Brian M, Thanks for the reply. I am looking into doing the following with historical market information
a) Base Table ID,Exchange,Description,Base Currency Char(30),Char(10),Varchar(256),Char(5) b) Market Data ID,Date,HighPrice,LowPrice,OpenPrice,ClosePrice,Volume Char(30),Date,Float,Float,Float,Float,Long I am unsure if that table setup is the best choice or if there is a better way to approach it? I've also been wondering if I should jump into the world of NoSQL (specifically cassandra) as I may need to have smaller pricing intervals than days in the future. -Trent On Tuesday, April 8, 2014 6:48:50 PM UTC-6, Brian M wrote: > > Assuming each source needs the same data fields, how about just using one > table and including an extra field to specify which source each record came > from? > Or if you really want a separate table for each timeseries, you could look > into using table inheritance. > http://web2py.com/books/default/chapter/29/06/the-database-abstraction-layer#Table-inheritance > > A little more about how you are planning to use or display the data might > help. 38 separate tables, one table with 38 columns or rows? As a graph > with each series being a line? > > ~Brian > > -- Resources: - http://web2py.com - http://web2py.com/book (Documentation) - http://github.com/web2py/web2py (Source code) - https://code.google.com/p/web2py/issues/list (Report Issues) --- You received this message because you are subscribed to the Google Groups "web2py-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
