Skip to main content

Transactions

SQL transactions provide a way to group multiple SQL operations into a single, atomic unit of work. A transaction ensures that either all operations within it are successfully completed (committed) or none of them are (rolled back), maintaining data integrity and consistency. Let's delve into SQL transactions with examples and key concepts.

 

ACID Properties:

Atomicity: Ensures that all operations within a transaction are completed successfully or none at all. If any part of the transaction fails, the entire transaction is rolled back to its initial state.

Consistency: Guarantees that the database remains in a consistent state before and after the transaction. Constraints, triggers, and cascades ensure data validity.

Isolation: Ensures that transactions are isolated from each other until they are completed. Concurrent transactions should not interfere with each other.

Durability: Once a transaction is committed, its changes are permanent even in the event of system failures.

 

Transaction Commands:

BEGIN TRANSACTION: Begins a new transaction explicitly.

COMMIT: Finalizes the transaction and makes all changes permanent.

ROLLBACK: Aborts the transaction and undoes any changes made since the transaction began.

SAVEPOINT: Creates a point within the transaction to which you can roll back.

 

Comments

Post a Comment

Popular posts from this blog

TechUplift: Elevating Your Expertise in Every Click

  Unlock the potential of data with SQL Fundamental: Master querying, managing, and manipulating databases effortlessly. Empower your database mastery with PL/SQL: Unleash the full potential of Oracle databases through advanced programming and optimization. Unlock the Potential of Programming for Innovation and Efficiency.  Transform raw data into actionable insights effortlessly. Empower Your Data Strategy with Power Dataware: Unleash the Potential of Data for Strategic Insights and Decision Making.
Post a Comment
Read more

Python Topics

Learning Python can be an exciting and rewarding journey, especially given its versatility and widespread use in various fields like web development, data science, automation, and more. Here's a structured guide to help you learn Python effectively, covering essential topics from beginner to advanced levels. Beginner Level Introduction to Python Installation and setup Python syntax and interactive shell Writing and running your first Python script Basic Concepts Variables and data types (integers, floats, strings, booleans) Basic arithmetic operations String operation Comments and documentation Control Structures Conditional statements ( if ,  elif ,  else ) Loops ( for ,  while ) Data Structures Lists Tuples Dictionaries Sets Functions Defining and calling functions Function arguments and return values Lambda functions Built-in functions Modules and Packages Importing modules Standard library overview (e.g.,  math ,  datetime ,  random ) Installing and using external packages
Post a Comment
Read more

DAX Functions

These are just some of the many DAX functions available in Power BI. Each  function serves a specific purpose and can be used to perform a wide range of calculations and transformations on your data. Aggregation Functions: SUM : Calculates the sum of values. AVERAGE : Calculates the arithmetic mean of values. MIN : Returns the smallest value in a column. MAX : Returns the largest value in a column. COUNT : Counts the number of rows in a table or column. COUNTA : Counts the number of non-blank values in a column. DISTINCTCOUNT : Counts the number of unique values in a column. Logical Functions: IF : Returns one value if a condition is true and another value if it's false. AND : Returns TRUE if all the conditions are true, otherwise FALSE. OR : Returns TRUE if any of the conditions are true, otherwise FALSE. NOT : Returns the opposite of a logical value. Text Functions: CONCATENATE : Concatenates strings together. LEFT : Returns the leftmost characters from a text string. RIGHT : Ret
Post a Comment
Read more