Age of Programming Languagesπ¨π»βπ»
π¦ Swift (10 years old) (2014)
π Kotlin (12 years old) (2011)
π¦ Rust (13 years old) (2010)
πΉ Go (14 years old) (2009)
π· TypeScript (11 years old) (2012)
πΈ C# (23 years old) (2000)
π Ruby (28 years old) (1995)
β Java (28 years old) (1995)
π JavaScript (28 years old) (1995)
π PHP (29 years old) (1994)
π Python (33 years old) (1991)
πͺ Perl (36 years old) (1987)
π C++ (38 years old) (1985)
π± Objective-C (39 years old) (1984)
π Prolog (51 years old) (1972)
π£οΈ Smalltalk (51 years old) (1972)
π₯οΈ C (51 years old) (1972)
π Pascal (53 years old) (1970)
π BASIC (59 years old) (1964)
πΌ COBOL (64 years old) (1959)
π€ Lisp (65 years old) (1958)
π Fortran (66 years old) (1957)
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π¦ Swift (10 years old) (2014)
π Kotlin (12 years old) (2011)
π¦ Rust (13 years old) (2010)
πΉ Go (14 years old) (2009)
π· TypeScript (11 years old) (2012)
πΈ C# (23 years old) (2000)
π Ruby (28 years old) (1995)
β Java (28 years old) (1995)
π JavaScript (28 years old) (1995)
π PHP (29 years old) (1994)
π Python (33 years old) (1991)
πͺ Perl (36 years old) (1987)
π C++ (38 years old) (1985)
π± Objective-C (39 years old) (1984)
π Prolog (51 years old) (1972)
π£οΈ Smalltalk (51 years old) (1972)
π₯οΈ C (51 years old) (1972)
π Pascal (53 years old) (1970)
π BASIC (59 years old) (1964)
πΌ COBOL (64 years old) (1959)
π€ Lisp (65 years old) (1958)
π Fortran (66 years old) (1957)
Join for more
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Sign2tech
Welcome to Sign2Tech! π
Stay updated with the latest in tech π₯οΈ, free and genuine resources π, free course alerts, internships, and job opportunities. Perfect for students and tech enthusiast looking to grow in the tech world! β‘ Join us and stay ahead!
Stay updated with the latest in tech π₯οΈ, free and genuine resources π, free course alerts, internships, and job opportunities. Perfect for students and tech enthusiast looking to grow in the tech world! β‘ Join us and stay ahead!
β€1
SQL Essentials for Quick Revision
π SELECT
Retrieve data from one or more tables.
π― WHERE Clause
Filter records based on specific conditions.
π ORDER BY
Sort query results in ascending (ASC) or descending (DESC) order.
π Aggregation Functions
MIN, MAX, AVG, COUNT: Summarize data.
Window Functions: Perform calculations across a dataset without grouping rows.
π GROUP BY
Group data based on one or more columns and apply aggregate functions.
π JOINS
INNER JOIN: Fetch matching rows from both tables.
LEFT JOIN: All rows from the left table and matching rows from the right.
RIGHT JOIN: All rows from the right table and matching rows from the left.
FULL JOIN: Combine rows when there is a match in either table.
SELF JOIN: Join a table with itself.
𧩠Common Table Expressions (CTE)
Simplify complex queries with temporary result sets.
Quick SQL Revision Notes π
Master these concepts for interviews and projects!
Join for more
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π SELECT
Retrieve data from one or more tables.
π― WHERE Clause
Filter records based on specific conditions.
π ORDER BY
Sort query results in ascending (ASC) or descending (DESC) order.
π Aggregation Functions
MIN, MAX, AVG, COUNT: Summarize data.
Window Functions: Perform calculations across a dataset without grouping rows.
π GROUP BY
Group data based on one or more columns and apply aggregate functions.
π JOINS
INNER JOIN: Fetch matching rows from both tables.
LEFT JOIN: All rows from the left table and matching rows from the right.
RIGHT JOIN: All rows from the right table and matching rows from the left.
