Hi Amit, Thanks for the reply. If I understand your suggestion correctly, and assuming we have 100 region servers, I would have to do 100 scans to merge reads if I want to pull any data for a specific date. Is that correct? Is the 100 scans the most efficient way to deal with this issue?
Any thoughts? Many thanks. Bill On Sun, Jan 19, 2014 at 4:02 PM, Amit Sela <[email protected]> wrote: > If you'll use bulk load to insert your data you could use the date as key > prefix and choose the rest of the key in a way that will split each day > evenly. You'll have X regions for Evey day >> 14X regions for the two weeks > window. > On Jan 19, 2014 8:39 PM, "Bill Q" <[email protected]> wrote: > > > Hi, > > I am designing a schema to host some large volume of data over HBase. We > > collect daily trading data for some markets. And we run a moving window > > analysis to make predictions based on a two weeks window. > > > > Since everybody is going to pull the latest two weeks data every day, if > we > > put the date in the lead positions of the Key, we will have some hot > > regions. So, we can use bucketing (date to mode bucket number) approach > to > > deal with this situation. However, if we have 200 buckets, we need to run > > 200 scans to extract all the data in the last two weeks. > > > > My questions are: > > 1. What happens when each scan return the result? Will the scan result be > > sent to a sink like place that collects and concatenate all the scan > > results? > > 2. Why having 200 scans might be a bad thing compared to have only 10 > > scans? > > 3. Any suggestions to the design? > > > > Many thanks. > > > > > > Bill > > >
