[jira] [Comment Edited] (HBASE-17819) Reduce the heap overhead for BucketCache

["Vladimir Rodionov (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/HBASE-17819?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16094930#comment-16094930 ] 

Vladimir Rodionov edited comment on HBASE-17819 at 7/20/17 4:33 PM:
--------------------------------------------------------------------

{quote}
BlockCacheKey
---------------
String hfileName - Ref - 4
long offset - 8
BlockType blockType - Ref - 4
boolean isPrimaryReplicaBlock - 1
Total = 12 (Object) + 17 = 29
BucketEntry
------------
int offsetBase - 4
int length - 4
byte offset1 - 1
byte deserialiserIndex - 1
long accessCounter - 8
BlockPriority priority - Ref - 4
volatile boolean markedForEvict - 1
AtomicInteger refCount - 16 + 4
long cachedTime - 8
Total = 12 (Object) + 51 = 63
ConcurrentHashMap Map.Entry - 40
blocksByHFile ConcurrentSkipListSet Entry - 40
Total = 29 + 63 + 80 = 172
{quote}

Just couple corrections on you math, guys

# compressed OOP (obj ref = 4 bytes) works up to 30.5GB of heap size. Many users already have more than that
# object's fields layout is slightly different: n-byte types are aligned on n-bytes boundaries, therefore if you have for example, boolean and long fields in the object, the object's size is going to be 16 (overhead) + 8 + 8 = 32 and not 16 + 1+ 8. You should take into account also that total object size is always multiple of 8, so if you get 42, then its actually - 48, because next object starts on a 8-byte boundary.

You can shave some bytes by just rearranging fields in the object in size descending order: first go 8 byte type, followed by 4-byte types, 2-byte and 1-byte at the end



was (Author: vrodionov):
{quote}
BlockCacheKey
---------------
String hfileName - Ref - 4
long offset - 8
BlockType blockType - Ref - 4
boolean isPrimaryReplicaBlock - 1
Total = 12 (Object) + 17 = 29
BucketEntry
------------
int offsetBase - 4
int length - 4
byte offset1 - 1
byte deserialiserIndex - 1
long accessCounter - 8
BlockPriority priority - Ref - 4
volatile boolean markedForEvict - 1
AtomicInteger refCount - 16 + 4
long cachedTime - 8
Total = 12 (Object) + 51 = 63
ConcurrentHashMap Map.Entry - 40
blocksByHFile ConcurrentSkipListSet Entry - 40
Total = 29 + 63 + 80 = 172
{quote}

Just couple corrections on you math, guys

# compressed OOP (obj ref = 4 bytes) works up to 30.5GB of heap size. Many users already have more than that
# object's fields layout is slightly different: n-byte types are aligned on n-bytes boundaries, therefore if you have for example, boolean and long fields of the object is going to be 16 (overhead) + 8 + 8 = 32 and not 16 + 1+ 8. You should take into account also that total object size is always multiple of 8, so if you get 42, then its actually - 48, because next object starts on a 8-byte boundary.

You can shave some bytes by just rearranging fields in the object in size descending order: first go 8 byte type, followed by 4-byte types, 2-byte and 1-byte at the end


> Reduce the heap overhead for BucketCache
> ----------------------------------------
>
>                 Key: HBASE-17819
>                 URL: https://issues.apache.org/jira/browse/HBASE-17819
>             Project: HBase
>          Issue Type: Sub-task
>          Components: BucketCache
>            Reporter: Anoop Sam John
>            Assignee: Anoop Sam John
>             Fix For: 2.0.0
>
>         Attachments: HBASE-17819_V1.patch, HBASE-17819_V2.patch
>
>
> We keep Bucket entry map in BucketCache.  Below is the math for heapSize for the key , value into this map.
> BlockCacheKey
> ---------------
> String hfileName  -  Ref  - 4
> long offset  - 8
> BlockType blockType  - Ref  - 4
> boolean isPrimaryReplicaBlock  - 1
> Total  =  12 (Object) + 17 = 29
> BucketEntry
> ------------
> int offsetBase  -  4
> int length  - 4
> byte offset1  -  1
> byte deserialiserIndex  -  1
> long accessCounter  -  8
> BlockPriority priority  - Ref  - 4
> volatile boolean markedForEvict  -  1
> AtomicInteger refCount  -  16 + 4
> long cachedTime  -  8
> Total = 12 (Object) + 51 = 63
> ConcurrentHashMap Map.Entry  -  40
> blocksByHFile ConcurrentSkipListSet Entry  -  40
> Total = 29 + 63 + 80 = 172
> For 10 million blocks we will end up having 1.6GB of heap size.  
> This jira aims to reduce this as much as possible



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