Sadly there's not a great lot of documentation about HDFS/Hive - we're learning a lot as we go with SnowPlow.
But I do agree with you - if the same queries keep coming up frequently, then it's worth putting some tech in place to save on ad hoc querying costs. But an RDBMS isn't a great fit for this - because the data is a) non-relational and b) immutable. Happily there's a whole class of database designed for this type of work - analytics databases such as Greenplum and Infobright (Infobright is a modded MySQL too).
In any case, if you have your event data stored in flat files, then as well as a "raw load" into your analytics database, you can also schedule regular map-reduce jobs to populate specific cubes into your analytics db. This is something we're working on for SnowPlow now as well.
But I do agree with you - if the same queries keep coming up frequently, then it's worth putting some tech in place to save on ad hoc querying costs. But an RDBMS isn't a great fit for this - because the data is a) non-relational and b) immutable. Happily there's a whole class of database designed for this type of work - analytics databases such as Greenplum and Infobright (Infobright is a modded MySQL too).
In any case, if you have your event data stored in flat files, then as well as a "raw load" into your analytics database, you can also schedule regular map-reduce jobs to populate specific cubes into your analytics db. This is something we're working on for SnowPlow now as well.