which index structure would fit Hbase more naturally and perform better in terms of overall throughput: 1) a sparse index where in each row there are 100 columns, each containing a 5MB data block (under a single column family) or 2) a dense index where each row contains 100 columns, with a single 6bytes value in each (under a single column family)
- assuming the total data size is 30-50TB, 500GB appends per day - the data is time series (output from a multichannel EEG sensor) the key performance metric for us is read throughput (random access reads/sec, range queries, sequential scans) Thanks Alex
