[ 
https://issues.apache.org/jira/browse/HBASE-13408?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14647348#comment-14647348
 ] 

Duo Zhang commented on HBASE-13408:
-----------------------------------

OK, I get your point. After a memstore compaction we may drop some old cells so 
set a new value of the {{oldestUnflushedSeqId}} in WAL is reasonable. And yes, 
this can avoid WAL triggers a flush for log truncating under your cases.

But I still think you can find a way to set it without changing the semantics 
of flush... Flush is a very critical operation in HBase so you should keep away 
from it as much as possible unless you have to...

Or a more difficult way, remove the old flush operation and introduce some new 
operations such as "reduce your memory usage" and "persist old cells" and so 
on. You can put your compaction logic in the "reduce your memory usage" 
operation.

Thanks.

> HBase In-Memory Memstore Compaction
> -----------------------------------
>
>                 Key: HBASE-13408
>                 URL: https://issues.apache.org/jira/browse/HBASE-13408
>             Project: HBase
>          Issue Type: New Feature
>            Reporter: Eshcar Hillel
>         Attachments: 
> HBaseIn-MemoryMemstoreCompactionDesignDocument-ver02.pdf, 
> HBaseIn-MemoryMemstoreCompactionDesignDocument.pdf, 
> InMemoryMemstoreCompactionEvaluationResults.pdf
>
>
> A store unit holds a column family in a region, where the memstore is its 
> in-memory component. The memstore absorbs all updates to the store; from time 
> to time these updates are flushed to a file on disk, where they are 
> compacted. Unlike disk components, the memstore is not compacted until it is 
> written to the filesystem and optionally to block-cache. This may result in 
> underutilization of the memory due to duplicate entries per row, for example, 
> when hot data is continuously updated. 
> Generally, the faster the data is accumulated in memory, more flushes are 
> triggered, the data sinks to disk more frequently, slowing down retrieval of 
> data, even if very recent.
> In high-churn workloads, compacting the memstore can help maintain the data 
> in memory, and thereby speed up data retrieval. 
> We suggest a new compacted memstore with the following principles:
> 1.    The data is kept in memory for as long as possible
> 2.    Memstore data is either compacted or in process of being compacted 
> 3.    Allow a panic mode, which may interrupt an in-progress compaction and 
> force a flush of part of the memstore.
> We suggest applying this optimization only to in-memory column families.
> A design document is attached.
> This feature was previously discussed in HBASE-5311.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

Reply via email to