[ 
https://issues.apache.org/jira/browse/AVRO-429?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12837258#action_12837258
 ] 

Jeff Hammerbacher commented on AVRO-429:
----------------------------------------

Thanks for reporting, Tyler. Even if the issue goes away, we should add some 
profiling to the tests to make sure we're not leaking anything for long-lived 
writers.

> investigate large heap size when writing many objects to an avro data file 
> (Python)
> -----------------------------------------------------------------------------------
>
>                 Key: AVRO-429
>                 URL: https://issues.apache.org/jira/browse/AVRO-429
>             Project: Avro
>          Issue Type: Bug
>          Components: python
>    Affects Versions: 1.3.0
>            Reporter: R. Tyler Ballance
>
> Logging ~13k entries via the Python client, seeing abnormally large memory 
> usage
> {{
> >>> from guppy import hpy; hp=hpy(); hp.heap()
> Partition of a set of 127501 objects. Total size = 18102576 bytes.
>  Index  Count   %     Size   % Cumulative  % Kind (class / dict of class)
>      0  58443  46  5227392  29   5227392  29 str
>      1  31964  25  2723312  15   7950704  44 tuple
>      2    422   0  1118096   6   9068800  50 dict of module
>      3   1209   1  1007064   6  10075864  56 dict (no owner)
>      4   1111   1  1002608   6  11078472  61 type
>      5   8253   6   990360   5  12068832  67 function
>      6   8225   6   987000   5  13055832  72 types.CodeType
>      7   1111   1   797992   4  13853824  77 dict of type
>      8    377   0   358232   2  14212056  79 dict of class
>      9    103   0   336040   2  14548096  80 dict of 
> django.db.models.fields.CharField
> <448 more rows. Type e.g. '_.more' to view.>
> >>>
> }}

-- 
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.

Reply via email to