintaining our database (compared to creating possibly hundreds of tables, one for each PageName) and makes querying easier (only need to query one table). However, this design could also lead to some unexpected query results.
This is your daily reminder that an attribute should be a thing which describes an entity, not one of multiple things.
The first command you have to learn is ‘docker pull’. You then have to supply something for it to pull, an image that will be used to create your containers. I’m using Powershell for the commands I’m posting this week. Here’s how you get an image with SQL Server 2017:
docker pull mcr.microsoft.com/mssql/server:2017-latest
Click through to learn more.
It could have chosen a Hash Join, but then the order of the Id column from the Posts table wouldn’t have been preserved on the other side.
Merge Joins are order preserving, Hash Joins aren’t. If we use a Hash Join, we’re looking at ordering the results of the join after it’s done.
Read on to learn why, as well as why a few other things are so.
Method 2 : Use xp_cmdshell – although this does mean enabling xp_cmdshell , which is in many organisations as security violation
exec master..xp_cmdshell 'systeminfo'
Click through for several less controversial methods.
This first step when using T-SQL to read Extended Files that are stored in an Azure Storage Account is to create a database credential. Of course the credential will provide essential security information to connect to the Azure Storage Account. This first data point you will need is the URL to a blog storage container in you storage account. If you look below, you can see where you would place your storage account name and the blob storage container name.
Dave gives us the grand tour of the configuration process, including where things differ between on-prem SQL Server and Azure SQL Database (which is quite a bit)