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Posted to issues@flink.apache.org by "Chenguang He (JIRA)" <ji...@apache.org> on 2016/04/21 22:32:13 UTC

[jira] [Updated] (FLINK-3802) Add Very Fast Reservoir Sampling

     [ https://issues.apache.org/jira/browse/FLINK-3802?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Chenguang He updated FLINK-3802:
--------------------------------
    Description: 
Adding Very Fast Reservoir Sampling (http://erikerlandson.github.io/blog/2015/11/20/very-fast-reservoir-sampling/)

An improved version of Reservoir Sampling, it's used to deal with small sampling in large dataset, where the size of dataset is much larger than the size of sampling.

It is a random sampling proved in the link. The average possibility is P(R/J), where R is size of sampling and J is index of streaming data 

Thanks Erik Erlandson who is the author of this algorithm help me with implementation.

  was:
Adding Very Fast Reservoir Sampling (http://erikerlandson.github.io/blog/2015/11/20/very-fast-reservoir-sampling/)

An improvement version of Reservoir Sampling, it's used to deal with small sampling in large dataset, where the set of dataset is much larger than the size of sampling.

It is a random sampling proved in the link. The average possibility is P(R/J), where R is size of sampling and J is index of streaming data 

Thanks Erik Erlandson who is the author of this algorithm help me with implementation.


> Add Very Fast Reservoir Sampling
> --------------------------------
>
>                 Key: FLINK-3802
>                 URL: https://issues.apache.org/jira/browse/FLINK-3802
>             Project: Flink
>          Issue Type: Improvement
>          Components: Java API
>            Reporter: Chenguang He
>            Assignee: Chenguang He
>              Labels: Sampling
>
> Adding Very Fast Reservoir Sampling (http://erikerlandson.github.io/blog/2015/11/20/very-fast-reservoir-sampling/)
> An improved version of Reservoir Sampling, it's used to deal with small sampling in large dataset, where the size of dataset is much larger than the size of sampling.
> It is a random sampling proved in the link. The average possibility is P(R/J), where R is size of sampling and J is index of streaming data 
> Thanks Erik Erlandson who is the author of this algorithm help me with implementation.



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