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    <p>Well, looks like an awful lot of data, with a perhaps prohibitive cost to store all frequencies. <strong>When the amount of data is so large</strong> that we cannot hope to store it all, we enter the domain of <strong>data stream algorithms</strong>.</p> <p>Useful book in this area: <a href="http://books.google.com/books?id=415loiMd_c0C&amp;lpg=PP1&amp;dq=Data%20Streams:%20Algorithms%20and%20Application&amp;hl=el&amp;pg=PP1#v=onepage&amp;q=Data%20Streams%3A%20Algorithms%20and%20Application&amp;f=false" rel="noreferrer">Muthukrishnan - "Data Streams: Algorithms and Applications"</a></p> <p>Closely related reference to the problem at hand which I picked from the above: <a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.19.8594&amp;rep=rep1&amp;type=pdf" rel="noreferrer">Manku, Motwani - "Approximate Frequency Counts over Data Streams" [pdf]</a></p> <p>By the way, Motwani, of Stanford, (edit) was an author of the very important <a href="http://rads.stackoverflow.com/amzn/click/0521474655" rel="noreferrer">"Randomized Algorithms"</a> book. <strike><strong>The 11th chapter of this book deals with this problem</strong></strike>. <strong>Edit:</strong> Sorry, bad reference, that particular chapter is on a different problem. After checking, I instead recommend <a href="http://books.google.com/books?id=415loiMd_c0C&amp;lpg=PP1&amp;dq=Data%20Streams%3A%20Algorithms%20and%20Application&amp;hl=el&amp;pg=PA33#v=onepage&amp;q&amp;f=false" rel="noreferrer">section 5.1.2 of <em>Muthukrishnan's</em> book</a>, available online.</p> <p>Heh, nice interview question. </p>
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    1. USDimitris Andreou
    1. USDimitris Andreou
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      1. VTUpMod
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    1. CO+1 Very interesting stuff, there should be a way on sites to tag "to read" stuff. Thanks for sharing.
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      1. USRamadheer Singh
    2. CO@Gollum: I have a to-read folder in my bookmarks; you could just do that. I know those links are being added to mine :)
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      1. USCam
    3. CO+1. Streaming algorithms is exactly the topic here, and Muthu's book (the only book written so far, AFAIK) is great.
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      1. USShreevatsaR
 

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