FULL JOIN: Combine rows when there is a match in either table.
SELF JOIN: Join a table with itself.
𧩠Common Table Expressions (CTE)
Simplify complex queries with temporary result sets.
Quick SQL Revision Notes π
Master these concepts for interviews and projects!
Join for more
https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
https://telegram.me/sign2tech
Everyone's talking about #ChatGPT. But 90% of you are missing out on the AI revolution. Here are the top AI tools you NEED to know about.
1. Krisp: Krisp's AI removes background voices, noises, and echo from your calls, giving you peace of call
Link: https://krisp.ai/
2. Beatoven: Create unique royalty-free music that elevates your story
Link: https://www.beatoven.ai/
3. Cleanvoice: Automatically edit your podcast episodes
Link: https://cleanvoice.ai/
4. Podcastle: Studio quality recording, right from your computer
Link: https://podcastle.ai/
5. Flair: Design branded content in a flash
Link: https://flair.ai/
6. Illustroke: Create killer vector images from text prompts
Link: https://illustroke.com/
7. Patterned: Generate the exact patterns you need for and design
Link: https://www.patterned.ai/
8. Stockimg: Generate the perfect stock photo you need, every time
Link: https://stockimg.ai/
9. Copy: AI Generated copy, that actually increases conversion
Link:https://www.copy.ai/
10. CopyMonkey: Create Amazon listings in seconds
Link: http://copymonkey.ai/
11. Ocoya: Create and schedule social media content 10x faster
Link: https://www.ocoya.com/
12. Unbounce Smart Copy: Write high-performing cold emails at scale
Link: https://unbounce.com/
13. Vidyo: Make short-form vids from long-form content in just a few clicks
Link: https://vidyo.ai/
14. Maverick: Generate personalized videos at scale
Link:https://lnkd.in/dmrkz_ah
15. Quickchat: AI chatbots that automate customer service charts
Link: https://www.quickchat.ai/
16. Puzzle: Build an AI-powered knowledge base for your team and customers
Link: https://www.puzzlelabs.ai/
17. Soundraw: Stop searching for the song you need. Create it.
Link: https://soundraw.io/
18. Cleanup: Remove any wanted object, defect, people, or text from your pictures in seconds
Link: https://cleanup.pictures/
19. Resumeworded: Improve your resume and LinkedIn profile
Link: https://lnkd.in/d9EurcnX
20. Looka: Design your own beautiful brand
Link: https://looka.com/
21. theresanaiforthat: Comprehensive database of AIs available for every task
Link: https://lnkd.in/dKhqaaF3
22. Synthesia: Create AI videos by simply typing in text.
Link: https://www.synthesia.io/
23. descript: New way to make video and podcasts
Link: https://lnkd.in/d_Kdj35E
24. Otter: Capture and share insights from your meetings
Link: https://otter.ai/
25. Inkforall: AI content (Generation, Optimization, Performance)
Link: https://inkforall.com/
26. Thundercontent: Generate Content with AI
Link: https://lnkd.in/djFxMZsZ
Join for More
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1. Krisp: Krisp's AI removes background voices, noises, and echo from your calls, giving you peace of call
