Spark Memory Management 

This is very helpful video to start with spark memory management. Thanks for posting

Great explanation on Spark Memory Management.

Thanks for your contributing your knowledge and experience to IT society.

This is gold .

Hi Shreya, thanks for the video, all viewers be safe

1 second ago Hi Shreya, Thanks for the video, wonderful presentation, and knowledge sharing. you are doing a great job and continue. Also, I like you to do practical experiments like spark in the future for practicing purpose.

Very insightful!! Great job Shreya!

Hi Shreya, Very clear and precise info. Hoping for more on spark performance issues.

This is what I am looking for Thankyou 🙏

Awesome and concepts are very nicely guided

Well explained. Please make videos on performance tuning in Spark

Just awesome tutorial.

Clear and lucid presentation mam 🙂

Nice explanation 👌👍👏

Good job!

Very nice

nice explanation mam

Its just awesome

Thanks for this. Could you explain the meaning of propagating internal data between cluster, which is done in storgae memory, is it not same as shuffling, which is taken xare in execution memory

Good video but noise in background

around approx 07:20 - 08:00 mark, isnt the spark.memory.fraction and not spark.memory.storagefraction value that defines the amount of memory available for Unified memory(Execution+Storage). Out of that default spark.memory.storagefraction defines how much of that memory can be blocked for Storage so that amount of data doesnt get evicted?

plz cover encoders in spark

Can you please share information on calculating num executors, memory core, memory drivers

what is Kyro. you used this jargon so asking? how broadcasting works in detail is another question?

Can you make videos with practical example and can we use kryoserrialser in pyspark.

Why there is no need of GC in off heap, how does that do clean up.

If you could explain user memory in little more details.