Hi, thank you for your enspiring answers. I think I'll stick to the direct sqlite approach instead of the v.distance. There are now two tables in my sqlite database, one is connected to the GRASS vector and the other is a table imported from a csv. For both tables I want to join/merge I created a new column . This new column contains a text-key (like "123.1232-3424.234"). These text strings are identical in both tables that's why I could use them as key.
As both tables have similarly approx. 130 000 rows I am not sure about the fastest way to join/merge/append 3 columns from on table to the GRASS vector table using sqlite? I tried your approach which took very long time (I stopped the process after 45 min), thus I interesting if there is a faster approach than: > sqlite> UPDATE vector SET from_csv_col1=(SELECT c.col1 FROM csv_table AS c > WHERE c.xy_key=vector.xy_key); Is there any way to speed up such a join? As I am newbie to SQL/SQlite, any help is much appreciated! Maybe this is more a question for a pure Sqlite/SQL forum... /johannes _______________________________________________ grass-user mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-user
