2009/7/9 Günther Schmidt
Hi,
I've developed this commercial app in Haskell with all of the business logic coded in SQL with the help of haskelldb. Some of the intermediate results (of queries) I had to manifest in extra tables because the initial query was expensive, the intermediate result would be the "source" data of other queries and queries can't themselves be indexed for further efficient querying. Since the amount of data could become rather large, in-memory processing wasn't an option and I thus chose SQL (Sqlite).
The solution works, but still I'm not quite happy about it, since I consider the tables that hold intermediate results fixes.
I understand that the financial industry employs Haskell to analyse large data set under complex schemes. I wonder what techniques are employed for that, do they use Haskell to create some sort of OLAPish tools? Do they use Haskell to run complex queries against SQL data warehouses?
Günther
A couple of years back when I was forced to learn MDX in excruciating detail, I wound up building a little Haskell DSL for manipulating small OLAP-like datasets; I never really liked the API though, and the embedding was pretty weak, because there wasn't much middle ground between getting almost no type protection and having to keep a bunch of HLists around to make sure you don't reuse a dimension attribute in a query incorrectly. As for interfacing with 3rd party OLAP cubes, I haven't heard of anyone having been masochistic enough to build an interface to something like ADO MD from Haskell. -Edward Kmett