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Editorial Team
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Asked: 2026-05-15T20:59:43+00:00

I’m currently preparing for an interview, and it reminded me of a question I

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I’m currently preparing for an interview, and it reminded me of a question I was once asked in a previous interview that went something like this:

“You have been asked to design some software to continuously display the top 10 search terms on Google. You are given access to a feed that provides an endless real-time stream of search terms currently being searched on Google. Describe what algorithm and data structures you would use to implement this. You are to design two variations:

(i) Display the top 10 search terms of all time (i.e. since you started reading the feed).

(ii) Display only the top 10 search terms for the past month, updated hourly.

You can use an approximation to obtain the top 10 list, but you must justify your choices.”

I bombed in this interview and still have really no idea how to implement this.

The first part asks for the 10 most frequent items in a continuously growing sub-sequence of an infinite list. I looked into selection algorithms, but couldn’t find any online versions to solve this problem.

The second part uses a finite list, but due to the large amount of data being processed, you can’t really store the whole month of search terms in memory and calculate a histogram every hour.

The problem is made more difficult by the fact that the top 10 list is being continuously updated, so somehow you need to be calculating your top 10 over a sliding window.

Any ideas?

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1 Answer

  1. Editorial Team

    Well, looks like an awful lot of data, with a perhaps prohibitive cost to store all frequencies. When the amount of data is so large that we cannot hope to store it all, we enter the domain of data stream algorithms.

    Useful book in this area:
    Muthukrishnan – “Data Streams: Algorithms and Applications”

    Closely related reference to the problem at hand which I picked from the above:
    Manku, Motwani – “Approximate Frequency Counts over Data Streams” [pdf]

    By the way, Motwani, of Stanford, (edit) was an author of the very important “Randomized Algorithms” book. The 11th chapter of this book deals with this problem. Edit: Sorry, bad reference, that particular chapter is on a different problem. After checking, I instead recommend section 5.1.2 of Muthukrishnan’s book, available online.

    Heh, nice interview question.

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