Link: https://krisp.ai/
2. Beatoven: Create unique royalty-free music that elevates your story
Link: https://www.beatoven.ai/
3. Cleanvoice: Automatically edit your podcast episodes
Link: https://cleanvoice.ai/
4. Podcastle: Studio quality recording, right from your computer
Link: https://podcastle.ai/
5. Flair: Design branded content in a flash
Link: https://flair.ai/
6. Illustroke: Create killer vector images from text prompts
Link: https://illustroke.com/
7. Patterned: Generate the exact patterns you need for and design
Link: https://www.patterned.ai/
8. Stockimg: Generate the perfect stock photo you need, every time
Link: https://stockimg.ai/
9. Copy: AI Generated copy, that actually increases conversion
Link:https://www.copy.ai/
10. CopyMonkey: Create Amazon listings in seconds
Link: http://copymonkey.ai/
11. Ocoya: Create and schedule social media content 10x faster
Link: https://www.ocoya.com/
12. Unbounce Smart Copy: Write high-performing cold emails at scale
Link: https://unbounce.com/
13. Vidyo: Make short-form vids from long-form content in just a few clicks
Link: https://vidyo.ai/
14. Maverick: Generate personalized videos at scale
Link:https://lnkd.in/dmrkz_ah
15. Quickchat: AI chatbots that automate customer service charts
Link: https://www.quickchat.ai/
16. Puzzle: Build an AI-powered knowledge base for your team and customers
Link: https://www.puzzlelabs.ai/
17. Soundraw: Stop searching for the song you need. Create it.
Link: https://soundraw.io/
18. Cleanup: Remove any wanted object, defect, people, or text from your pictures in seconds
Link: https://cleanup.pictures/
19. Resumeworded: Improve your resume and LinkedIn profile
Link: https://lnkd.in/d9EurcnX
20. Looka: Design your own beautiful brand
Link: https://looka.com/
21. theresanaiforthat: Comprehensive database of AIs available for every task
Link: https://lnkd.in/dKhqaaF3
22. Synthesia: Create AI videos by simply typing in text.
Link: https://www.synthesia.io/
23. descript: New way to make video and podcasts
Link: https://lnkd.in/d_Kdj35E
24. Otter: Capture and share insights from your meetings
Link: https://otter.ai/
25. Inkforall: AI content (Generation, Optimization, Performance)
Link: https://inkforall.com/
26. Thundercontent: Generate Content with AI
Link: https://lnkd.in/djFxMZsZ
Join for More
https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
https://telegram.me/sign2tech
Krisp
Voice AI for Meetings: Noise Cancellation & AI Note Taker | Krisp
Krisp cancels background noise, records, transcribes, and summarizes meetings and calls.
β€2π1
Excel vs SQL vs Python (pandas):
1οΈβ£ Filtering Data
β³ Excel: =FILTER(A2:D100, B2:B100>50) (Excel 365 users)
β³ SQL: SELECT * FROM table WHERE column > 50;
β³ Python: df_filtered = df[df['column'] > 50]
2οΈβ£ Sorting Data
β³ Excel: Data β Sort (or =SORT(A2:A100, 1, TRUE))
β³ SQL: SELECT * FROM table ORDER BY column ASC;
β³ Python: df_sorted = df.sort_values(by="column")
3οΈβ£ Counting Rows
β³ Excel: =COUNTA(A:A)
β³ SQL: SELECT COUNT(*) FROM table;
β³ Python: row_count = len(df)
4οΈβ£ Removing Duplicates
β³ Excel: Data β Remove Duplicates
β³ SQL: SELECT DISTINCT * FROM table;
β³ Python: df_unique = df.drop_duplicates()
5οΈβ£ Joining Tables
β³ Excel: Power Query β Merge Queries (or VLOOKUP/XLOOKUP)
β³ SQL: SELECT * FROM table1 JOIN table2 ON table1.id = table2.id;
β³ Python: df_merged = pd.merge(df1, df2, on="id")
6οΈβ£ Ranking Data
β³ Excel: =RANK.EQ(A2, $A$2:$A$100)
β³ SQL: SELECT column, RANK() OVER (ORDER BY column DESC) AS rank FROM table;
β³ Python: df["rank"] = df["column"].rank(method="min", ascending=False)
7οΈβ£ Moving Average Calculation
β³ Excel: =AVERAGE(B2:B4) (manually for rolling window)
