Hi, I am using pio V0.12.0 (Hbase 1.2.6, Elasticsearch 5.2.1, Spark 2.6.1). I am using template
> https://github.com/EmergentOrder/template-scala-probabilistic-classifier-batch-lbfgs I spawned two servers each having configuration(244 GB RAM, 16 Cores). On 1 server I uploaded 1 million events with 6000 features and on the second server uploaded 1 million events with 30000 features. It took 24 hrs to train events with 6000 features whereas dataset with 30000 features set got trained in 3 hours. I am not able to get how is this possible that data with 30000 features got trained so quickly compared to the dataset having less number of features. Regards, Abhimanyu
