As a DBA, you might come across a request where you need to extract the domain of the email address, the email address that is stored in the database table. In case you want to count the most used domain names from email addresses in any given table, you can count the number of extracted domains from Email in SQL Server as shown below.
SQL Queries could be used to extract the domain from the Email address.
Let us created table named “email_demo” –
create table (ID int, Email varchar (200));
#dbms #sql #sql-server
SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:
1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.
2. Every database seller needs an approach to separate its item from others.
Right now, contrasts are noted where fitting.
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When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.
When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,
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This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,
In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.
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Would SQL Server graph database features fit your next project? While you may not know the definitive answer right now, you might be wondering, “What problems does it solve?”.
In broad terms, this post tackles the issues of what a graph database is, what its uses are, and what benefits you and your stakeholders can derive from SQL Server graph database capabilities. And see for yourself why that is not another excuse for using something new for your new project. So, if you haven’t yet checked out this “feature”, it’s time to take a look at how cool this is.
Who knows? This can be a great solution for your next project.
So, let’s dive right in.
While we know rows, columns, primary and foreign keys are part of relational databases, graph databases use nodes and edges. They are mainly suitable for many-to-many relationships. Unlike the HierarchyID, a node can have more than 1 parent, while HierarchyIDs are limited to one-to-many relationships only.
Meanwhile, nodes can have properties, and edges define the relationship between nodes.
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When you develop large chunks of T-SQL code with the help of the SQL Server Management Studio tool, it is essential to test the “Live” behavior of your code by making sure that each small piece of code works fine and being able to allocate any error message that may cause a failure within that code.
The easiest way to perform that would be to use the T-SQL debugger feature, which used to be built-in over the SQL Server Management Studio tool. But since the T-SQL debugger feature was removed completely from SQL Server Management Studio 18 and later editions, we need a replacement for that feature. This is because we cannot keep using the old versions of SSMS just to support the T-SQL Debugger feature without “enjoying” the new features and bug fixes that are released in the new SSMS versions.
If you plan to wait for SSMS to bring back the T-SQL Debugger feature, vote in the Put Debugger back into SSMS 18 to ask Microsoft to reintroduce it.
As for me, I searched for an alternative tool for a T-SQL Debugger SSMS built-in feature and found that Devart company rolled out a new T-SQL Debugger feature to version 6.4 of SQL – Complete tool. SQL Complete is an add-in for Visual Studio and SSMS that offers scripts autocompletion capabilities, which help develop and debug your SQL database project.
The SQL Debugger feature of SQL Complete allows you to check the execution of your scripts, procedures, functions, and triggers step by step by adding breakpoints to the lines where you plan to start, suspend, evaluate, step through, and then to continue the execution of your script.
You can download SQL Complete from the dbForge Download page and install it on your machine using a straight-forward installation wizard. The wizard will ask you to specify the installation path for the SQL Complete tool and the versions of SSMS and Visual Studio that you plan to install the SQL Complete on, as an add-in, from the versions that are installed on your machine, as shown below:
Once SQL Complete is fully installed on your machine, the dbForge SQL Complete installation wizard will notify you of whether the installation was completed successfully or the wizard faced any specific issue that you can troubleshoot and fix easily. If there are no issues, the wizard will provide you with an option to open the SSMS tool and start using the SQL Complete tool, as displayed below:
When you open SSMS, you will see a new “Debug” tools menu, under which you can navigate the SQL Debugger feature options. Besides, you will see a list of icons that will be used to control the debug mode of the T-SQL query at the leftmost side of the SSMS tool. If you cannot see the list, you can go to View -> Toolbars -> Debugger to make these icons visible.
During the debugging session, the SQL Debugger icons will be as follows:
The functionality of these icons within the SQL Debugger can be summarized as:
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