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Ask HN: Can engineers from Google or Facebook solve whiteboard questions easily?

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Re: Ask HN: Can engineers from Google or Facebook solve whiteboard questions easily?

#51
post #37

Earlier quoted context omitted.

i don't understand why people do this. you're raging against a machine. do you think you're going to change this person's mind on how effective whiteboard questions are?

No, but it helps to highlight the pointlessness of these methods in hiring people for a real world project. I keep hearing, how startups use multiple online judge algorithm screening sessions, to filter and hire the best. But the candidates just can't do any real world work, because they are busy practicing interview questions for the next job they seek while they are in their current jobs. In other words you are opt…

>No, but it helps to highlight the pointlessness of these methods in hiring people for a real world project.

for whom? who is the intended audience of your response?

Re: Ask HN: Can engineers from Google or Facebook solve whiteboard questions easily?

#54
post #49
post #39

Earlier quoted context omitted.

Even after choosing a technology (like Hadoop), there's a lot of difference between the best and the worst algorithm to solve a problem. For example, the reduce phase of MapReduce is pretty much "apply the algorithm you want on this List", and that's where knowing good list algorithms (for example) shine.

Sorry, in almost all cases its really choosing over several ways of Joining the data, not writing SELECT *, not writing cross joins and learning SQL well. Which why I ask again. Please list your problem which is so novel it requires you to invent a novel algorithm. Please note statistics is a science that has existed for centuries now. Unless you are in a university, its highly unlikely you have a problem that will n…

I don't understand your point.

It seems to me you mix statisticals approaches and algorithms, meaning you completely ignore the fact that code runs on computers, and that computers have mechanical characteristics, making two implementations of the same statistical approach wildly different in performance.

I used to work at a company where some guys spent literally weeks inventing a fast way to do a dot product over huge vectors. Which doesn't mean they invented the concept of dot product.

Re: Ask HN: Can engineers from Google or Facebook solve whiteboard questions easily?

#56
post #28

Earlier quoted context omitted.

Those look like software design skills. Also the type of systems you describes use something like Hadoop, and use things like Hive and Pig on top of it. Once you get the data out you use Python or R. And you generally use a standard library to work with. That really SQL + general programming. What new problems are you working on that require you to invent novel algorithmic techniques?

Even with Hadoop, there's still algorithmic decisions that you have to make like whether to choose a stripes or pairs strategy when synchronization is needed[1], or choosing appropriate data structures for real time queries [2]. Sure something like Hive and Pig might work well enough for certain queries, but for some of the more complex queries where writing bare MapReduce or Spark is needed then these data structure…

I noticed that talk comes from a University. I understand thats a totally different domain of work.

Secondly, you are not inventing any algorithm there. You are only using algorithm invented by others.

Thirdly, you are only deciding what solution works better.

Lastly, in an interview you have to invent this algorithm in 45 minutes.

None of this involves you to invent a new algorithm. At least not in 45 minutes. I doubt if the person giving that talk himself did it so quickly.

Re: Ask HN: Can engineers from Google or Facebook solve whiteboard questions easily?

#57
post #36

I work at Google and no it's not easy for us either. I've heard many of my coworkers joke that if they went through the interview process again they'd probably fail. That said I see two kinds of interviewers. One kind (the good kind) takes a medium difficulty question and uses it to explore the candidate's coding, algorithms, communication, and problem solving skills. The other kind has a super hard question with a s…

> I've heard many of my coworkers joke that if they went through the interview process again they'd probably fail.

I don't see how companies that claim it's hard to find talent can be OK with a system that would reject more than a small portion (Edit: fixed word sense ambiguity

Re: Ask HN: Can engineers from Google or Facebook solve whiteboard questions easily?

#58
post #41
post #36

I work at Google and no it's not easy for us either. I've heard many of my coworkers joke that if they went through the interview process again they'd probably fail. That said I see two kinds of interviewers. One kind (the good kind) takes a medium difficulty question and uses it to explore the candidate's coding, algorithms, communication, and problem solving skills. The other kind has a super hard question with a s…

I got the same response from an old friend who has worked for Google for the better part of a decade. FWIW my understanding is that the Hiring Committee tends to discard feedback from interviewers like your latter type here.

Is there any mechanism like those olympics diving competition? i.e. the highest and lowest score are discarded.

Re: Ask HN: Can engineers from Google or Facebook solve whiteboard questions easily?

#59
post #25

Earlier quoted context omitted.

> Sure you can write a for loop to iterate over a data set, but will you fall on your face when that data set is petabytes in size? I also asked a question in HN yesterday. It looks like there are more questions on data structure and algorithm for big data. However, books I read don't focus much in this area. As I haven't worked on big data before, that would also be a challenge for me.

Here's a few pointers on big data: * You obviously need more than one machine to do computation. Things become more difficult as you go from one machine to many, so learn about parallel programming tactics like MapReduce[1] and Flume[2]. * Storing stuff is also much more difficult. You'll either be working with distributed filesystems like GFS [3] or Colossus [4], NoSQL databases like bigtable [5], or SQL-like databa…

Thanks. Appreciate for the links!

Re: Ask HN: Can engineers from Google or Facebook solve whiteboard questions easily?

#60
post #10

Earlier quoted context omitted.

> algorithmic primitives from which modern algorithms are born. What is a good way to learn more about these?

I find my problem mapping methodology often leads me to remember these three books: Aho and Ullmann: Foundations of Computer Science (old but really, really, really good) Steven Skiena: Algorithm Design Manual Abelson: Structure and Interpretation of Computer Programs

After a quick search, this came up:

Foundations of Computer Science, full book: http://infolab.stanford.edu/~ullman/focs.html

Also turns out Skiena's website is a very large resource!

http://www.algorist.com/algorist.html

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