[jira] [Closed] (MADLIB-1509) Memory Shortage when serializing the model

["Orhan Kislal (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MADLIB-1509?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Orhan Kislal closed MADLIB-1509.
--------------------------------
    Fix Version/s: v1.21.0
                       (was: v1.19.0)
       Resolution: Cannot Reproduce

> Memory Shortage when serializing the model
> ------------------------------------------
>
>                 Key: MADLIB-1509
>                 URL: https://issues.apache.org/jira/browse/MADLIB-1509
>             Project: Apache MADlib
>          Issue Type: Bug
>          Components: Deep Learning
>            Reporter: Xinyi Zhang
>            Priority: Major
>             Fix For: v1.21.0
>
>
> When I train a model whose size is about 400MB, the execution time for serialize_nd_weights can be very slow. Specifically, the first-time execution of serialize_nd_weights lasts about {color:#FF0000}2 seconds{color}, which is reasonable. However, afterward, its execution time becomes about {color:#FF0000}190 seconds{color}.
> I think the memory shortage causes the long execution time for serialize_nd_weights, since the time can be reduced with a more memory-efficient implementation for serializing (from 190 seconds to 70 seconds).
> However, the instance I run Madlib has 290G memory available. I think that Madlib might set the wrong memory limit for its task. Is there any way to configure the memory limit for Madlib tasks?



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