[jira] [Updated] (SPARK-19208) MaxAbsScaler and MinMaxScaler are very inefficient

["zhengruifeng (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-19208?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

zhengruifeng updated SPARK-19208:
---------------------------------
    Attachment: WechatIMG2621.jpeg

OOM

> MaxAbsScaler and MinMaxScaler are very inefficient
> --------------------------------------------------
>
>                 Key: SPARK-19208
>                 URL: https://issues.apache.org/jira/browse/SPARK-19208
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>            Reporter: zhengruifeng
>         Attachments: WechatIMG2621.jpeg
>
>
> Now, {{MaxAbsScaler}} and {{MinMaxScaler}} are using {{MultivariateOnlineSummarizer}} to compute the min/max.
> However {{MultivariateOnlineSummarizer}} will also compute extra unused statistics. It slows down the task, moreover it is more prone to cause OOM.
> For example:
> env : --driver-memory 4G --executor-memory 1G --num-executors 4
> data: 748401 instances,   and 3,000,000 features
> {{MaxAbsScaler.fit}} fail because OOM
> {{MultivariateOnlineSummarizer}} maintain 8 arrays
> For {{MaxAbsScaler}}, only one array is needed (max of abs value)
> For {{MinMaxScaler}}, only 3 arrays are needed (max, min, nnz)



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

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