[jira] Updated: (HADOOP-4437) Use qMC sequence to improve the accuracy of PiEstimator

["Tsz Wo (Nicholas), SZE (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HADOOP-4437?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Tsz Wo (Nicholas), SZE updated HADOOP-4437:
-------------------------------------------

    Attachment: 4437_20081019.patch

4437_20081019.patch: replace java.util.Random with Halton sequence.

Try totally 100000000 samples
- Before the patch:
Job Finished in 22.422 seconds
Estimated value of PI is 3.14145832

- After the patch:
Job Finished in 13.375 seconds
Estimated value of PI is 3.14159256000000000000


> Use qMC sequence to improve the accuracy of PiEstimator
> -------------------------------------------------------
>
>                 Key: HADOOP-4437
>                 URL: https://issues.apache.org/jira/browse/HADOOP-4437
>             Project: Hadoop Core
>          Issue Type: Improvement
>          Components: examples
>            Reporter: Tsz Wo (Nicholas), SZE
>            Priority: Minor
>         Attachments: 4437_20081019.patch
>
>
> Currently, PiEstimator uses java.util.Random to generate random 2d-points for estimating pi. The numbers generated by java.util.Random are uniformly distributed.  The 2d-points generated tense to have clump and gap. So the accuracy of the estimated pi is low.  The accuracy can be improved by using a quasi-Monte Carlo (qMC) sequence.

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