Hey Brock
I used Cascading quite extensively with time series data.
Along with the standard function/filter/aggregator operations in the
Cascading processing model, there is what we call a "buffer".
Its really just a user friendly Reduce that integrates well with other
operations and offers up a "sliding window" across your grouped data.
Quite useful for running averages or filling in missing intervals etc.
Plus there are handy operations for switching from text time strings
to long time stamps and back etc..
YMMV
cheers,
ckw
On Jan 7, 2009, at 5:03 PM, Brock Judkins wrote:
Hi list,
I am researching hadoop as a possible solution for my company's data
warehousing solution. My question is whether hadoop, possibly in
combination
with Hive or Pig, is a good solution for time-series data? We
basically have
a ton of web analytics to store that we display both internally and
externally.
For the time being I am storing timestamped data points in a huge
MySQL
table, but I know this will not scale very far (although it's
holding up ok
at almost 90MM rows). I am aware that hadoop can scale insanely large
(larger than I need), but does anyone have experience using it to draw
charts based on time series with fairly low latency?
Thanks!
Brock
--
Chris K Wensel
ch...@wensel.net
http://www.cascading.org/
http://www.scaleunlimited.com/
