New to matrices ... coming from relational database background ...
I've got a database table that has: rowkey, columnkey, cellvalue which is read in from SQL to a reader
and the keys are in a hashtable which allows lookup based on key to get row and col IDs. (same set of keys can be in either row or column)
Problem is that it's taking about 4 hours to load ~2M datapoints into a 10500x10500 SparseMatrix A in memory for calculation by looping over the following C# stmt:
A [ (int)idHash [reader[0].ToString()], (int)idHash [reader[1].ToString()] ] = reader.GetDouble(2);
I was looking for a "bulk load" function and see SetColumn and SetRow but just not sure, since it's sparse data, whether it's worth it to prepare by columns or ? ...
Any ideas on how to speed this process up?
Thanks!