β³ SQL: SELECT date, AVG(value) OVER (ORDER BY date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS moving_avg FROM table;
β³ Python: df["moving_avg"] = df["value"].rolling(window=3).mean()
8οΈβ£ Running Total
β³ Excel: =SUM($B$2:B2) (drag down)
β³ SQL: SELECT date, SUM(value) OVER (ORDER BY date) AS running_total FROM table;
β³ Python: df["running_total"] = df["value"].cumsum()
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https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
1οΈβ£ Filtering Data
β³ Excel: =FILTER(A2:D100, B2:B100>50) (Excel 365 users)
β³ SQL: SELECT * FROM table WHERE column > 50;
β³ Python: df_filtered = df[df['column'] > 50]
2οΈβ£ Sorting Data
β³ Excel: Data β Sort (or =SORT(A2:A100, 1, TRUE))
β³ SQL: SELECT * FROM table ORDER BY column ASC;
β³ Python: df_sorted = df.sort_values(by="column")
3οΈβ£ Counting Rows
β³ Excel: =COUNTA(A:A)
β³ SQL: SELECT COUNT(*) FROM table;
β³ Python: row_count = len(df)
4οΈβ£ Removing Duplicates
β³ Excel: Data β Remove Duplicates
β³ SQL: SELECT DISTINCT * FROM table;
β³ Python: df_unique = df.drop_duplicates()
5οΈβ£ Joining Tables
β³ Excel: Power Query β Merge Queries (or VLOOKUP/XLOOKUP)
β³ SQL: SELECT * FROM table1 JOIN table2 ON table1.id = table2.id;
β³ Python: df_merged = pd.merge(df1, df2, on="id")
6οΈβ£ Ranking Data
β³ Excel: =RANK.EQ(A2, $A$2:$A$100)
β³ SQL: SELECT column, RANK() OVER (ORDER BY column DESC) AS rank FROM table;
β³ Python: df["rank"] = df["column"].rank(method="min", ascending=False)
7οΈβ£ Moving Average Calculation
β³ Excel: =AVERAGE(B2:B4) (manually for rolling window)
β³ SQL: SELECT date, AVG(value) OVER (ORDER BY date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS moving_avg FROM table;
β³ Python: df["moving_avg"] = df["value"].rolling(window=3).mean()
8οΈβ£ Running Total
β³ Excel: =SUM($B$2:B2) (drag down)
β³ SQL: SELECT date, SUM(value) OVER (ORDER BY date) AS running_total FROM table;
β³ Python: df["running_total"] = df["value"].cumsum()
Join for more
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https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
β€1
π Key Python Libraries for Data Science:
Numpy: Core for numerical operations and array handling.
SciPy: Complements Numpy with scientific computing features like optimization.
Pandas: Crucial for data manipulation, offering powerful DataFrames.
Matplotlib: Versatile plotting library for creating various visualizations.
Keras: High-level neural networks API for quick deep learning prototyping.
TensorFlow: Popular open-source ML framework for building and training models.
Scikit-learn: Efficient tools for data mining and statistical modeling.
Seaborn: Enhances data visualization with appealing statistical graphics.
Statsmodels: Focuses on estimating and testing statistical models.
NLTK: Library for working with human language data.
These libraries empower data scientists across tasks, from preprocessing to advanced machine learning.
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Numpy: Core for numerical operations and array handling.
SciPy: Complements Numpy with scientific computing features like optimization.
Pandas: Crucial for data manipulation, offering powerful DataFrames.
Matplotlib: Versatile plotting library for creating various visualizations.
Keras: High-level neural networks API for quick deep learning prototyping.
TensorFlow: Popular open-source ML framework for building and training models.
Scikit-learn: Efficient tools for data mining and statistical modeling.
Seaborn: Enhances data visualization with appealing statistical graphics.
Statsmodels: Focuses on estimating and testing statistical models.
NLTK: Library for working with human language data.
These libraries empower data scientists across tasks, from preprocessing to advanced machine learning.
