After the current sorted profile finishes I will revert to the textual version and run a profile on that. I expect another 10-15 minutes for this to finish right now.
At present the batch size is set to 1000, total record count is just over 9000 in these tests. The reason for 1000 was at first I was looking at doing this as a tuple_(fld, fld).in_((val, val),(val,val)) format. The 1000 should keep me under most DB restrictions on the in statement. However since SQL Server does not seem to support the tuple_ usage I reverted to this method. I technically have one more method and that is a concat_ in_ where I concat the fields. Other specifics, the table in question has 2 fields for the PK, both are varchar, one length 3, the other length 10. There are 5 non key fields, 3 short varchars, one decimal at 14,2 precision and one varchar(800) which contains description text. Total record count of the table before any deletion is about 1.05 million. Python version is 3.4.5, running on a modest CentOS desktop and to be fair the SQL Server instance is sub optimal for development. On Wednesday, August 30, 2017 at 11:18:13 AM UTC-4, Simon King wrote: > > It would be interesting to see the profile of the textual SQL version. > It looks like most of the time is being spent inside pyodbc, rather > than SQLAlchemy, so I guess it must be something to do with the > processing of bind parameters. How many parameters are being sent in > per query? ie. what is len(id_batch) * len(cls.SQL_PK)? > > You could try playing with your batch sizes to see what sort of effect > that has. > > Simon > -- SQLAlchemy - The Python SQL Toolkit and Object Relational Mapper http://www.sqlalchemy.org/ To post example code, please provide an MCVE: Minimal, Complete, and Verifiable Example. See http://stackoverflow.com/help/mcve for a full description. --- You received this message because you are subscribed to the Google Groups "sqlalchemy" group. To unsubscribe from this group and stop receiving emails from it, send an email to sqlalchemy+unsubscr...@googlegroups.com. To post to this group, send email to sqlalchemy@googlegroups.com. Visit this group at https://groups.google.com/group/sqlalchemy. For more options, visit https://groups.google.com/d/optout.
