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# Order statistics and estimating cardinalities of massive data sets

1 ALGORITHMS - Algorithms
Inria Paris-Rocquencourt
Abstract : We introduce a new class of algorithms to estimate the cardinality of very large multisets using constant memory and doing only one pass on the data. It is based on order statistics rather that on bit patterns in binary representations of numbers. We analyse three families of estimators. They attain a standard error of $\frac{1}{\sqrt{M}}$ using $M$ units of storage, which places them in the same class as the best known algorithms so far. They have a very simple internal loop, which gives them an advantage in term of processing speed. The algorithms are validated on internet traffic traces.
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Conference papers
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Cited literature [12 references]

https://hal.inria.fr/hal-01184025
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Submitted on : Wednesday, August 12, 2015 - 3:51:21 PM
Last modification on : Thursday, February 3, 2022 - 11:18:43 AM
Long-term archiving on: : Friday, November 13, 2015 - 11:39:58 AM

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### Citation

Frédéric Giroire. Order statistics and estimating cardinalities of massive data sets. 2005 International Conference on Analysis of Algorithms, 2005, Barcelona, Spain. pp.157-166, ⟨10.46298/dmtcs.3353⟩. ⟨hal-01184025⟩

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