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https://issues.apache.org/jira/browse/HDFS-17496?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17908036#comment-17908036
 ] 

ASF GitHub Bot commented on HDFS-17496:
---------------------------------------

hadoop-yetus commented on PR #6764:
URL: https://github.com/apache/hadoop/pull/6764#issuecomment-2560823848

   :confetti_ball: **+1 overall**
   
   
   
   
   
   
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> DataNode supports more fine-grained dataset lock based on blockid
> -----------------------------------------------------------------
>
>                 Key: HDFS-17496
>                 URL: https://issues.apache.org/jira/browse/HDFS-17496
>             Project: Hadoop HDFS
>          Issue Type: Sub-task
>          Components: datanode
>            Reporter: farmmamba
>            Assignee: farmmamba
>            Priority: Major
>              Labels: pull-request-available
>         Attachments: image-2024-04-23-16-17-07-057.png
>
>
> Recently, we used NvmeSSD as volumes in datanodes and performed some stress 
> tests.
> We found that NvmeSSD and HDD disks achieve similar performance when create 
> lots of small files, such as 10KB.
> This phenomenon is counterintuitive.  After analyzing the metric monitoring , 
> we found that fsdataset lock became the bottleneck in high concurrency 
> scenario.
>  
> Currently, we have two level locks which are BLOCK_POOL and VOLUME.  We can 
> further split the volume lock to DIR lock.
> DIR lock is defined as below: given a blockid, we can determine which subdir 
> this block will be placed in finalized dir. We just use 
> subdir[0-31]/subdir[0-31] as the
> name of DIR lock.
> More details, please refer to method DatanodeUtil#idToBlockDir:
> {code:java}
>   public static File idToBlockDir(File root, long blockId) {
>     int d1 = (int) ((blockId >> 16) & 0x1F);
>     int d2 = (int) ((blockId >> 8) & 0x1F);
>     String path = DataStorage.BLOCK_SUBDIR_PREFIX + d1 + SEP +
>         DataStorage.BLOCK_SUBDIR_PREFIX + d2;
>     return new File(root, path);
>   } {code}
> The performance comparison is as below:
> experimental setup:
> 3 DataNodes with single disk.
> 10 Cients concurrent write and delete files after writing.
> 550 threads per Client.
> !image-2024-04-23-16-17-07-057.png!
>  



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