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https://issues.apache.org/jira/browse/PIG-3059?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13544219#comment-13544219
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Russell Jurney commented on PIG-3059:
-------------------------------------
Regarding Avro, in reading
https://github.com/apache/avro/blob/trunk/lang/java/avro/src/main/java/org/apache/avro/file/DataFileReader.java
- it looks like you can still sync to the next record under most bad reads. We
should do so.
You're right about a bad sync halting things, but in the case of a bad sync -
you might try advancing by some amount using seek() and then sync'ing again? I
think this would work. I could be wrong, but in looking how seeks work - I
think that would be ok. Kinda neat, maybe? Worst case, we would only throw out
inputsplits on a bad sync(), not a bad read(). length() should help, as might
pastSync(), skip() and available()
I agree with Dmitriy's feedback, thanks for taking the time.
> Global configurable minimum 'bad record' thresholds
> ---------------------------------------------------
>
> Key: PIG-3059
> URL: https://issues.apache.org/jira/browse/PIG-3059
> Project: Pig
> Issue Type: New Feature
> Components: impl
> Affects Versions: 0.11
> Reporter: Russell Jurney
> Assignee: Cheolsoo Park
> Fix For: 0.12
>
> Attachments: avro_test_files-2.tar.gz, PIG-3059-2.patch,
> PIG-3059.patch
>
>
> See PIG-2614.
> Pig dies when one record in a LOAD of a billion records fails to parse. This
> is almost certainly not the desired behavior. elephant-bird and some other
> storage UDFs have minimum thresholds in terms of percent and count that must
> be exceeded before a job will fail outright.
> We need these limits to be configurable for Pig, globally. I've come to
> realize what a major problem Pig's crashing on bad records is for new Pig
> users. I believe this feature can greatly improve Pig.
> An example of a config would look like:
> pig.storage.bad.record.threshold=0.01
> pig.storage.bad.record.min=100
> A thorough discussion of this issue is available here:
> http://www.quora.com/Big-Data/In-Big-Data-ETL-how-many-records-are-an-acceptable-loss
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