[jira] [Updated] (SPARK-33678) Numerical product aggregation

["Richard Penney (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-33678?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Richard Penney updated SPARK-33678:
-----------------------------------
    Affects Version/s: 2.4.7
                       3.0.0

> Numerical product aggregation
> -----------------------------
>
>                 Key: SPARK-33678
>                 URL: https://issues.apache.org/jira/browse/SPARK-33678
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.4.7, 3.0.0, 3.1.0
>            Reporter: Richard Penney
>            Priority: Minor
>
> There is currently no facility in `spark.sql.functions` to allow computation of the product of all numbers in a grouping expression. Such a facility would likely be useful when computing statistical quantities such as the combined probability of a set of independent events, or in financial applications when calculating a cumulative interest rate.
> Although it is certainly possible to achieve this by an expression of the form `exp(log(sum(column)))`, this has a number of significant drawbacks:
>  * It involves computationally costly functions (exp, log)
>  * It is much more verbose than something like `product(column)`
>  * It is more prone to numerical inaccuracies when handling quantities that are close to one than by directly multiplying a set of numbers
>  * It will not handle negative numbers cleanly
> I am currently developing an addition to `sql.functions`, which involves [a new Catalyst aggregation expression|[https://github.com/rwpenney/spark/blob/feature/agg-product/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Product.scala].] This needs some additional testing, and I hope to issue a pull-request soon.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org