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https://issues.apache.org/jira/browse/HDFS-13709?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16909643#comment-16909643
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Wei-Chiu Chuang commented on HDFS-13709:
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Thanks [~zhangchen]
 Can you help verify the failed tests are unrelated?
 Additionally, it would be great if you can add a few javadoc comments for the 
new handleBadBlock() method. Its logic can be a little convoluted given that 
there are two asynchronous threads involved (datanode and volume scanner) We 
definitely want to avoid a situation where volumescanner finds a suspect, 
calling handleBadBlock() and then the suspect is put into voumescanner's queue 
and get scanned again and again non-stop.

nit
{code:java}
assertTrue(replicaCount == 1);
{code}
better to use 
{code:java}
assertEquals("error message", 1, replicaCount);
 {code}

> Report bad block to NN when transfer block encounter EIO exception
> ------------------------------------------------------------------
>
>                 Key: HDFS-13709
>                 URL: https://issues.apache.org/jira/browse/HDFS-13709
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>          Components: datanode
>            Reporter: Chen Zhang
>            Assignee: Chen Zhang
>            Priority: Major
>         Attachments: HDFS-13709.002.patch, HDFS-13709.003.patch, 
> HDFS-13709.004.patch, HDFS-13709.patch
>
>
> In our online cluster, the BlockPoolSliceScanner is turned off, and sometimes 
> disk bad track may cause data loss.
> For example, there are 3 replicas on 3 machines A/B/C, if a bad track occurs 
> on A's replica data, and someday B and C crushed at the same time, NN will 
> try to replicate data from A but failed, this block is corrupt now but no one 
> knows, because NN think there is at least 1 healthy replica and it keep 
> trying to replicate it.
> When reading a replica which have data on bad track, OS will return an EIO 
> error, if DN reports the bad block as soon as it got an EIO,  we can find 
> this case ASAP and try to avoid data loss



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