Interview Questions

Indupriya S. - "This was during a Production VM Migration and the the DB crashed.We had to rollback the migration and after a 22 hour migration window present to the customer. At that point, I did not have answers to the WHY very clearly but had to present to the customer. I walked them through the situation and what had happened when the customer responded that they knew what happened but would like to know the why if we are asking for another migration window. I had to walk out of the meeting but on the hind"See full answer

Alexander S. - "By ROMI/CAC and revenue"See full answer

Sai R. - "def countuniqueoutfits(totalpants: int, uniquepants: int, totalshirts: int, uniqueshirts: int, totalhats: int, uniquehats: int) -> int: """ Number of unique outfits can simply be defined by (uniquepantschoose1uniqueshirtschoose1uniquehatschoose_1) (uniquepantschoose1*uniqueshirtschoose1) # Not wearing a hat nchoosek is n """ res = (uniquepants*uniqueshirtsuniquehats) + (uniquepantsunique_shirts) return res print(countuniqueoutfits(2, 1, 1, 1, 3, 2))"See full answer

Exponent - "This is one of the core behavioral questions that you should expect to cover in any interview. In particular, it asks you to justify why you want to work at a specific company that you've applied for. There's no right answer for this, however we do recommend you list at least three distinct reasons. Here's an example of what you might say: > Great question! There's so many reasons, but I'll keep it to the three biggest so that I don't just go on and on. Those reasons are:Building an impactful pr"See full answer

Archna M. - "Caching is a strategy to have the frequently accessed data in the memory to reduce the latency. whenever a client request the data from server, it is first accessed into cache and if not available then it is getting fetched from the storage and stored into cache. As cache is having limited memory, so amount of data can be stored in cache is less. Data will be flushed out from cache based on a criteria which is termed as caching strategy. There could be different mechanisms under which a data can"See full answer

Sean L. - " import pandas as pd from datetime import datetime def findfastestlike(log: pd.DataFrame) -> pd.DataFrame: log=log.sortvalues(['userid','timestamp']) #get the prev event, time by user log['prevevent'] = log.groupby('userid')['event'].shift(1) log['prevtimestamp'] = log.groupby('userid')['timestamp'].shift(1) True only on rows where the previous event was a login and the current event is a like log['loginlike'] = (log['prevevent'] == 'log"See full answer