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From "Gangl, Michael E (388K)" <Michael.E.Ga...@jpl.nasa.gov>
Subject Realtime Query with hbase (aggregation)
Date Tue, 28 Dec 2010 19:11:50 GMT
I¹m trying to do some realtime queries in HBASE over about 550 million
points of data (~150K rows, ~3700 columns/row), and need some help/ideas on
speeding it up.

I have a dataset in HBASE that consist of the following:

Row ­ a geohashed lat/lon value (there are 150k unique row keys)

Column family 1: science data ­ There are a bunch of columns in this family,
notable a year/day-of-year (doy) pair from 1999260 to 2009366 (so about 3700
columns per family)

It looks like this:

Key          |1999266|1999267|1999268|  ...  |2009365 | 2009366
ljkashd781aj |  -14  | -16   | -17   | ..... | -17.755| -17.5    |
ljkavhd79ads |  -14  | -17   | -17   | ..... | -16.785| -16.665  |
ljkcshd84q2d |  -15  | -16   | -17.35| ..... | -15.445| -12.34   |

So if I wanted to look for the all-time data for a single point (let¹s say
lat/lon ­75,-135) I¹d geohash that point and do a get on it (we¹re assuming
the point exists).

I¹d get back the science column family which has ~3700 points (10 years *
365 days), and can plot this or do whatever I need just fine.

The issue happens when I want to get the data over a larger region- I can
select the region simply enough, I simply do a scan from the start point to
then end point (a bounding box of lat/long values, where geohashes inside
that box are in lexicographic order, this is all straight forward for me).
The issue I have is aggregating the results and returning the average result
for a year/doy pair.

Currently I set up a scanner to go through each row, and for each key I
parse the yeardoy/value and add this to a hash map- the yeardoy is a key
into it, and then I have an object with sum and count (incremented each time
I add to the sum, no more than +1 per row) fields. This lets me sum up the
values and find the average by dividing the sum by the count and having the
average value for a certain year/doy. But this takes a long time for larger
regions (>1 minute, often times 2-3 minutes), and I'm trying to figure out
the best way to do this-

I currently have a 10 node hbase setup (c1.xlarge on AWS). LZO compression
and caching the scan results to a certain extent (I've played with this but
don't think it's speeding me up or slowing me down too much) I'm wondering
if I should add more machines, or if there is a better way to get the
results I'm looking for.

I'm trying to do the aggregation in realtime, but understand I can submit
jobs and return the results to a user at a later time if needs be.

Sorry for the long email, just want to explain the problem clearly.


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