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courses:mapreduce-tutorial:step-13 [2012/01/26 23:13] straka |
courses:mapreduce-tutorial:step-13 [2012/01/31 15:54] (current) straka |
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| You can assume that the integers are uniformly distributed. | You can assume that the integers are uniformly distributed. | ||
| - | Your task is to sort these data. Your solution should work for TBs of data. For that reason, you must use multiple reducers. If your job is executed using //r// reducers, the output consists of //r// files, which when concatenated would produce sorted (key, value) pairs. In other words, each of the output files contains sorted (integer, data) pairs and all keys in one file are either smaller or larger than in other file. | + | Your task is to sort these data, comparing the key numerically and not lexicographically. The lines in the output must be the same as in the input, only in different order. |
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| + | Your solution should work for TBs of data. For that reason, you must use multiple reducers. If your job is executed using //r// reducers, the output consists of //r// files, which when concatenated would produce sorted (key, value) pairs. In other words, each of the output files contains sorted (integer, data) pairs and all keys in one file are either smaller or larger than in other file. Your solution should work for any value //r// -- this value is given to [[.: | ||
| ===== Nonuniform data ===== | ===== Nonuniform data ===== | ||
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| - Find best //r-1// integer separators using the sampled data. | - Find best //r-1// integer separators using the sampled data. | ||
| - Run the second pass, using the separators to guide the partitioning. | - Run the second pass, using the separators to guide the partitioning. | ||
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