@SumitM_X Because delete usually doesn’t remove the file’s data immediately.
The filesystem mainly removes the file’s directory entry and marks its disk space as available.
Copying is different: it has to read the actual bytes and write them somewhere else.
₹2,400 less salary from September? Here's why 👇
The EPFO raised the PF wage ceiling from ₹15,000 to ₹25,000 (effective 17 Sept 2026).
📌PF rate is still 12%
📌Employee share: ₹1,800 → ₹3,000
📌Employer share: ₹1,800 → ₹3,000
📌If your company keeps CTC fixed, in-hand drops by about ₹2,400
September only has 14 days of impact, so the full effect shows from October.
This isn't money lost. It goes into your PF account and builds your retirement savings.
Check your payslip and ask HR if anything looks off.
#PF #EPFO #PFWageCeiling #Salary #PersonalFinance #India
A running program actually lives in RAM.
The executable is stored on disk, but when you run it:
Storage -> RAM -> CPU
The OS loads the program’s required code and data into RAM. The CPU executes instructions from RAM.
So:
Storage = where the program is kept
RAM = where the running program lives
CPU = where instructions are executed
C. SSE
For a live dashboard where updates flow server->client, SSE is usually more memory-efficient than WebSockets because you don't need a full bidirectional connection.
But the bigger point: 80,000 persistent connections still consume resources. With proper connection handling, SSE can be a good fit when clients only need server-side updates.
Container: shares the host OS kernel and isolates the application + dependencies.
VM: emulates a complete machine and runs its own OS kernel.
So:
Container → lighter, faster startup, less isolation
VM → heavier, slower startup, stronger isolation
That’s the core difference.
It’s searching an index, not the 50,000 emails directly.
When emails arrive, Gmail builds indexes for things like:
sender
recipient
subject
words in the email
dates
labels
When you search, it looks up your word in those indexes and gets the matching email IDs.
So the flow is roughly:
Email → build index → search index → fetch matching emails
That’s why searching 50,000 emails can still be fast.