Insert performance with Cassandra
It's possible you're hitting the python GIL but more likely you're doing something wrong.
For instance, putting 2M rows in a single batch would be Doing It Wrong.
sorry for my English in advance. 
I am a beginner with Cassandra and his data model. I am trying to insert one million rows in a cassandra database in local on one node. Each row has 10 columns and I insert those only in one column family.
With one thread, that operation took around 3 min. But I would like do the same operation with 2 millions rows, and keeping a good time. Then I tried with 2 threads to insert 2 millions rows, expecting a similar result around 3-4min. bUT i gor a result like 7min...twice the first result. As I check on differents forums, multithreading is recommended to improve performance.
That is why I am asking that question : is it useful to use multithreading to insert data in local node (client and server are in the same computer), in only one column family?
Some informations :
 - I use pycassa
 - I have separated commitlog repertory and data repertory on differents disks
 - I use batch insert for each thread
 - Consistency Level : ONE
 - Replicator factor : 1