In the world of SQL, knowing how to efficiently aggregate and analyze data is essential. For this reason, SQL offers two very effective tools: GROUP BY and PARTITION BY. Despite their initial similarities, they have varied functions and are employed in various situations. The differences between GROUP BY and PARTITION BY, their applications, and real-world examples will all be covered in this article to help you select the best tool for your data analysis requirements.

Understanding GROUP BY
GROUP BY is used to aggregate data across multiple records by one or more columns. It groups rows with the same values in specified columns into aggregated data like SUM, AVG, COUNT, etc. It's commonly used in conjunction with aggregate functions to perform calculations on each group of rows.
Syntax
SELECT column_name, AGGREGATE_FUNCTION(column_name)
FROM table_name
GROUP BY column_name;

Example
Suppose we have a sales table with the following data.

To find the total sales amount for each product, we use GROUP BY.

This query will return

Understanding PARTITION BY
PARTITION BY is used with window functions to perform calculations across a set of table rows that are somehow related to the current row. Unlike GROUP BY, it doesn't reduce the number of rows in the result set. Instead, it adds a new column with the aggregated result for each row.

Syntax
SELECT column_name,
       WINDOW_FUNCTION() OVER (PARTITION BY column_name)
FROM table_name;

Example
Using the same sales table, let's say we want to calculate the total sales for each product but display it alongside each row.
SELECT
    product,
    amount,
    SUM(amount) OVER (PARTITION BY product) AS total_sales
FROM
    sales;

This query will return.

# 'total_sales': 'window_function',
(B, SUM, OVER)
50 |

Here, the total_sales column shows the sum of sales for each product next to every row, retaining all the original rows.

Key Differences

• Purpose
  • GROUP BY is used for aggregating data to produce a summary row for each group.
  • PARTITION BY is used to perform calculations across related rows without collapsing them into summary rows.

• Result Set
  • GROUP BY reduces the number of rows by grouping them.
  • PARTITION BY keeps the original number of rows, adding new columns with aggregated data.

• Usage Context
  • Use GROUP BY when you need summarized results, like total sales per product.
  • Use PARTITION BY when you need detailed results along with aggregated values, like total sales displayed alongside each sale.

Practical Scenarios

• Sales Reporting
  • GROUP BY: To get a report of total sales per product.
  • PARTITION BY: To analyze the sales trend within each product category while keeping individual sales records visible.

• Employee Performance
  • GROUP BY: To find average performance metrics per department.
  • PARTITION BY: To show each employee's performance metrics along with the department's average.

• Customer Transactions
  • GROUP BY: To calculate total transactions per customer.
  • PARTITION BY: To display each transaction along with the running total of transactions per customer.

Conclusion
Both GROUP BY and PARTITION BY are essential tools in SQL for data aggregation and analysis. GROUP BY is ideal for summary-level data, while PARTITION BY is powerful for detailed, row-level analysis with aggregated data. Understanding when and how to use these clauses will enhance your ability to write efficient and effective SQL queries, providing deeper insights into your data.

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Common Table Expressions (CTEs) and subqueries can be chosen based on a number of criteria, including performance, readability, maintainability, and use case specificity.

Subqueries
When to Use Subqueries?

• Simplicity: Use subqueries for simple, straightforward queries where the logic is easy to understand without nesting.
• Single Use: When the result of the subquery is only needed once within the main query.
• Inline Calculations: When performing calculations or filtering within a single SQL statement.
• Performance: In some databases, subqueries might perform better due to optimization techniques. However, this can vary depending on the database engine and query complexity.

    -- Select all employees whose salaries are not null
    SELECT *
    FROM Employees
    WHERE EmployeeID IN (
        SELECT EmployeeID
        FROM Employees
        WHERE Salary IS NOT NULL
    );

Common Table Expressions (CTEs)
When to Use CTEs?

1. Readability and Maintainability: CTEs are easier to read and maintain, especially for complex queries. They allow you to break down a query into understandable parts.
2. Reusability: When you need to use the result of a subquery multiple times within a query.
3. Recursion: Use recursive CTEs for hierarchical data or to perform recursive operations.
4. Modularity: When you want to modularize complex query logic for better organization and readability.
5. Intermediate Results: When breaking down complex logic into steps can help in debugging and optimizing queries.

    -- Using a CTE to select all employees whose salaries are not null
    WITH FilteredEmployees AS (
        SELECT EmployeeID, FirstName, LastName, Department, Salary, HireDate
        FROM Employees
        WHERE Salary IS NOT NULL
    )
    SELECT *
    FROM FilteredEmployees;

Comparing Use Cases
Readability:
    CTE: Better for complex queries due to modularity and readability.
    Subquery: This can become difficult to read if nested deeply within the main query.
Maintainability:
    CTE: Easier to maintain due to clear structure and separation of logic.
    Subquery: Harder to maintain, especially for complex and deeply nested queries.
Performance: Performance can vary based on the database engine and query structure. Some engines optimize CTEs better, while others might handle subqueries more efficiently. It's crucial to test and profile queries in your specific database environment.
Recursion:
    CTE: The only choice for recursive queries.
    Subquery: Not suitable for recursion.

