Interviewed with facebook a while ago and had a pretty weird experience.
Was asked to design a type ahead suggestion for google search. It was a product design interview , not system design.
Came up with a trie, computed via map reduce periodically over 1 hour(configurable), frontend implementation, load balancer, app servers, mq, cache and a key value db. Took the assumption that we would only be interested in popular terms for type ahead and there would be a lot of duplicates in 5 billion odd queries that Google would get everyday. Had thought about this question before and seen it on grokking the system design.
Interviewer: But google doesn't only do it for popular terms it does typeahead for all terms
Me: No it doesn't. Only the popular terms are what show up on type ahead, otherwise, it'd defeat the purpose.
Interview: I'm sure google does typeahead for all terms.
Me. So you are saying that if a single random bloke entered the term 'xyzowkdyzxc' on google, and another random bloke entered the term xyz google will show a typeahead suggestion?
Interviewer: Yes it will
Me: *completely in disbelief at this point , points out the daily query volume for google and space requirements for storing the entire trie*
Interviewer: Okay , do it for youtube. Youtube shows typeahead for all of it's videos.
Me: It doesn't, based on my experience. But I'll try to solve it anyway.
Interview: It does, I have tried it.
I just went on to add more fanout nodes to the map reduce output jobs , reduced cassandra's replication factor , added more message queue nodes etc.
Follow up: How will the system scale if map reduce job ran every minute?
I think the interview went even more downhill after that.
People of blind, how do you solve a question like this and what would you do in this sort of a situation?
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What a dumb way to get blacklisted lmfao.