Join for More
https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
https://telegram.me/sign2tech
π3
π₯Different Tools and their use cases
1. Selenium: π Automation testing that scales effortlessly.
2. Postman: π Simplify your API testing journey.
3. Appium: π± Master mobile app testing like a pro.
4. JIRA: π Track bugs & collaborate with ease.
5. JMeter: β‘οΈ Unleash the power of performance testing.
6. TestRail: π§Ύ Organize and manage your test cases seamlessly.
7. Cypress: π΅οΈββοΈ Take UI automation to the next level with modern tools.
8. SoapUI: π Comprehensive API testing and service virtualization.
9. Katalon Studio: π A versatile web, API, and mobile testing tool.
10. QTest: π A reliable tool for test management and execution.
11. BrowserStack: π Test across multiple browsers and devices.
12. TestComplete: π€ Build reliable automated UI tests quickly.
13. Robot Framework: π Open-source automation for everyone.
14. LoadRunner: π Performance testing for heavy loads and stress tests.
15. Bugzilla: π Lightweight yet powerful bug tracking tool.
16. Ranorex: π― User-friendly desktop, web, and mobile application automation.
17. Cucumber: π₯ Simplify behavior-driven testing (BDD).
18. TestLink: π Manage test cases and requirements effectively.
19. Zephyr: π Integrate testing into your Agile workflow seamlessly.
20. Charles Proxy: π΅οΈ Debug and monitor HTTP/HTTPS traffic effortlessly.
1. Selenium: π Automation testing that scales effortlessly.
2. Postman: π Simplify your API testing journey.
3. Appium: π± Master mobile app testing like a pro.
4. JIRA: π Track bugs & collaborate with ease.
5. JMeter: β‘οΈ Unleash the power of performance testing.
6. TestRail: π§Ύ Organize and manage your test cases seamlessly.
7. Cypress: π΅οΈββοΈ Take UI automation to the next level with modern tools.
8. SoapUI: π Comprehensive API testing and service virtualization.
9. Katalon Studio: π A versatile web, API, and mobile testing tool.
10. QTest: π A reliable tool for test management and execution.
11. BrowserStack: π Test across multiple browsers and devices.
12. TestComplete: π€ Build reliable automated UI tests quickly.
13. Robot Framework: π Open-source automation for everyone.
14. LoadRunner: π Performance testing for heavy loads and stress tests.
15. Bugzilla: π Lightweight yet powerful bug tracking tool.
16. Ranorex: π― User-friendly desktop, web, and mobile application automation.
17. Cucumber: π₯ Simplify behavior-driven testing (BDD).
18. TestLink: π Manage test cases and requirements effectively.
19. Zephyr: π Integrate testing into your Agile workflow seamlessly.
20. Charles Proxy: π΅οΈ Debug and monitor HTTP/HTTPS traffic effortlessly.
β€1
95% of the companies ask the same SQL questions π±
Check the questions list below π»
1.) Explain order of execution of SQL.
2.) What is difference between where and having?
3.) What is the use of group by?
4.) Explain all types of joins in SQL?
5.) What are triggers in SQL?
6.) What is stored procedure in SQL
7.) Explain all types of window functions?
(Mainly rank, row_num, dense_rank, lead & lag)
8.) What is difference between Delete and Truncate?
9.) What is difference between DML, DDL and DCL?
10.) What are aggregate function and when do we use them? explain with few example.
11.) Which is faster between CTE and Subquery?
12.) What are constraints and types of Constraints?
13.) Types of Keys?
14.) Different types of Operators ?
15.) Difference between Group By and Where?
16.) What are Views?
17.) What are different types of constraints?
18.) What is difference between varchar and nvarchar?
19.) Similar for char and nchar?
20.) What are index and their types?
21.) What is an index? Explain its different types.
22.) List the different types of relationships in SQL.
23.) Differentiate between UNION and UNION ALL.
24.) How many types of clauses in SQL?
25.) What is the difference between UNION and UNION ALL in SQL?
26.) What are the various types of relationships in SQL?
27.) Difference between Primary Key and Secondary Key?
28.) What is the difference between where and having?
29.) Find the second highest salary of an employee?
30.) Write retention query in SQL?
31.) Write year-on-year growth in SQL?
32.) Write a query for cumulative sum in SQL?
33.) Difference between Function and Store procedure ?
34.) Do we use variable in views?
35.) What are the limitations of views?
Follow our Communityβ€οΈπ»
https://telegram.me/sign2tech
https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
Check the questions list below π»
1.) Explain order of execution of SQL.
