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From "Yongjun Zhang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HDFS-12051) Intern duplicate byte[] arrays (mainly those denoting file/directory names) to save memory
Date Wed, 17 Jan 2018 07:51:00 GMT

    [ https://issues.apache.org/jira/browse/HDFS-12051?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16328411#comment-16328411
] 

Yongjun Zhang commented on HDFS-12051:
--------------------------------------

HI [~szetszwo],

Thanks for your feedback. [~misha@cloudera.com] changed the summary and description to address
your comments, so now they are consistent with the patch changes. Wold you please take a look
to see if it works for you? Thanks.

 

 

> Intern duplicate byte[] arrays (mainly those denoting file/directory names) to save memory
> ------------------------------------------------------------------------------------------
>
>                 Key: HDFS-12051
>                 URL: https://issues.apache.org/jira/browse/HDFS-12051
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>            Reporter: Misha Dmitriev
>            Assignee: Misha Dmitriev
>            Priority: Major
>         Attachments: HDFS-12051.01.patch, HDFS-12051.02.patch, HDFS-12051.03.patch, HDFS-12051.04.patch,
HDFS-12051.05.patch, HDFS-12051.06.patch
>
>
> When snapshot diff operation is performed in a NameNode that manages several million
HDFS files/directories, NN needs a lot of memory. Analyzing one heap dump with jxray (www.jxray.com),
we observed that duplicate byte[] arrays result in 6.5% memory overhead, and most of these
arrays are referenced by {{org.apache.hadoop.hdfs.server.namenode.INodeFileAttributes$SnapshotCopy.name}}
and {{org.apache.hadoop.hdfs.server.namenode.INodeFile.name}}:
> {code:java}
> 19. DUPLICATE PRIMITIVE ARRAYS
> Types of duplicate objects:
>      Ovhd         Num objs  Num unique objs   Class name
> 3,220,272K (6.5%)   104749528      25760871         byte[]
> ....
>   1,841,485K (3.7%), 53194037 dup arrays (13158094 unique)
> 3510556 of byte[17](112, 97, 114, 116, 45, 109, 45, 48, 48, 48, ...), 2228255 of byte[8](48,
48, 48, 48, 48, 48, 95, 48), 357439 of byte[17](112, 97, 114, 116, 45, 109, 45, 48, 48, 48,
...), 237395 of byte[8](48, 48, 48, 48, 48, 49, 95, 48), 227853 of byte[17](112, 97, 114,
116, 45, 109, 45, 48, 48, 48, ...), 179193 of byte[17](112, 97, 114, 116, 45, 109, 45, 48,
48, 48, ...), 169487 of byte[8](48, 48, 48, 48, 48, 50, 95, 48), 145055 of byte[17](112, 97,
114, 116, 45, 109, 45, 48, 48, 48, ...), 128134 of byte[8](48, 48, 48, 48, 48, 51, 95, 48),
108265 of byte[17](112, 97, 114, 116, 45, 109, 45, 48, 48, 48, ...)
> ... and 45902395 more arrays, of which 13158084 are unique
>      <-- org.apache.hadoop.hdfs.server.namenode.INodeFileAttributes$SnapshotCopy.name
<-- org.apache.hadoop.hdfs.server.namenode.snapshot.FileDiff.snapshotINode <--  {j.u.ArrayList}
<-- org.apache.hadoop.hdfs.server.namenode.snapshot.FileDiffList.diffs <-- org.apache.hadoop.hdfs.server.namenode.snapshot.FileWithSnapshotFeature.diffs
<-- org.apache.hadoop.hdfs.server.namenode.INode$Feature[] <-- org.apache.hadoop.hdfs.server.namenode.INodeFile.features
<-- org.apache.hadoop.hdfs.server.blockmanagement.BlockInfo.bc <-- ... (1 elements)
... <-- org.apache.hadoop.hdfs.server.blockmanagement.BlocksMap$1.entries <-- org.apache.hadoop.hdfs.server.blockmanagement.BlocksMap.blocks
<-- org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.blocksMap <-- org.apache.hadoop.hdfs.server.blockmanagement.BlockManager$BlockReportProcessingThread.this$0
<-- j.l.Thread[] <-- j.l.ThreadGroup.threads <-- j.l.Thread.group <-- Java Static:
org.apache.hadoop.fs.FileSystem$Statistics.STATS_DATA_CLEANER
>   409,830K (0.8%), 13482787 dup arrays (13260241 unique)
> 430 of byte[32](116, 97, 115, 107, 95, 49, 52, 57, 55, 48, ...), 353 of byte[32](116,
97, 115, 107, 95, 49, 52, 57, 55, 48, ...), 352 of byte[32](116, 97, 115, 107, 95, 49, 52,
57, 55, 48, ...), 350 of byte[32](116, 97, 115, 107, 95, 49, 52, 57, 55, 48, ...), 342 of
byte[32](116, 97, 115, 107, 95, 49, 52, 57, 55, 48, ...), 341 of byte[32](116, 97, 115, 107,
95, 49, 52, 57, 55, 48, ...), 341 of byte[32](116, 97, 115, 107, 95, 49, 52, 57, 55, 48, ...),
340 of byte[32](116, 97, 115, 107, 95, 49, 52, 57, 55, 48, ...), 337 of byte[32](116, 97,
115, 107, 95, 49, 52, 57, 55, 48, ...), 334 of byte[32](116, 97, 115, 107, 95, 49, 52, 57,
55, 48, ...)
> ... and 13479257 more arrays, of which 13260231 are unique
>      <-- org.apache.hadoop.hdfs.server.namenode.INodeFile.name <-- org.apache.hadoop.hdfs.server.blockmanagement.BlockInfo.bc
<-- org.apache.hadoop.util.LightWeightGSet$LinkedElement[] <-- org.apache.hadoop.hdfs.server.blockmanagement.BlocksMap$1.entries
<-- org.apache.hadoop.hdfs.server.blockmanagement.BlocksMap.blocks <-- org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.blocksMap
<-- org.apache.hadoop.hdfs.server.blockmanagement.BlockManager$BlockReportProcessingThread.this$0
<-- j.l.Thread[] <-- org.apache.hadoop.hdfs.server.blockmanagement.BlocksMap$1.entries
<-- org.apache.hadoop.hdfs.server.blockmanagement.BlocksMap.blocks <-- org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.blocksMap
<-- org.apache.hadoop.hdfs.server.blockmanagement.BlockManager$BlockReportProcessingThread.this$0
<-- j.l.Thread[] <-- j.l.ThreadGroup.threads <-- j.l.Thread.group <-- Java Static:
org.apache.hadoop.fs.FileSystem$Statistics.STATS_DATA_CLEANER
> ....
> {code}
> There are several other places in NameNode code which also produce duplicate {{byte[]}}
arrays.
> To eliminate this duplication and reclaim memory, we will need to write a small class
similar to StringInterner, but designed specifically for byte[] arrays.



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