Example with both CTE and Subquery
Let's consider a scenario where you want to retrieve employees with a salary greater than a certain threshold, but you also want to get the average salary of their department.

Using Subquery
SELECT EmployeeID, FirstName, LastName, Department, Salary
FROM Employees e
WHERE Salary > (
    SELECT AVG(Salary)
    FROM Employees
    WHERE Department = e.Department
);

Using CTE
WITH DepartmentAvgSalaries AS (
    SELECT Department, AVG(Salary) AS AvgSalary
    FROM Employees
    GROUP BY Department
)
SELECT e.EmployeeID, e.FirstName, e.LastName, e.Department, e.Salary
FROM Employees e
JOIN DepartmentAvgSalaries das ON e.Department = das.Department
WHERE e.Salary > das.AvgSalary;

Use subqueries for simpler, straightforward, and single-use cases.
Use CTEs for complex, multi-step, and recursive queries, as well as for improving readability and maintainability.

Always consider the complexity of your query and the need for readability and maintainability, and then choose the approach that best fits those needs.

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SQL Server is typically installed by default and functions perfectly. However, in certain unique circumstances, which may result from security settings, a Windows account cannot open a SQL Server database. This article provides a solution to the issue.

Issue
If your SQL Server database cannot be started automatically, try starting it from a service.

Find SQL Server and select Start in the upper left corner; however, an error notice appears.,Find SQL Server and select Start in the upper left corner; however, an error notice appears.

Fix
Right Click SQL Server in Service:

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Synonyms: What Are They?
A synonym is a type of database object that gives another database object, called the base object, a different name. The base object might be on a local or remote server.

Why Use Synonyms?

• Simplifying: They make the SQL queries simpler by giving complex object names shorter or more meaningful names.
• Abstraction: By hiding the specifics of the underlying database objects, synonyms enable modifications to those items without impacting the code that uses them as references.
• Flexibility: You can modify the database structure using them without needing to redo the current SQL code.

Syntax

CREATE SYNONYM schema_name.synonym_name FOR [object]

Example. Create a Synonym for a local object.
I have a Sales. Customer table in the AdventureWorks2022 database. Now, I am going to create a synonym in the MyWork database with the name dbo.SalesCustomer.
--Customer table in AdventureWorks2022
SELECT * FROM AdventureWorks2022.Sales.Customer

--Create a synonym for the Customer table MyWork databasel
USE MyWork
CREATE SYNONYM dbo.SalesCustomer
FOR AdventureWorks2022.Sales.Customer

--Query synonym to access the Sales.Customer base table
SELECT * FROM dbo.SalesCustomer

Output

Example. Create a Synonym for a remote object.

In this example, I have the AdventureWorks 2022.Person.[Address] table on the MyDevServer linked server. Now, I am going to create a synonym named dbo.PersonAddress.
CREATE SYNONYM dbo.PersonAddress FOR MyDevServer.AdventureWorks2022.Person.[Address]

What operations can we do using Synonyms?

The following operations can be performed using synonyms.

• SELECT
• UPDATE
• EXECUTE
• INSERT
• DELETE
• SUB-SELECTS

Get information about synonyms

The catalog view contains an entry for each synonym in a given database.

SELECT * FROM sys.synonyms

Output

Conclusion
Synonyms allow us to utilize shorter, more understandable names for complex or remote database objects, which simplifies and maintains your SQL code.

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//create Temporary Table

CREATE TABLE #Table_Details (
    table_name sysname,
    row_count INT,
    reserved_size VARCHAR(50),
    data_size VARCHAR(50),
    index_size VARCHAR(50),
    unused_size VARCHAR(50)
);
INSERT INTO #Table_Details
EXEC sp_msforeachtable 'sp_spaceused ''?''';

sp_MSforeachtable is a system-stored procedure in Microsoft SQL Server that allows you to execute a specified command against each table in a database.

Ensure that the command you are executing is appropriate for all tables, as sp_MSforeachtable does not check if the command is valid for each individual table.

EXEC sp_spaceused ''?'': The sp_spaceused stored procedure is called for each table. The ? is a placeholder that gets replaced with the table name.
SELECT
    TD.table_name,
    TD.row_count,
    COUNT(*) AS col_count,
    TD.data_size
FROM
    #Table_Details TD
INNER JOIN
    information_schema.columns b ON TD.table_name COLLATE database_default = b.table_name COLLATE database_default
GROUP BY
    TD.table_name,
    TD.row_count,
    TD.data_size
ORDER BY
    CAST(REPLACE(TD.data_size, ' KB', '') AS INT) DESC;
DROP TABLE #Table_Details;

Order By is used to get the biggest table first.

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