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From "Nicholas Chammas (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-19553) Add GroupedData.countApprox()
Date Mon, 13 Feb 2017 17:21:41 GMT

    [ https://issues.apache.org/jira/browse/SPARK-19553?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15864000#comment-15864000
] 

Nicholas Chammas commented on SPARK-19553:
------------------------------------------

Quick API question for you [~marmbrus]: Is this feature request appropriate? If yes, would
it be better expressed as a SQL function or as a method on {{GroupedData}}?

> Add GroupedData.countApprox()
> -----------------------------
>
>                 Key: SPARK-19553
>                 URL: https://issues.apache.org/jira/browse/SPARK-19553
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.1.0
>            Reporter: Nicholas Chammas
>            Priority: Minor
>
> We already have a [{{pyspark.sql.functions.approx_count_distinct()}}|http://spark.apache.org/docs/latest/api/python/pyspark.sql.html#pyspark.sql.functions.approx_count_distinct]
that can be applied to grouped data, but it seems odd that you can't just get regular approximate
count for grouped data.
> I imagine the API would mirror that for [{{RDD.countApprox()}}|http://spark.apache.org/docs/latest/api/python/pyspark.html#pyspark.RDD.countApprox],
but I'm not sure:
> {code}
> (df
>     .groupBy('col1')
>     .countApprox(timeout=300, confidence=0.95)
>     .show())
> {code}
> Or, if we want to mirror the {{approx_count_distinct()}} function, we can do that too.
I'd want to understand why that function doesn't take a timeout or confidence parameter, though.
Also, what does {{rsd}} mean? It's not documented.



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