Hi Neil, Mike summed it up well, as usual. :) Your choices of where to describe this "dimension" of your data (a one-to-many between users and events) are:
- one row per event - one row per user, with events as columns - one row per user, with events as versions on a single cell The first two are the best choices, since the third is sort of a perversion of the time dimension (it isn't one thing that's changing, it's many things over time), and might make things counter-intuitive when combined with deletes, compaction, etc. You can do it, but caveat emptor. :) Since you have in the 100s or 1000s of events per user, it's reasonable to use the 2nd (columns). And with 1k cell sizes, even extreme cases (thousands of events) won't kill you. That said, the main plus you get out of using columns over rows is ACID properties; you could get & set all the stuff for a single user atomically if it's columns in a single row, but not if its separate rows. That's nice, but I'm guessing you probably don't need to do that, and instead would write out the events as they happen (i.e., you would rarely be doing PUTs for multiple events for the same user at the same time, right?). In theory, tall tables (the row-wise model) should have a slight performance advantage over wide tables (the column-wise model), all other things being equal; the shape of the data is nearly the same, but the row-wise version doesn't have to do any work preserving consistency. Your informal tests about GET vs SCAN perf seem a little suspect, since a GET is actually implemented as a one-row SCAN; but the devil's in the details, so if you see that happening repeatably with data that's otherwise identical, raise it up to the dev list and people should look at it. The key thing is to try it for yourself and see. :) Ian ps - Sorry Mike was rude to you in his response. Your question was well-phrased and not at all boring. Mike, you can explain all you want, but saying "Your question is boring" is straight up rude; please don't do that. From: Neil Yalowitz <[email protected]<mailto:[email protected]>> Date: Tue, Oct 16, 2012 at 2:53 PM Subject: crafting your key - scan vs. get To: [email protected]<mailto:[email protected]> Hopefully this is a fun question. :) Assume you could architect an HBase table from scratch and you were choosing between the following two key structures. 1) The first structure creates a unique row key for each PUT. The rows are events related to a user ID. There may be up to several hundred events for each user ID (probably not thousands, an average of perhaps ~100 events per user). Each key would be made unique with a reverse-order-timestamp or perhaps just random characters (we don't particularly care about using ROT for sorting newest here). key ---- AAAAAA + some-unique-chars The table will look like this: key vals cf:mycf ts ------------------------------------------------------------------- AAAAAA9999... myval1 1350345600 AAAAAA8888... myval2 1350259200 AAAAAA7777... myval3 1350172800 Retrieving these values will use a Scan with startRow and stopRow. In hbase shell, it would look like: $ scan 'mytable',{STARTROW=>'AAAAAA', ENDROW=>'AAAAAA_'} 2) The second structure choice uses only the user ID as the key and relies on row versions to store all the events. For example: key vals cf:mycf ts --------------------------------------------------------------------- AAAAAA myval1 1350345600 AAAAAA myval2 1350259200 AAAAAA myval3 1350172800 Retrieving these values will use a Get with VERSIONS = somebignumber. In hbase shell, it would look like: $ get 'mytable','AAAAAA',{COLUMN=>'cf:mycf', VERSIONS=>999} ...although this probably violates a comment in the HBase documentation: "It is not recommended setting the number of max versions to an exceedingly high level (e.g., hundreds or more) unless those old values are very dear to you because this will greatly increase StoreFile size." ...found here: http://hbase.apache.org/book/schema.versions.html So, are there any performance considerations between Scan vs. Get in this use case? Which choice would you go for? Neil Yalowitz [email protected]<mailto:[email protected]>
