Overcome memory limitation when downloading from database into Orange 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?
You can use "download data to local memory" checkbox in SQL Table widget, it should allow you to work with up to 1000000 rows.