How to load large dataset to python and perform matrix operations
From python perspective, I'm currently using h5py to handle this big data. And it is fast too. You should check it out. However, I believe that Google might have provide something to handle this type of data.
I have a large dataset with 100 million rows of user online activities.  Each row includes a timestamp, user id, and site domain name. I would like to transform the dataset into a matrix of unique domain and user id, in order to perform some matrix operations.  The number of unique domains is about 100K and the number of unique user is about 10 million.  The matrix is very sparse.  
What's the best packages or technologies to use? I realize my question is very broad.  I am using python and Google Cloud Platform, so I am hoping the solutions would be on those lines.