Spark code not running bcz of incorrect compute size

[ashraf1395]

I have a dataset having 260 billion records

I need to group by 4 columns and find out the sum on four other columns

I increased the memory to e32 for driver and workers nodes, max workers is 40

The job still is stuck in this aggregate step where I’m writing it to the disk for persisting purpose.

Any solution?

We can use serverless compute but if I want to do it the normal way what can be the optimal size of cluster or some optimisations which I can do

[Rishabh_Tiwari]

Hi @ashraf1395 ,

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