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From "Matt Corgan (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-7667) Support stripe compaction
Date Sun, 24 Mar 2013 00:13:15 GMT

    [ https://issues.apache.org/jira/browse/HBASE-7667?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13611909#comment-13611909
] 

Matt Corgan commented on HBASE-7667:
------------------------------------

{quote}If data insertion is uniformly spread (ie, key is uniform random), this proposal performs
much worse than the existing scheme.{quote}I think the goal for uniformly random keys is to
have the same amount of total work done but to stagger that work.  Instead of doing 1 big
24 GB compaction per day, it could do a 1 GB compaction each hour.

The savings/efficiency become more pronounced with less random keys, with the biggest savings
for sequential keys.
                
> Support stripe compaction
> -------------------------
>
>                 Key: HBASE-7667
>                 URL: https://issues.apache.org/jira/browse/HBASE-7667
>             Project: HBase
>          Issue Type: New Feature
>          Components: Compaction
>            Reporter: Sergey Shelukhin
>            Assignee: Sergey Shelukhin
>         Attachments: Stripe compactions.pdf
>
>
> So I was thinking about having many regions as the way to make compactions more manageable,
and writing the level db doc about how level db range overlap and data mixing breaks seqNum
sorting, and discussing it with Jimmy, Matteo and Ted, and thinking about how to avoid Level
DB I/O multiplication factor.
> And I suggest the following idea, let's call it stripe compactions. It's a mix between
level db ideas and having many small regions.
> It allows us to have a subset of benefits of many regions (wrt reads and compactions)
without many of the drawbacks (managing and current memstore/etc. limitation).
> It also doesn't break seqNum-based file sorting for any one key.
> It works like this.
> The region key space is separated into configurable number of fixed-boundary stripes
(determined the first time we stripe the data, see below).
> All the data from memstores is written to normal files with all keys present (not striped),
similar to L0 in LevelDb, or current files.
> Compaction policy does 3 types of compactions.
> First is L0 compaction, which takes all L0 files and breaks them down by stripe. It may
be optimized by adding more small files from different stripes, but the main logical outcome
is that there are no more L0 files and all data is striped.
> Second is exactly similar to current compaction, but compacting one single stripe. In
future, nothing prevents us from applying compaction rules and compacting part of the stripe
(e.g. similar to current policy with rations and stuff, tiers, whatever), but for the first
cut I'd argue let it "major compact" the entire stripe. Or just have the ratio and no more
complexity.
> Finally, the third addresses the concern of the fixed boundaries causing stripes to be
very unbalanced.
> It's exactly like the 2nd, except it takes 2+ adjacent stripes and writes the results
out with different boundaries.
> There's a tradeoff here - if we always take 2 adjacent stripes, compactions will be smaller
but rebalancing will take ridiculous amount of I/O.
> If we take many stripes we are essentially getting into the epic-major-compaction problem
again. Some heuristics will have to be in place.
> In general, if, before stripes are determined, we initially let L0 grow before determining
the stripes, we will get better boundaries.
> Also, unless unbalancing is really large we don't need to rebalance really.
> Obviously this scheme (as well as level) is not applicable for all scenarios, e.g. if
timestamp is your key it completely falls apart.
> The end result:
> - many small compactions that can be spread out in time.
> - reads still read from a small number of files (one stripe + L0).
> - region splits become marvelously simple (if we could move files between regions, no
references would be needed).
> Main advantage over Level (for HBase) is that default store can still open the files
and get correct results - there are no range overlap shenanigans.
> It also needs no metadata, although we may record some for convenience.
> It also would appear to not cause as much I/O.

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