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Posted to issues@arrow.apache.org by "Igor Yastrebov (Jira)" <ji...@apache.org> on 2019/08/30 09:40:00 UTC
[jira] [Commented] (ARROW-6380) Method pyarrow.parquet.read_table
has memory spikes from version 0.14
[ https://issues.apache.org/jira/browse/ARROW-6380?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16919370#comment-16919370 ]
Igor Yastrebov commented on ARROW-6380:
---------------------------------------
Is it a duplicate of [ARROW-6059|https://issues.apache.org/jira/browse/ARROW-6059]?
> Method pyarrow.parquet.read_table has memory spikes from version 0.14
> ---------------------------------------------------------------------
>
> Key: ARROW-6380
> URL: https://issues.apache.org/jira/browse/ARROW-6380
> Project: Apache Arrow
> Issue Type: Bug
> Components: C++
> Affects Versions: 0.14.0, 0.14.1
> Environment: ubuntu 18, 16GB ram, 4 cpus
> Reporter: Renan Alves Fonseca
> Priority: Major
> Fix For: 0.13.0
>
>
> Method pyarrow.parquet.read_table is very slow and cause RAM spikes from version 0.14.0
> Reading a 40MB parquet file takes less than 1 second in versions 0.11, 0.12 and 0.13. wheras it takes from 6 to 30 seconds in versions 0.14.x
> This impact in performance is easily measured. However, there is another problem that I could only detect on htop screen. While opening a 40MB parquet, the process occupies almost 16GB for some miliseconds. The pyarrow table will result in around 300MB in the python process (registered using memory-profiler). This does not happens in versions 0.13 and previous ones.
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