that is, data consists of of an account id with a timestamp column that indicates when the account was updated. This is not to be confused with row insertion/update times tamp maintained by Cassandra for conflict resolution within the Cassanda Nodes. Furthermore the account has about 200 columns and updates occur nightly in batch mode where roughly 300-400 million updates are sent. The problems occurs during the day where updates can be sent that possibly contain older data then the nightly batch update. As such the requirement to first look at the account update time stamp in the database and comparing the proposed update time stamp to determine whether to update or not.
The idea here is that a read before update in Cassandra is generally not a good idea. To alleviate this problem I was thinking of either maintaining a separate Cassandra db with only two columns of account id and update time stamp and using this as a look up before updating or setting a stored procedure within the main database to do the read and update if the data within the database is older.
UPDATE Account SET some columns WHERE lastUpdateTimeStamp < proposedUpdateTimeStamp.
I am kind of leaning towards the separate database or keys pace as a simple look up to determine whether to update the data in the main Cassandra database, that is the database that contain the 200 columns of account data. If this is the best choice then I would like to explore the pros and cons of creating a separate Cassandra Node cluster for look up of account update time stamps vs just adding another key space within the main Cassandra database in terms of performance implications. In this account and time stamp only database I would need to also update the time stamp when the main database would be updated.
Any thoughts are welcome