We are importing data from 3 CSV files. Documentation regarding the originating database is for the most part, not available to us.
Translating directly from CSV to .sql files, we can see that the three files are really the first, second and third parts of one huge table and could be merged into one. This would simplify queries for us.
We realize that eventually, normalization should be applied, but for the interim, can we expect a performance penalty if we "concatenate" the the 3 tables into 1.
Taken as a sum, we should have about 330 columns and 5000+ rows.
Comments would be appreciated. Pointers to documentation on this subject are also quite welcome.
Are you saying: each CSV contains about 110 columns for the same key values - or - each CSV contains 1700+ rows for the same 330 columns. - or - something else?
In the first case, I would consider loading three tables, then using sql to "join" the data by key values and dump it into a new table with all 330 columns. Then delete the three temp tables.
In the second case, I would concatenate the CSV files, then import them into a table of 330 columns.
What performance penalty are you expecting with either of these scenarios?
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