That's true.Then there would be max. 86,400 records per day per userid. That is about 100MB per day. I don't see much difference in both approaches from the storage perspective.
On Wed, Oct 10, 2012 at 1:09 PM, Doug Meil <[email protected]>wrote: > Hi there- > > Given the fact that the userid is in the lead position of the key in both > approaches, I'm not sure that he'd have a region hotspotting problem > because the userid should be able to offer some spread. > > > > > On 10/10/12 12:55 PM, "Jerry Lam" <[email protected]> wrote: > > >Hi: > > > >So you are saying you have ~3TB of data stored per day? > > > >Using the second approach, all data for one day will go to only 1 > >regionserver no matter what you do because HBase doesn't split a single > >row. > > > >Using the first approach, data will spread across regionservers but there > >will be hotspotted to each regionserver during write since this is a > >time-series problem. > > > >Best Regards, > > > >Jerry > > > >On Wed, Oct 10, 2012 at 11:24 AM, yutoo yanio <[email protected]> > >wrote: > > > >> hi > >> i have a question about key & column design. > >> in my application we have 3,000,000,000 record in every day > >> each record contain : user-id, "time stamp", content(max 1KB). > >> we need to store records for one year, this means we will have about > >> 1,000,000,000,000 after 1 year. > >> we just search a user-id over rang of "time stamp" > >> table can design in two way > >> 1.key=userid-timestamp and column:=content > >> 2.key=userid-yyyyMMdd and column:HHmmss=content > >> > >> > >> in first design we have tall-narrow table but we have very very > >>records, in > >> second design we have flat-wide table. > >> which of them have better performance? > >> > >> thanks. > >> > > >
