XGBoost Huge Dataset ~1TB Can a gradient boosting solution like XGBoost or Lightbgm be used for a huge amount of data ? I have a csv file of 820GB containing 1 Billion observations and each observation has 650 datapoints.

Is this too much data for XGBoost ? I have searched all over the internet for a solution to when the data won't fit into RAM memory to no avail. I read about external memory for xgb but there is no detailed doc. Can someone point me in the right direction please and thank you !
1) Split data in smaller blocks 

2) learn clf on first block

3) Dump model into pickle 

4) load second block 

5) load model from pickle 

6)
    learn clf on second block and so on