SQL is one of the most important tool a Data Scientist or a Data analyst should know of. SQL is a query language which is used to manipulate and retrieve information from a Database.
SQL is used with R-DBMS (Relationship Database Management System) for retrieving and querying purpose.
In this blog, we will look into various basic SQL queries , where and when those queries are used.
There are five types of SQL commands:
The DDL commands are used to define the structure of the database. It is used for creating and modifying the database objects such as table, indexes etc… The basic DDL Commands are:
CREATE TABLE <table_name> (
DROP TABLE <table_name>;
TRUNCATE TABLE <table_name>;
ALTER TABLE <table_name>
ADD <column_name> datatype;
ALTER TABLE <table_name>
DROP COLUMN <column_name>;
ALTER TABLE <table_name>
MODIFY COLUMN <column_name> datatype;
ALTER TABLE <table_name>
RENAME TO <new_table_name>;
DQL command are query commands which are used to retrieve data from the database.
Most used DQL command is SELECT command
Various condition can be specified with the select command. We will look into that in another blog.
SELECT * FROM<table_name>;
SELECT <column_name1>, <column_name2>, …
_‘*’ operator _is used for selecting all the columns from a table.
#database #rdbms #sql #mysql
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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There is no doubt that writing code is more art than science and every coder cannot write beautiful code which is both readable and maintainable, even with the experience. Yes, it’s blunt and hard but it’s mostly true.
In general, coding improves with experience but only when you learn the art of coding like favoring composition over inheritance or coding for interface than implementation, but, unfortunately only a few developers able to master these techniques.
The same applies to SQL queries. The way you structure your query, the way you write it goes a long way to communicate your intent to the fellow developer, DBA, and even yourself after a few months.
Whenever I see SQL queries on emails from different developers, I can see the stark difference in their writing style. Some developers and DBAs write it so neatly and indent their query such that you can easily spot key details like which columns you are extracting, and from which table, and what are joining or filtering conditions.
Since in real-life projects, SQL queries are hardly one-liner, learning the right way to write complex SQL queries makes a lot of difference; especially when you share that query to someone for review or execution. It also helps when you read it yourself later as I said, after a few months.
The problem is there are many books and courses to teach you SQL like what is a table, different SQL commands but there are very few (like The Complete SQL Bootcamp by Josh Portilla) which focus on writing proper SQL queries.
In this article, I am going to show you a couple of styles which I have tried in the past, their pros and cons and what I think is the best way to write SQL queries.
Unless you have a good reason not to use my style e.g. you have a better style or you want to stick with the style used in your project (consistency overrules everything) there is no reason not to use it.
By the way, I expect that you are familiar with SQL and definitely know how to write queries. I expect that you have used different SQL clauses like SELECT, INSERT, UPDATE, DELETE and understand their meaning in a SQL query. If you are not, it’s better you gain some experience with SQL by joining some of my recommended courses like:
Learn SQL by CodeCademy
Introduction to SQL by Jon Flanders
The Complete SQL Bootcamp by Josh Portilla, a Data Scientist, on Udemy or
SQL for Newbs: Data Analysis for Beginners by David Kim and Peter Sefton’s course on Udemy.
They all are great courses and teach you SQL basics, but, if you need some free alternatives you can also check out this list of free SQL courses for programmers and developers.
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This article will introduce the concept of SQL recursive. Recursive CTE is a really cool. We will see that it can often simplify our code, and avoid a cascade of SQL queries!
The recursive queries are used to query hierarchical data. It avoids a cascade of SQL queries, you can only do one query to retrieve the hierarchical data.
First, what is a CTE? A CTE (Common Table Expression) is a temporary named result set that you can reference within a SELECT, INSERT, UPDATE, or DELETE statement. For example, you can use CTE when, in a query, you will use the same subquery more than once.
A recursive CTE is one having a subquery that refers to its own name!
Recursive CTE is defined in the SQL standard.
A recursive CTE has this structure:
In this example, we use hierarchical data. Each row can have zero or one parent. And it parent can also have a parent etc.
Create table test (id integer, parent_id integer); insert into test (id, parent_id) values (1, null); insert into test (id, parent_id) values (11, 1); insert into test (id, parent_id) values (111, 11); insert into test (id, parent_id) values (112, 11); insert into test (id, parent_id) values (12, 1); insert into test (id, parent_id) values (121, 12);
For example, the row with id 111 has as ancestors: 11 and 1.
Before knowing the recursive CTE, I was doing several queries to get all the ancestors of a row.
For example, to retrieve all the ancestors of the row with id 111.
While (has parent) Select id, parent_id from test where id = X
With recursive CTE, we can retrieve all ancestors of a row with only one SQL query :)
WITH RECURSIVE cte_test AS ( SELECT id, parent_id FROM test WHERE id = 111 UNION SELECT test.id, test.parent_id FROM test JOIN cte_test ON cte_test.id = test.parent_id
) SELECT * FROM cte_test
It indicates we will make recursive
It is the initial query.
It is the recursive expression! We make a jointure with the current CTE!
Replay this example here
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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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Let’s say the chief credit and collections officer asks you to list down the names of people, their unpaid balances per month, and the current running balance and wants you to import this data array into Excel. The purpose is to analyze the data and come up with an offer making payments lighter to mitigate the effects of the COVID19 pandemic.
Do you opt to use a query and a nested subquery or a join? What decision will you make?
Before we do a deep dive into syntax, performance impact, and caveats, why not define a subquery first?
