I watched Lars George's video about HBase and read the documentation and it's saying that it's not a good idea to have the timestamp as a key because that will always load the same region until the timestamp reach a certain value and move to the next region (hotspotting).
I have a table with a uniq key, a file path and a "last update" field. I can easily find back the file with the ID and find when it has been updated. But what I need too is to find the files not updated for more than a certain period of time. If I want to retrieve that from this single table, I will have to do a full parsing of the table. Which might take a while. So I thought of building a table to reference that (kind of secondary index). The key is the "last update", one FC and each column will have the ID of the file with a dummy content. When a file is updated, I remove its cell from this table, and introduce a new cell with the new timestamp as the key. And so one. With this schema, I can find the files by ID very quickly and I can find the files which need to be updated pretty quickly too. But it's hotspotting one region. >From the video (0:45:10) I can see 4 situations. 1) Hotspotting. 2) Salting. 3) Key field swap/promotion 4) Randomization. I need to avoid hostpotting, so I looked at the 3 other options. I can do salting. Like prefix the timestamp with a number between 0 and 9. So that will distribut the load over 10 servers. To find all the files with a timestamp below a specific value, I will need to run 10 requests instead of one. But when the load will becaume to big for 10 servers, I will have to prefix by a byte between 0 and 99? Which mean 100 request? And the more regions I will have, the more requests I will have to do. Is that really a good approach? Key field swap is close to salting. I can add the first few bytes from the path before the timestamp, but the issue will remain the same. I looked and randomization, and I can't do that. Else I will have no way to retreive the information I'm looking for. So the question is. Is there a good way to store the data to retrieve them base on the date? Thanks, JM
