Hi all, I have a question regarding the difference between storing a set of data as: *a) n columns with 1 version each* *b) 1 column with n versions*
Since the storage unit in hbase is a cell (rowkey, column family, column qualifier, timestamp), is there a difference between the above two storage options in terms of read/write performance, compaction/GC time, etc? I know it is not recommended to use high number of versions if you do not really need them. However, if those n versions of data are really needed for reading, then will it cause any problem to store the data in a single column with n versions. Also, even if max versions is set to 1 for a column (option a), new values are still stored as a new cell and old cell is deleted at compaction time. So, I also feel like compaction-wise two options are identical. I wonder if there is anything that makes one option superior to the other. *Example*: To clarify more, say the data to be stored is set of urls visited in certain time ranges and we want to keep the last 100 hours of url sets: *a) store each hour as column name with one url set in it (column names will be used in cyclic manner (data for hour 101 will be written into column 1))* column_qualifier: value --------------------------- urls_hour1: <abc.com, xyz.com, ...> urls_hour2: <urls> urls_hour3: <urls> ... urls_hour100: <urls> *b) store in a single column with 100 versions (one for each hour) (max versions for column will be 100 and hbase will do the auto-compaction for old versions)* column_qualifier: value @ timestamp --------------------------- urls: <abc.com, xyz.com, ...> @ ts_hour1, <urls> @ ts_hour2, <urls> @ ts_hour3, .... , <urls> @ ts_hour100 Thanks, -Serkan