2.) What is difference between where and having?
3.) What is the use of group by?
4.) Explain all types of joins in SQL?
5.) What are triggers in SQL?
6.) What is stored procedure in SQL
7.) Explain all types of window functions?
(Mainly rank, row_num, dense_rank, lead & lag)
8.) What is difference between Delete and Truncate?
9.) What is difference between DML, DDL and DCL?
10.) What are aggregate function and when do we use them? explain with few example.
11.) Which is faster between CTE and Subquery?
12.) What are constraints and types of Constraints?
13.) Types of Keys?
14.) Different types of Operators ?
15.) Difference between Group By and Where?
16.) What are Views?
17.) What are different types of constraints?
18.) What is difference between varchar and nvarchar?
19.) Similar for char and nchar?
20.) What are index and their types?
21.) What is an index? Explain its different types.
22.) List the different types of relationships in SQL.
23.) Differentiate between UNION and UNION ALL.
24.) How many types of clauses in SQL?
25.) What is the difference between UNION and UNION ALL in SQL?
26.) What are the various types of relationships in SQL?
27.) Difference between Primary Key and Secondary Key?
28.) What is the difference between where and having?
29.) Find the second highest salary of an employee?
30.) Write retention query in SQL?
31.) Write year-on-year growth in SQL?
32.) Write a query for cumulative sum in SQL?
33.) Difference between Function and Store procedure ?
34.) Do we use variable in views?
35.) What are the limitations of views?
Follow our Communityβ€οΈπ»
https://telegram.me/sign2tech
https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
β€5π2
8 Key Data Structures That Power Modern Databases
πΉSkiplist: a common in-memory index type. Used in Redis
πΉHash index: a very common implementation of the βMapβ data structure (or βCollectionβ)
πΉSSTable: immutable on-disk βMapβ implementation
πΉLSM tree: Skiplist + SSTable. High write throughput
πΉB-tree: disk-based solution. Consistent read/write performance
πΉInverted index: used for document indexing. Used in Lucene
πΉSuffix tree: for string pattern search
πΉR-tree: multi-dimension search, such as finding the nearest neighbor
πΉSkiplist: a common in-memory index type. Used in Redis
πΉHash index: a very common implementation of the βMapβ data structure (or βCollectionβ)
πΉSSTable: immutable on-disk βMapβ implementation
πΉLSM tree: Skiplist + SSTable. High write throughput
πΉB-tree: disk-based solution. Consistent read/write performance
πΉInverted index: used for document indexing. Used in Lucene
πΉSuffix tree: for string pattern search
πΉR-tree: multi-dimension search, such as finding the nearest neighbor
β€3π2
25 Papers That Completely Transformed the Computer World.
1. Dynamo - Amazonβs Highly Available Key Value Store
2. Google File System: Insights into a highly scalable file system
3. Scaling Memcached at Facebook: A look at the complexities of Caching
4. BigTable: The design principles behind a distributed storage system
5. Borg - Large Scale Cluster Management at Google
6. Cassandra: A look at the design and architecture of a distributed NoSQL database
7. Attention Is All You Need: Into a new deep learning architecture known as the transformer
8. Kafka: Internals of the distributed messaging platform
9. FoundationDB: A look at how a distributed database
10. Amazon Aurora: To learn how Amazon provides high-availability and performance
11. Spanner: Design and architecture of Googleβs globally distributed databas
12. MapReduce: A detailed look at how MapReduce enables parallel processing of massive volumes of data
13. Shard Manager: Understanding the generic shard management framework
14. Dapper: Insights into Googleβs distributed systems tracing infrastructure
15. Flink: A detailed look at the uniο¬ed architecture of stream and batch processing
16. A Comprehensive Survey on Vector Databases
17. Zanzibar: A look at the design, implementation and deployment of a global system for managing access control lists at Google
18. Monarch: Architecture of Googleβs in-memory time series database
19. Thrift: Explore the design choices behind Facebookβs code-generation tool
