Hello, *Question 1: *I am new to Spark. I am trying to train classification model on Spark DataFrame. I am using PySpark. And aFrame object in df:ted a Spark DataFrame object in df:
from pyspark.sql.types import * query = """select * from table""" df = sqlContext.sql(query) My question is how to continue extend the code to train models (e.g., classification model etc.) on object df? I have checked many online resources and haven't seen any similar approach like the following: lr = LogisticRegression(maxIter=10, regParam=0.3, elasticNetParam=0.8) # Fit the modellrModel = lr.fit(df) Is it a feasible way to train the model? If yes, where could I find the reference code? *Question 2: *Why in MLib dataframe based API there is no SVM model support, however, in RDD-based APIs there was SVM model? Thanks a lot! Best, Shi
