Git is a distributed version control system DVCS designed for efficient source code management, suitable for both small and large projects. It allows multiple developers to work on a project simultaneously without overwriting changes, supporting collaborative work, continuous integration, and deployment. This Git and GitHub tutorial is designed for beginners to learn fundamentals and advanced concepts, including branching, pushing, merging conflicts, and essential Git commands. Prerequisites include familiarity with the command line interface CLI, a text editor, and basic programming concepts. Git was developed by Linus Torvalds for Linux kernel development and tracks changes, manages versions, and enables collaboration among developers. It provides a complete backup of project history in a repository. GitHub is a hosting service for Git repositories, facilitating project access, collaboration, and version control. The tutorial covers topics such as Git installation, repository creation, Git Bash usage, managing branches, resolving conflicts, and working with platforms like Bitbucket and GitHub. The text is a comprehensive guide to using Git and GitHub, covering a wide range of topics. It includes instructions on working directories, using submodules, writing good commit messages, deleting local repositories, and understanding Git workflows like Git Flow versus GitHub Flow. There are sections on packfiles, garbage collection, and the differences between concepts like HEAD, working tree, and index. Installation instructions for Git across various platforms Ubuntu, macOS, Windows, Raspberry Pi, Termux, etc. are provided, along with credential setup. The guide explains essential Git commands, their usage, and advanced topics like debugging, merging, rebasing, patch operations, hooks, subtree, filtering commit history, and handling merge conflicts. It also covers managing branches, syncing forks, searching errors, and differences between various Git operations e.g., push origin vs. push origin master, merging vs. rebasing. The text provides a comprehensive guide on using Git and GitHub. It covers creating repositories, adding code of conduct, forking and cloning projects, and adding various media files to a repository. The text explains how to push projects, handle authentication issues, solve common Git problems, and manage repositories. It discusses using different IDEs like VSCode, Android Studio, and PyCharm, for Git operations, including creating branches and pull requests. Additionally, it details deploying applications to platforms like Heroku and Firebase, publishing static websites on GitHub Pages, and collaborating on GitHub. Other topics include the use of Git with R and Eclipse, configuring OAuth apps, generating personal access tokens, and setting up GitLab repositories. The text covers various topics related to Git, GitHub, and other version control systems Key Pointers Git is a distributed version control system DVCS for source code management. Supports collaboration, continuous integration, and deployment. Suitable for both small and large projects. Developed by Linus Torvalds for Linux kernel development. Tracks changes, manages versions, and provides complete project history. GitHub is a hosting service for Git repositories. Tutorial covers Git and GitHub fundamentals and advanced concepts. Includes instructions on installation, repository creation, and Git Bash usage. Explains managing branches, resolving conflicts, and using platforms like Bitbucket and GitHub. Covers working directories, submodules, commit messages, and Git workflows. Details packfiles, garbage collection, and Git concepts HEAD, working tree, index. Provides Git installation instructions for various platforms. Explains essential Git commands and advanced topics debugging, merging, rebasing. Covers branch management, syncing forks, and differences between Git operations. Discusses using different IDEs for Git operations and deploying applications. Details using Git with R, Eclipse, and setting up GitLab repositories. Explains CI/CD processes and using GitHub Actions. Covers internal workings of Git and its decentralized model. Highlights differences between Git version control system and GitHub hosting platform.
In the realm of Database Management Systems (DBMS), SQL (Structured Query Language) is divided into various types of commands, each serving a specific purpose. Two primary types of SQL commands are Data Definition Language (DDL) and Data Manipulation Language (DML). Understanding the differences between DDL and DML is crucial for anyone working with databases, as these commands perform fundamentally different functions.
Overview of DDL and DML
Data Definition Language (DDL)
DDL commands are used to define and modify the structure of database objects such as tables, indexes, and views. They are primarily concerned with the schema of the database.
Data Manipulation Language (DML)
DML commands are used to manipulate data stored in the database. They are focused on inserting, updating, deleting, and retrieving data from the database tables.
Key Differences Between DDL and DML
Purpose
- DDL: DDL commands define, alter, and manage the structure of database objects. They do not handle the data within these objects but rather the objects themselves.
- DML: DML commands are used to manipulate the data within the database objects. They handle data operations like insertions, updates, deletions, and data retrieval.
Commands
- DDL Commands: CREATE, ALTER, DROP, TRUNCATE
- DML Commands: INSERT, UPDATE, DELETE, SELECT
Execution
- DDL: DDL commands are auto-committed, meaning that once executed, the changes are immediately saved in the database. They cannot be rolled back.
- DML: DML commands are not auto-committed. They require an explicit COMMIT to save the changes permanently. They can be rolled back before the COMMIT is executed.
Transaction Control
- DDL: DDL commands do not support transaction control. Once executed, the changes are permanent.
- DML: DML commands support transaction control. They allow for ROLLBACK to undo changes before committing them.
Effect
- DDL: DDL commands affect the entire schema or database objects.
- DML: DML commands affect the data within the database objects.
- Impact
- DDL: DDL operations can potentially impact the database structure significantly, such as dropping a table which removes all its data and structure.
- DML: DML operations impact only the data within the database objects, not the structure of the objects themselves.
Difference Between DDL and DML
Data Definition Language (DDL) and Data Manipulation Language (DML) are two categories of SQL (Structured Query Language) statements used to manage databases. They serve distinct purposes in defining and manipulating data structures and content. Here’s a comparison of their main differences:
| Feature | DDL | DML |
|---|---|---|
| Full Form | Data Definition Language | Data Manipulation Language |
| Purpose | Define and manage structure of database objects | Manipulate data within database objects |
| Operations | Create, alter, and drop objects (e.g., tables) | Select, insert, update, delete data |
| Examples | CREATE TABLE, ALTER TABLE, DROP TABLE | SELECT, INSERT, UPDATE, DELETE |
| Effect on Data | Changes database schema | Changes data content |
| Transaction Scope | Typically autocommitted | May require explicit transaction management |
| Granularity | Operates at the level of entire database objects | Operates at the level of individual data records |
| Concurrency | Can impact concurrent transactions (locks) | Can be concurrent with other DML operations |
| Transaction Safety | Generally safe within transactions | Requires careful management within transactions |
| Typical Use Cases | Setting up database schema, data definition | Application-level data manipulation |