20. Bitcoin: The ground-breaking introduction to the peer-to-peer electronic cash system
21. WTF - Who to Follow Service at Twitter: Twitterβs (now X) user recommendation system
22. MyRocks: LSM-Tree Database Storage Engine
23. GoTo Considered Harmful
24. Raft Consensus Algorithm: To learn about the more understandable consensus algorithm
25. Time Clocks and Ordering of Events: The extremely important paper that explains the concept of time and event ordering in a distributed system
Follow our Communityβ€οΈπ»
https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
https://telegram.me/sign2tech
1. Dynamo - Amazonβs Highly Available Key Value Store
2. Google File System: Insights into a highly scalable file system
3. Scaling Memcached at Facebook: A look at the complexities of Caching
4. BigTable: The design principles behind a distributed storage system
5. Borg - Large Scale Cluster Management at Google
6. Cassandra: A look at the design and architecture of a distributed NoSQL database
7. Attention Is All You Need: Into a new deep learning architecture known as the transformer
8. Kafka: Internals of the distributed messaging platform
9. FoundationDB: A look at how a distributed database
10. Amazon Aurora: To learn how Amazon provides high-availability and performance
11. Spanner: Design and architecture of Googleβs globally distributed databas
12. MapReduce: A detailed look at how MapReduce enables parallel processing of massive volumes of data
13. Shard Manager: Understanding the generic shard management framework
14. Dapper: Insights into Googleβs distributed systems tracing infrastructure
15. Flink: A detailed look at the uniο¬ed architecture of stream and batch processing
16. A Comprehensive Survey on Vector Databases
17. Zanzibar: A look at the design, implementation and deployment of a global system for managing access control lists at Google
18. Monarch: Architecture of Googleβs in-memory time series database
19. Thrift: Explore the design choices behind Facebookβs code-generation tool
20. Bitcoin: The ground-breaking introduction to the peer-to-peer electronic cash system
21. WTF - Who to Follow Service at Twitter: Twitterβs (now X) user recommendation system
22. MyRocks: LSM-Tree Database Storage Engine
23. GoTo Considered Harmful
24. Raft Consensus Algorithm: To learn about the more understandable consensus algorithm
25. Time Clocks and Ordering of Events: The extremely important paper that explains the concept of time and event ordering in a distributed system
Follow our Communityβ€οΈπ»
https://whatsapp.com/channel/0029Va9pSbzBlHpU1fu6ff1Q
https://telegram.me/sign2tech
π2β€1
Placement toh ho kar rahegi!
Padhai nahi rukni chahiye!
Keep studying, stay focused!
Your hard work will pay off!
Reactionππ
Padhai nahi rukni chahiye!
Keep studying, stay focused!
Your hard work will pay off!
Reactionππ
β€18β€βπ₯3
GET, POST, PUT... Common HTTP βverbsβ in one figure.
1. HTTP GET
This retrieves a resource from the server. It is idempotent. Multiple identical requests return the same result.
2. HTTP PUT
This updates or Creates a resource. It is idempotent. Multiple identical requests will update the same resource.
3. HTTP POST
This is used to create new resources. It is not idempotent, making two identical POST will duplicate the resource creation.
4. HTTP DELETE
This is used to delete a resource. It is idempotent. Multiple identical requests will delete the same resource.
5. HTTP PATCH
The PATCH method applies partial modifications to a resource.
6. HTTP HEAD
The HEAD method asks for a response identical to a GET request but without the response body.
7. HTTP CONNECT
The CONNECT method establishes a tunnel to the server identified by the target resource.
8. HTTP OPTIONS
This describes the communication options for the target resource.
9. HTTP TRACE
This performs a message loop-back test along the path to the target resource.
1. HTTP GET
This retrieves a resource from the server. It is idempotent. Multiple identical requests return the same result.
2. HTTP PUT
This updates or Creates a resource. It is idempotent. Multiple identical requests will update the same resource.
3. HTTP POST
This is used to create new resources. It is not idempotent, making two identical POST will duplicate the resource creation.
