Ritesh Roushan

@knowRowan Nothing bro. being in tech it's eye opening post.

@devXritesh 🤷

@LuckyGoldx They have used Trie data structures and edge caching to serve this massive results.

..autocomplete looks up your keystrokes in a massive prefix tree stored in memory across data centers. edge servers cache the hottest prefixes, rank them by popularity/context, and return top results in milliseconds, no full web search needed. with 8.5 billion daily queries, they pre-compute and shard the index for speed.

As a developer, Have you ever wondered : You type just "how to" in Google search and it instantly shows full suggestions like "how to make money", "how to cook pasta" etc... There are 8.5+ billion searches globally every day. How is this autocomplete so fast?

@shub0414 It's trie DS and edge cache is real game in this massive result.

@devXritesh CDN maybe

@pravinemani Trie+ edge cache both

@devXritesh I assumed it was tries as well, the comments confirmed that:)

@knowRowan Correct 💯

@devXritesh Google's autocomplete runs on tries + massive caching

@shub0414 Great share subh

html ↓ css ↓ javascript ↓ git & github ↓ react ↓ node.js ↓ express ↓ mongodb ↓ rest apis ↓ authentication (jwt / oauth) ↓ typescript ↓ next.js ↓ docker ↓ ci/cd congrats you are a full-stack developer now

@0xlelouch_ Throughput is limited by partition parallelism. Adding consumers beyond partition count doesn’t help. Also check processing latency per message could be the real bottleneck.

Your Kafka consumer is processing messages very slowly. Increasing consumer count from 3 to 10 doesn't help. Why not and what's the bottleneck?

@SumitM_X I’d rebase. Keeps history clean and avoids a messy merge commit. But only if the branch isn’t shared otherwise, merge to avoid rewriting history.

Your feature branch has 50 commits. Main has moved ahead with 300 commits. What will you do: Rebase your branch or merge main into your branch?

@ChillxxLife You got this buddy and also add caching too.

@devXritesh Trie data structure 🤧 Last topic of DSA 💀🤧

@thekevinqi DS using trie + edge cache for faster lookups and result serving

@devXritesh Caching

@Itstheanurag Totally agree! Diversifying from field experts > one creator grind. Unemployed dev wisdom hits different .

See i believe if you want to learn something learn from the experts in that field. Learning about databases from ezsnippet would be stupid if Hussain nasser and arpit bhayani exist. Learning DSA from code with Harry would be stupid if kunal's videos exists. Learning rust from technical thapa would be stupid if let's get rusty exists. The point is stop working one guy, everyone on YouTube has something they are best known for. By not following them all you are hindering your progress. You are learning things from the top layer only but never from the core of it. Thanks for this matter, an unemployed dev and not the president of United States.

@Inosukeei_coder Helpful bro, keep sharing

30 tech companies with massive workforce + strong engineer pay.. - Amazon — 1,576,000 employees — SWE avg pay: ~$190k–$230k . - IBM — ~270,000 employees — SWE avg pay: ~$150k–$190k. - Microsoft — 228,000 employees — SWE avg pay: ~$220k–$250k . - Accenture — ~210,000 tech total company is far bigger — SWE avg pay: ~$120k–$170k. - Alphabet (Google) — 190,820 employees — SWE avg pay: ~$250k–$340k . - Apple — 166,000 employees — SWE avg pay: ~$230k–$280k. - Oracle — 162,000 employees — SWE avg pay: ~$180k–$230k. - Cisco — ~90,000 employees — SWE avg pay: ~$190k–$230k. - Salesforce — 76,453 employees — SWE avg pay: ~$210k–$260k . - Lenovo — 72,000 employees — SWE avg pay: ~$120k–$170k . - HP — 55,000 employees — SWE avg pay: ~$140k–$180k. - Intel — ~124,800 employees — SWE avg pay: ~$180k–$230k. - Dell — ~97,000 employees — SWE avg pay: ~$140k–$180k . - SAP — 109,973 employees — SWE avg pay: ~$160k–$210k . - Meta — ~74,000 employees — SWE avg pay: ~$280k–$380k . - Adobe — 31,360 employees — SWE avg pay: ~$210k–$260k . - NVIDIA — ~36,000 employees — SWE avg pay: ~$240k–$320k. -Uber — ~31,000 employees — SWE avg pay: ~$220k–$300k. LinkedIn — ~18,000 employees — SWE avg pay: ~$316k. - Intuit — 18,200 employees — SWE avg pay: ~$210k–$260k . - Airbnb — ~7,300 employees — SWE avg pay: ~$250k–$330k. - Atlassian — ~14,400 after recent layoffs — SWE avg pay: ~$180k–$240k . - ServiceNow — ~26,000 employees — SWE avg pay: ~$210k–$270k. - Workday — ~20,400 employees — SWE avg pay: ~$190k–$240k. - PayPal — ~27,000 employees — SWE avg pay: ~$170k–$220k. - Shopify — ~8,100 employees — SWE avg pay: ~$170k–$230k . - Expedia — 16,000 employees — SWE avg pay: ~$160k–$210k . - Block — ~12,000 employees — SWE avg pay: ~$200k–$270k. - Pinterest — ~4,200 employees — SWE avg pay: ~$220k–$300k. - Dropbox — ~2,300 employees — SWE avg pay: ~$210k–$280k.

@Inosukeei_coder In searching Trie ruling, I have also used in my work.

@devXritesh It means DSA handles main role.

@0xPrajwal_ I have prepared yesterday and yeah it's coincidence 😅

@devXritesh Bro what a coincidence 😂 I posted similar

@DINESHVERM578 Glad you liked buddy, more such stuff coming soon

@devXritesh Great share 💪

@0xPrajwal_ Using DS and caching to serve data faster. Trie + Edge Cache.

Interviewer :- If Google shows results in milliseconds, how does it search the whole internet so quickly?

@Devinbuild So it's part of claude now?

Claude after realizing OpenClaw has been dominating

@droidbuilds I have started at 18 bro

Be honest , what age did you start coding? I started at 19 😅

@nia_thinks Vibe coding changes game, just need faster development and deployment.

Before vibe coding: – 6 months to ship – $30K spent on developers – 3 pivots before launch – still not done After vibe coding: – idea on Monday – live on Friday – real users by the weekend the speed changes everything.