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https://issues.apache.org/jira/browse/HBASE-50?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12854299#action_12854299
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Li Chongxin commented on HBASE-50:
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@ Todd Lipcon Here are some comments for your questions
* How do we make snapshot creation very low impact on the cluster?
According to the proposal, there is no memstore flush for the snapshot
creation, and no real copy is performed. What snapshot creation does is to dump
the manifest and meta data as well as roll the WAL. I think this does not
impact the cluster very much. What do you think?
* What happens if the snapshot is initiated during a transition? eg a region is
in the middle of a split or recovery?
In current implementation, a write lock is acquired when the system is trying
to do a transition. When the snapshot is requested, we can try to acquire this
write lock. Snapshot is initiated only If the write lock can be obtained.
* How do we do the reference counting in an efficient way?
I'm not sure what Jonathan Gray mean is hard-link or hard-lock in HDFS. If
hard-links is supported in HDFS, then everything is simple since HDFS wil
handle the reference counting of the files. But if hard-link is not supported,
then we will have to count the reference by outselves. Probably via metadata,
zookeeper or ondisk files. Any ideas?
* If old files are moved aside after a compaction, how do we deal with
concurrent readers of the snapshot?
I'm not very clear about this question. What's the problem with concurrent
readers of the snapshot? Can you give some more comments?
> Snapshot of table
> -----------------
>
> Key: HBASE-50
> URL: https://issues.apache.org/jira/browse/HBASE-50
> Project: Hadoop HBase
> Issue Type: New Feature
> Reporter: Billy Pearson
> Priority: Minor
>
> Havening an option to take a snapshot of a table would be vary useful in
> production.
> What I would like to see this option do is do a merge of all the data into
> one or more files stored in the same folder on the dfs. This way we could
> save data in case of a software bug in hadoop or user code.
> The other advantage would be to be able to export a table to multi locations.
> Say I had a read_only table that must be online. I could take a snapshot of
> it when needed and export it to a separate data center and have it loaded
> there and then i would have it online at multi data centers for load
> balancing and failover.
> I understand that hadoop takes the need out of havening backup to protect
> from failed servers, but this does not protect use from software bugs that
> might delete or alter data in ways we did not plan. We should have a way we
> can roll back a dataset.
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