4. HTTP DELETE
This is used to delete a resource. It is idempotent. Multiple identical requests will delete the same resource.
5. HTTP PATCH
The PATCH method applies partial modifications to a resource.
6. HTTP HEAD
The HEAD method asks for a response identical to a GET request but without the response body.
7. HTTP CONNECT
The CONNECT method establishes a tunnel to the server identified by the target resource.
8. HTTP OPTIONS
This describes the communication options for the target resource.
9. HTTP TRACE
This performs a message loop-back test along the path to the target resource.
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Top 10 Github Repositories For Web Developer
1. Web Developer-Roadmap : https://github.com/kamranahmedse/developer-roadmap
2. 30-Seconds-Of-Code : https://github.com/30-seconds/30-seconds-of-code
3. Awesome-Cheatsheets : https://github.com/LeCoupa/awesome-cheatsheets
4. CSS-Protips : https://github.com/AllThingsSmitty/css-protips
5. 33-JS-Concepts : https://github.com/leonardomso/33-js-concepts
6. You-Dont-Know-JS : https://github.com/getify/You-Dont-Know-JS/tree/2nd-ed
7. Front-End-Checklist : https://github.com/thedaviddias/Front-End-Checklist
8. Javascript-Questions : https://github.com/lydiahallie/javascript-questions
9. Clean-Code-Javascript : https://github.com/ryanmcdermott/clean-code-javascript
Follow our Communityβ€οΈπ»
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1. Web Developer-Roadmap : https://github.com/kamranahmedse/developer-roadmap
2. 30-Seconds-Of-Code : https://github.com/30-seconds/30-seconds-of-code
3. Awesome-Cheatsheets : https://github.com/LeCoupa/awesome-cheatsheets
4. CSS-Protips : https://github.com/AllThingsSmitty/css-protips
5. 33-JS-Concepts : https://github.com/leonardomso/33-js-concepts
6. You-Dont-Know-JS : https://github.com/getify/You-Dont-Know-JS/tree/2nd-ed
7. Front-End-Checklist : https://github.com/thedaviddias/Front-End-Checklist
8. Javascript-Questions : https://github.com/lydiahallie/javascript-questions
9. Clean-Code-Javascript : https://github.com/ryanmcdermott/clean-code-javascript
Follow our Communityβ€οΈπ»
https://telegram.me/sign2tech
GitHub
GitHub - kamranahmedse/developer-roadmap: Interactive roadmaps, guides and other educational content to help developers grow inβ¦
Interactive roadmaps, guides and other educational content to help developers grow in their careers. - kamranahmedse/developer-roadmap
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Forwarded from Tech Cubes
The Temporal Dead Zone (TDZ) in JavaScript refers to a specific period within a scope where variables declared with
let or const exist but cannot be accessed or used until their declaration and initialization are reached in the code.β€1
image_2026-02-15_01-01-34.png
11.4 KB
A message queue is an asynchronous communication component that stores messages sent by producers until consumers are ready to process them, enabling decoupled, reliable, and scalable system architecture. It acts as a buffer (shock absorber) allowing fast producers and slower consumers to operate at their own pace.
Producer (Sender): Applications or services that create and send data/messages to the queue.
Consumer (Receiver): Applications or services that retrieve and process messages from the queue.
Message Queue (Broker): A, durable, asynchronous buffer that holds messages. In this pattern, a message is typically consumed only once and removed after acknowledgment.
Topic (Pub/Sub Model): Unlike a point-to-point queue, a Topic allows a message to be published once and received by multiple consumers (subscribers) simultaneously.
Core Concepts:
Producer (Sender): Applications or services that create and send data/messages to the queue.
Consumer (Receiver): Applications or services that retrieve and process messages from the queue.
Message Queue (Broker): A, durable, asynchronous buffer that holds messages. In this pattern, a message is typically consumed only once and removed after acknowledgment.
Topic (Pub/Sub Model): Unlike a point-to-point queue, a Topic allows a message to be published once and received by multiple consumers (subscribers) simultaneously.