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