#Rad Software Development Methodology

My second most asked question is always how I learnt R     I taught myself mainly by just trial and error (I have to actually physically do something I can’t just watch videos as I don’t take it in) so I started with the very basics.   I think it’s so easy to overdo and feel like you need to know how to do everything or a lot of things at the start. Stick to simple things like understanding the R studio interface and loading packages and other basic commands     (after this most things I learnt were googling very specifically what I needed to do and adding the command to a ‘useful command’ list I have)    Next:  Following a vignette from start to finish (one that would be similar to what I would soon need) I then would go through and click on functions to look at the arguments (this tells you all the parameters for the function) and how I can change them if needed!    Finally try swirl it’s so easy to just load directly in the terminal and you learn as you go!        What’s your top tips?    I also have so many more so make sure you follow!      #phd #student #coding #rprogramming #university #tipsandtricks

Handling 1 Million RPS isn’t about code — it’s about smart architecture. 1️⃣ Traffic Distribution (Load Balancers) ➡️ Spreads incoming requests across many servers so nothing overloads. Example: 1M requests split across 200 servers = ~5K requests per server. ⸻ 2️⃣ Scale Out, Not Up (Horizontal Scaling) ➡️ Add more machines instead of making one server bigger. Example: Flash sale traffic? Instantly launch 50 new API instances. ⸻ 3️⃣ Fast Reads with Cache ➡️ Use Redis/Memcached to avoid hitting the database every time. Example: Cached user data = millions of DB calls saved daily. ⸻ 4️⃣ Edge Delivery with CDN ➡️ Static content loads from servers closest to the user. Example: Users in Delhi fetch images from a Delhi CDN node. ⸻ 5️⃣ Background Work with Queues ➡️ Heavy tasks run asynchronously so APIs respond instantly. Example: Payment succeeds now, email receipt sent in background. ⸻ 6️⃣ Split the Database (Sharding) ➡️ Divide data across multiple databases to handle scale. Example: Usernames A–M on one shard, N–Z on another. ⸻ 7️⃣ Rate Limiting ➡️ Prevent abuse and traffic spikes from taking the system down. Example: Limit clients to 100 requests/sec to block bots from killing the API. ⸻ 8️⃣ Lightweights Payloads ➡️ Smaller payloads = faster responses + less bandwidth. Example: Send only required fields instead of massive JSON blobs. Please follow for more such videos🙏 #systemdesign #softwaredevelopers #programming #tech #interview [API Design] [System Architecture] [API Scaling] [1 Million RPS] [Distributed Systems] [Load Balancing] [Database Sharding] [High Availability]

Plan A? #software #softwareengineer #ai #programming #yazılım #softwaredevelopment #softwaredeveloper

Design Rate Limitter #systemdesign #dsa #faang

Comment “Build” and I’ll send the tool. If you want to get better at building software, spend less time preparing and more time making small things that actually run. A simple project forces you to make real decisions. You have to define the data, think about what the user does first, and decide what the interface should show. Those decisions are where most of the learning happens. Once the structure is clear, the rest becomes implementation. You connect the interface to the data, test how it behaves, and adjust it when something breaks. Treat small projects as experiments. Choose one narrow problem, build the smallest version that works, and let people interact with it. Pay attention to what feels confusing or unnecessary. That feedback shows you what to simplify. Share the result in a way that makes it easy to understand. Explain the problem, show the core idea of the tool, and include a link so someone can try it immediately. When you repeat this process often, the projects become clearer, the decisions become faster, and the systems you build start to feel deliberate rather than improvised. Focus on finishing small tools, learning from them, and improving the next one. #explore #explorepage #fyp #tech #softwareengineering

Performing joins especially with large datasets will be a huge challenge in data processing. Here is the fix. 👇 1️⃣ Make a broadcast join Instead of shuffling 50TB of data across the network to find matches, you should send a copy of the small table to every single worker node. 2️⃣ Map-Side Operation This converts the operation into a local lookup. Each executor holds the full 100MB table in RAM and joins it against its local slice of the 50TB data. 3️⃣ The Memory Trap Be careful -> if that “small” table grows too big (e.g., 2GB), broadcasting it will cause Out-Of-Memory (OOM) errors on the executors and crash the application. 4️⃣ Configuration Threshold Check the spark.sql.autoBroadcastJoinThreshold. If the table is slightly larger than the default (usually 10MB), the system might default to a slow Sort-Merge join unless I increase this limit. #dataengineering #bigdata #coding 🏷️ Data Engineering, Apache Spark, Coding Interview, Tech Interview, Big Data Processing, Spark, Python

1️⃣ “R for Data Science” by Wickham et al. is widely recommended across stats forums as one of the best books to learn hands on R programming. The is available online for free at www.r4ds.hadley.nz 2️⃣ HarvardX Data Science R Basics is free to audit assumes no prior knowledge and teaches you foundational programming concepts and operations (it doesn’t get into statistical modeling yet). 3️⃣ “An Introduction to Statistical Learning with Applications in R” by James et al. can be a little bit more technical and advanced (as it actually covers statistical topics), but comes with great real-life R coding examples.The PDF of the book is available online for free at www.statlearning.com 4️⃣ www.rscreencasts.com has a long list of screencast videos by data scientist David Robinson where he shares real-world examples of live data analyses in R, including how to approach analysis, what packages and methods he uses, as well as general R tricks and tips. 5️⃣ If you prefer more interactive learning, you might enjoy swirl (swirlstats.com) that teaches you R programming interactively inside the R console, no reading books or watching courses required. ❓Any other good recs? Drop them in the comments! #rprogramming #rstudio #datascientist #womenintech #womeninstem

On Google search 👇🏼 System Design Roadmap takeUforward Thank you @gkcs__ for helping us to cover this! #engineering #softwareengineer #coding #programming #systemdesign #hld #lld #interviews #trending #coding #programming #faang #google #amazon #microsoft #striver #engineer #placements

You should probably save this post ✌️ What's your best tip??? Decided to flex some of my favorite r tips on y'all today Gotta be real though, I JUST FOUND OUT ABOUT THE REFORMAT SHORTCUT This is a game changer for my Rstudio productivity 🥲 #scicomm #rstats #rstudio #codinglife #programminglife #codingtips

#softwareimplementation follows a traditional model and the more you ‘ride the bike’ the more second nature it becomes. #projectmanagement #businessanalysis #softwaredevelopmentlifecycle #sdlc

Now it’s time to connect Frontend with backend through RestAPI’s 💥 #codes #learning #mernstack #projects #reactjs

Software Project Ideas 💡 (ft: 2025) The above projects will help you learn how to build solutions for software systems. Once you develop them, you can solve real-world problems, and people might even pay for your service. Let me know your 💭 in the 💬 below. Yours, KosDevLab #tech #software #project #ideas #2025 #by #kosdevlab