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From Ian Varley <ivar...@salesforce.com>
Subject Re: Key Design Question for list data
Date Tue, 03 Apr 2012 19:59:41 GMT
Hi Derek,

If I understand you correctly, you're ultimately trying to store triples in the form "user,
valueid, value", right? E.g., something like:

"user123, firstname, Paul",
"user234, lastname, Smith"

(But the usernames are fixed width, and the valueids are fixed width).

And, your access pattern is along the lines of: "for user X, list the next 30 values, starting
with valueid Y". Is that right? And these values should be returned sorted by valueid?

The tl;dr version is that you should probably go with one row per user+value, and not build
a complicated intra-row pagination scheme on your own unless you're really sure it is needed.

Your two options mirror a common question people have when designing HBase schemas: should
I go "tall" or "wide"? Your first schema is "tall": each row represents one value for one
user, and so there are many rows in the table for each user; the row key is user + valueid,
and there would be (presumably) a single column qualifier that means "the value". This is
great if you want to scan over rows in sorted order by row key (thus my question above, about
whether these ids are sorted correctly). You can start a scan at any user+valueid, read the
next 30, and be done. What you're giving up is the ability to have transactional guarantees
around all the rows for one user, but it doesn't sound like you need that. Doing it this way
is generally recommended (see here<http://hbase.apache.org/book.html#schema.smackdown>).

Your second option is "wide": you store a bunch of values in one row, using different qualifiers
(where the qualifier is the valueid). The simple way to do that would be to just store ALL
values for one user in a single row. I'm guessing you jumped to the "paginated" version because
you're assuming that storing millions of columns in a single row would be bad for performance,
which may or may not be true; as long as you're not trying to do too much in a single request,
or do things like scanning over and returning all of the cells in the row, it shouldn't be
fundamentally worse. The client has methods that allow you to get specific slices of columns.

Note that neither case fundamentally uses more disk space than the other; you're just "shifting"
part of the identifying information for a value either to the left (into the row key, in option
one) or to the right (into the column qualifiers in option 2). Under the covers, every key/value
still stores the whole row key, and column family name. (If this is a bit confusing, take
an hour and watch Lars George's excellent video about understanding HBase schema design: http://www.youtube.com/watch?v=_HLoH_PgrLk).

A manually paginated version has lots more complexities, as you note, like having to keep
track of how many things are in each page, re-shuffling if new values are inserted, etc. That
seems significantly more complex. It might have some slight speed advantages (or disadvantages!)
at extremely high throughput, and the only way to really know that would be to try it out.
If you don't have time to build it both ways and compare, my advice would be to start with
the simplest option (one row per user+value). Start simple & iterate! :)

(Let me know if I've misunderstood your situation.)


On Apr 2, 2012, at 3:10 PM, Derek Wollenstein wrote:

We're looking at how to store a large amount of (per-user) list data in
hbase, and we were trying to figure out what kind of access pattern made
the most sense.  One option is store the majority of the data in a key, so
we could have something like
<FixedWidthUserName><FixedWidthValueId1>:"" (no value)
<FixedWidthUserName><FixedWidthValueId2>:"" (no value)
<FixedWidthUserName><FixedWidthValueId3>:"" (no value)

The other option we hade was to do this entirely using

where each row would contain multiple values.
So in one case reading the first thirty values would be
scan { STARTROW => 'FixedWidthUsername' LIMIT => 30}
And in the second case it would be
get 'FixedWidthUserName\x00\x00\x00\x00'

The general usage pattern would be to read only the first 30 values of
these lists, with infrequent access reading deeper into the lists.  Some
users would have <= 30 total values in these lists, and some users would
have millions (i.e. power-law distribution)

  The single-value format seems like it would take up more space on hbase,
but would offer some improved retrieval / pagination flexibility.  Would
there be any significant performance advantages to be able to paginate via
gets vs paginating with scans?
   My initial understanding was that doing a scan should be faster if our
paging size is unknown (and caching is set appropriately), but that gets
should be faster if we'll always need the same page size.  I've ended up
hearing different people tell me opposite things about performance.  I
assume the page sizes would be relatively consistent, so for most use cases
we could guarantee that we only wanted one page of data in the
fixed-page-length case.  I would also assume that we would have infrequent
updates, but may have inserts into the middle of these lists (meaning we'd
need to update all subsequent rows).

Thanks for help / suggestions / followup questions


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