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https://issues.apache.org/jira/browse/FLINK-3613?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Todd Lisonbee updated FLINK-3613:
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Description:
Implement standard deviation, mean, variance for
org.apache.flink.api.java.aggregation.Aggregations
Ideally implementation should be single pass and numerically stable.
References:
"Scalable and Numerically Stable Descriptive Statistics in SystemML", Tian et
al, International Conference on Data Engineering 2012
http://dl.acm.org/citation.cfm?id=2310392
"The Kahan summation algorithm (also known as compensated summation) reduces
the numerical errors that occur when adding a sequence of finite precision
floating point numbers. Numerical errors arise due to truncation and rounding.
These errors can lead to numerical instability when calculating variance."
https://en.wikipedia.org/wiki/Kahan_summation_algorithm
was:
Implement Standard Deviation for
org.apache.flink.api.java.aggregation.Aggregations
Ideally implementation should be single pass and numerically stable.
References:
"Scalable and Numerically Stable Descriptive Statistics in SystemML", Tian et
al, International Conference on Data Engineering 2012
http://dl.acm.org/citation.cfm?id=2310392
"The Kahan summation algorithm (also known as compensated summation) reduces
the numerical errors that occur when adding a sequence of finite precision
floating point numbers. Numerical errors arise due to truncation and rounding.
These errors can lead to numerical instability when calculating variance."
https://en.wikipedia.org/wiki/Kahan_summation_algorithm
> Add standard deviation, mean, variance to list of Aggregations
> --------------------------------------------------------------
>
> Key: FLINK-3613
> URL: https://issues.apache.org/jira/browse/FLINK-3613
> Project: Flink
> Issue Type: Improvement
> Reporter: Todd Lisonbee
> Priority: Minor
>
> Implement standard deviation, mean, variance for
> org.apache.flink.api.java.aggregation.Aggregations
> Ideally implementation should be single pass and numerically stable.
> References:
> "Scalable and Numerically Stable Descriptive Statistics in SystemML", Tian et
> al, International Conference on Data Engineering 2012
> http://dl.acm.org/citation.cfm?id=2310392
> "The Kahan summation algorithm (also known as compensated summation) reduces
> the numerical errors that occur when adding a sequence of finite precision
> floating point numbers. Numerical errors arise due to truncation and
> rounding. These errors can lead to numerical instability when calculating
> variance."
> https://en.wikipedia.org/wiki/Kahan_summation_algorithm
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