Thanks for the advise. What about key is userId + no_day(since user registered), and column family is each typeEvent, and qualifier is the detailed trxs.
On Thu, Nov 14, 2013 at 8:51 AM, Jean-Marc Spaggiari < [email protected]> wrote: > Hi Sam, > > So are you saying that you will have about 30 column families? If so I > don't think tit's a good idea. > > JM > > > 2013/11/13 Sam Wu <[email protected]> > > > Hi all, > > > > I am thinking about using Random Forest to do churn analysis with Hbase > as > > NoSQL data store. > > Currently, we have all the user history (basically many type of event > > data) resides in S3 & Redshift (we have one table per date/per event) > > Events includes startTime, endTime, and other pertinent information,.. > > > > We are thinking about converting all the event tables into one fat > > table(with other helper parameter tables) with one row per user using > Hbase. > > > > Each row will have user id as key, with some column-family/qualifier, > > e.g.: col-family, d1,d2,……d30 (days in the system), and qualifier as > > different types of event. Since initially we are more interested in new > > user retention, so 30 days might be good to start with. > > > > We can label record as churning away by no active activity in continuous > > 10 days. > > > > If data schema looks good, ingest data from S3 into HBase. Then do Random > > Forest to classifier new profile data. > > > > Is this types of data a good candidate for Hbase. > > Opinion is highly appreciated. > > > > > > BR > > > > Sam >
