I would like to run the association rule mining algorithm of the Orange library on a dataset that is stored in a PostgreSQL database. The table 'buildingset' contains the itemsets for each user, thus each record is related to a user, and each field is related to an item. The values are either 1 (smallint) or missing. The table has about 14,000 records and 31 fields.
When I try to run the algorithm on this dataset, I get the following error:
ValueError Traceback (most recent call last): File "/opt/orange/orange3/Orange/canvas/scheme/widgetsscheme.py", line 722, in process_signals_for_widget handler(*args) File "/home/bdukai/.local/lib/python3.4/site-packages/orangecontrib/associate/widgets/owassociate.py", line 444, in set_data self.X = data.X File "/opt/orange/orange3/Orange/data/sql/table.py", line 353, in X self.download_data(AUTO_DL_LIMIT) File "/opt/orange/orange3/Orange/data/sql/table.py", line 333, in download_data raise ValueError("Too many rows to download the data into memory.") ValueError: Too many rows to download the data into memory.
Thus is there any way overcome this limitation, without upgrading the hardware?