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You have a potentially very-large set of documents, which are potentially very-large, and contain text. For searching these documents, they've been pre-processed into a (very-large) table mapping words to the set of documents that contain each word. E.g. (word) : (documents (referenced by ID) containing that word) Apple: 1, 4, 5, 6, 32 Banana: 5, 6, 7, 9, 32 Cantaloupe: 1, 2, 6 ... Clients will pass in a set of words (e.g. {apple, cantaloupe}), and want the set of document IDs that contain all the words. (e.g. {apple, cantaloupe} -> {1, 6}) Design a distributed system to implement this, bearing in mind that the number of documents, the number of words, and the number of document-IDs-per-word are potentially really, really big.
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Interviewed at LinkedIn

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Aug 8, 2015

You have a potentially very-large set of documents, which are potentially very-large, and contain text. For searching these documents, they've been pre-processed into a (very-large) table mapping words to the set of documents that contain each word. E.g. (word) : (documents (referenced by ID) containing that word) Apple: 1, 4, 5, 6, 32 Banana: 5, 6, 7, 9, 32 Cantaloupe: 1, 2, 6 ... Clients will pass in a set of words (e.g. {apple, cantaloupe}), and want the set of document IDs that contain all the words. (e.g. {apple, cantaloupe} -> {1, 6}) Design a distributed system to implement this, bearing in mind that the number of documents, the number of words, and the number of document-IDs-per-word are potentially really, really big.

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