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From "Julien Nioche (JIRA)" <j...@apache.org>
Subject [jira] Resolved: (GORA-20) Flush datastore regularly
Date Tue, 11 Jan 2011 10:09:45 GMT

     [ https://issues.apache.org/jira/browse/GORA-20?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Julien Nioche resolved GORA-20.
-------------------------------

    Resolution: Fixed

Committed revision 1057554.

I've modified the patch slightly to include the license header + removed author comment (as
the other classes do not have that)
GORA does not come with a default Hadoop-like config file, overriding the value can be done
e.g. in the Nutch conf

Thanks Alexis! 

> Flush datastore regularly
> -------------------------
>
>                 Key: GORA-20
>                 URL: https://issues.apache.org/jira/browse/GORA-20
>             Project: Gora
>          Issue Type: New Feature
>          Components: storage
>    Affects Versions: 0.1-incubating
>            Reporter: Alexis
>             Fix For: 0.1-incubating
>
>         Attachments: gora.patch, mapred-site.xml
>
>
> Right now you need to explicitly call the flush method to make the IO operation happen,
or close the datastore.
> The issue is described here: http://techvineyard.blogspot.com/2010/12/build-nutch-20.html#Free_up_the_memory.
Click on the image to see it in real size and look at the Heap utilization on the top right
chart.
> Not everybody has infinite memory. In a Nutch fetch process, I usually run into trouble
after around 20k urls downloaded because it takes up all the memory, the Java Heap space being
set to 1G with a system that "only" has 1G RAM as well.
> The feature consists of allowing the datastore to be flushed regularly during the Hadoop
job's reducer, org.apache.gora.mapreduce.GoraReducer. We would just add a maxBuffer parameter,
which default value is 10000 for example and that you can override in org.apache.gora.mapreduce.GoraOutputFormat.
It indicates the maximum number of records buffered in memory before the next flush operation
occurs to actually write them in the datastore. This would actually be a member of the org.apache.hadoop.mapreduce.RecordWriter
extension returned by getRecordWriter method.
> An idea of the fix is suggested in the above link. 

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