In the simplest terms, a subquery is a query within a query. While a query that embodies a subquery is the outer query, we refer to a subquery as the inner query or inner select. And parentheses enclose a subquery similar to the structure below:
SELECT col1 ,col2 ,(subquery) as col3 FROM table1 [JOIN table2 ON table1.col1 = table2.col2] WHERE col1 <operator> (subquery)
We are going to look upon the following points in this post:
As is customary, we provide examples and illustrations to enhance understanding. But bear in mind that the main focus of this post is on subqueries in SQL Server.
Now, let’s get started.
For one thing, subqueries are categorized based on their dependency on the outer query.
Let me describe what a self-contained subquery is.
Self-contained subqueries (or sometimes referred to as non-correlated or simple subqueries) are independent of the tables in the outer query. Let me illustrate this:
-- Get sales orders of customers from Southwest United States -- (TerritoryID = 4) USE [AdventureWorks] GO SELECT CustomerID, SalesOrderID FROM Sales.SalesOrderHeader WHERE CustomerID IN (SELECT [CustomerID] FROM [AdventureWorks].[Sales].[Customer] WHERE TerritoryID = 4)
As demonstrated in the above code, the subquery (enclosed in parentheses below) has no references to any column in the outer query. Additionally, you can highlight the subquery in SQL Server Management Studio and execute it without getting any runtime errors.
Which, in turn, leads to easier debugging of self-contained subqueries.
The next thing to consider is correlated subqueries. Compared to its self-contained counterpart, this one has at least one column being referenced from the outer query. To clarify, I will provide an example:
USE [AdventureWorks] GO SELECT DISTINCT a.LastName, a.FirstName, b.BusinessEntityID FROM Person.Person AS p JOIN HumanResources.Employee AS e ON p.BusinessEntityID = e.BusinessEntityID WHERE 1262000.00 IN (SELECT [SalesQuota] FROM Sales.SalesPersonQuotaHistory spq WHERE p.BusinessEntityID = spq.BusinessEntityID)
Were you attentive enough to notice the reference to BusinessEntityID from the Person table? Well done!
Once a column from the outer query is referenced in the subquery, it becomes a correlated subquery. One more point to consider: if you highlight a subquery and execute it, an error will occur.
And yes, you are absolutely right: this makes correlated subqueries pretty harder to debug.
To make debugging possible, follow these steps:
Isolating the subquery for debugging will make it look like this:
SELECT [SalesQuota] FROM Sales.SalesPersonQuotaHistory spq WHERE spq.BusinessEntityID = <constant value>
Now, let’s dig a little deeper into the output of subqueries.
Well, first, let’s think of what returned values can we expect from SQL subqueries.
In fact, there are 3 possible outcomes:
Let’s start with single-valued output. This type of subquery can appear anywhere in the outer query where an expression is expected, like the WHERE clause.
-- Output a single value which is the maximum or last TransactionID USE [AdventureWorks] GO SELECT TransactionID, ProductID, TransactionDate, Quantity FROM Production.TransactionHistory WHERE TransactionID = (SELECT MAX(t.TransactionID) FROM Production.TransactionHistory t)
When you use a MAX() function, you retrieve a single value. That’s exactly what happened to our subquery above. Using the equal (=) operator tells SQL Server that you expect a single value. Another thing: if the subquery returns multiple values using the equals (=) operator, you get an error, similar to the one below:
Msg 512, Level 16, State 1, Line 20 Subquery returned more than 1 value. This is not permitted when the subquery follows =, !=, <, <= , >, >= or when the subquery is used as an expression.
Next, we examine the multi-valued output. This kind of subquery returns a list of values with a single column. Additionally, operators like IN and NOT IN will expect one or more values.
-- Output multiple values which is a list of customers with lastnames that --- start with 'I' USE [AdventureWorks] GO SELECT [SalesOrderID], [OrderDate], [ShipDate], [CustomerID] FROM Sales.SalesOrderHeader WHERE [CustomerID] IN (SELECT c.[CustomerID] FROM Sales.Customer c INNER JOIN Person.Person p ON c.PersonID = p.BusinessEntityID WHERE p.lastname LIKE N'I%' AND p.PersonType='SC')
And last but not least, why not delve into whole table outputs.
-- Output a table of values based on sales orders USE [AdventureWorks] GO SELECT [ShipYear], COUNT(DISTINCT [CustomerID]) AS CustomerCount FROM (SELECT YEAR([ShipDate]) AS [ShipYear], [CustomerID] FROM Sales.SalesOrderHeader) AS Shipments GROUP BY [ShipYear] ORDER BY [ShipYear]
Have you noticed the FROM clause?
Instead of using a table, it used a subquery. This is called a derived table or a table subquery.
And now, let me present you some ground rules when using this sort of query:
In this case, a derived table has the benefits of a physical table. That’s why in our example, we can use COUNT() in one of the columns of the derived table.
That’s about all regarding subquery outputs. But before we get any further, you may have noticed that the logic behind the example for multiple values and others as well can also be done using a JOIN.
-- Output multiple values which is a list of customers with lastnames that start with 'I' USE [AdventureWorks] GO SELECT o.[SalesOrderID], o.[OrderDate], o.[ShipDate], o.[CustomerID] FROM Sales.SalesOrderHeader o INNER JOIN Sales.Customer c on o.CustomerID = c.CustomerID INNER JOIN Person.Person p ON c.PersonID = p.BusinessEntityID WHERE p.LastName LIKE N'I%' AND p.PersonType = 'SC'
In fact, the output will be the same. But which one performs better?
Before we get into that, let me tell you that I have dedicated a section to this hot topic. We’ll examine it with complete execution plans and have a look at illustrations.
So, bear with me for a moment. Let’s discuss another way to place your subqueries.
#sql server #sql query #sql server #sql subqueries #t-sql statements #sql