Django with huge mysql database
Depending upon the data format (you said CSV) and the database, you'll probably be better off loading the data directly into the database (either directly into the Django-managed tables, or into temp tables).  As an example, Oracle and SQL Server provide custom tools for loading large amounts of data.  In the case of MySQL, there are a lot of tricks that you can do.  As an example, you can write a perl/python script to read the CSV file and create a SQL script with insert statements, and then feed the SQL script directly to MySQL.
As others have said, always drop your indexes and triggers before loading large amounts of data, and then add them back afterwards -- rebuilding indexes after every insert is a major processing hit.  
If you're using transactions, either turn them off or batch your inserts to keep the transactions from being too large (the definition of too large varies, but if you're doing 1 million rows of data, breaking that into 1 thousand transactions is probably about right).
And most importantly, BACKUP UP YOUR DATABASE FIRST!  The only thing worse than having to restore your database from a backup because of an import screwup is not having a current backup to restore from.
What would be the best way to import multi-million record csv files into django.
Currently using python csv module, it takes 2-4 days for it process 1 million record file. It does some checking if the record already exists, and few others.
Can this process be achieved to execute in few hours.
Can  memcache be used somehow.
Update: There are django ManyToManyField fields that get processed as well. How will these used with direct load.