How to train my model efficiently?
From what I understand - your problem is "sample selection bias" problem. Any kind of pattern to select a subset out of large data may lead to bias. This raises two question.


How to choose? Random/stratified random (If you have multiple classes) under sampling to obtain a smaller subset.
How big to choose? we can set percentage of undersampling. 


Reducing training time : We can perform preprocessing : dimensionality reduction techniques to remove correlated data by aplying techniques like- PCA. Or Sparse reconstruction methods - Transform data to sparse data and then process.