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https://issues.apache.org/jira/browse/HBASE-17819?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16107038#comment-16107038
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ramkrishna.s.vasudevan commented on HBASE-17819:
------------------------------------------------
bq.private volatile boolean markedForEvict;
Minor nit : This comes in both the new impl? Should we add another abstract
class and have this markedForEvict there.
bq.Still it will be worth doing that as above 32 GB heap size, compressed ref
wont be there and refs might take 8 bytes
Compressed ref are not applied in bigger heap sizes? or is it just related to
64 bit or 32 bit architecture?
Rest looks good to me.
> 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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