Feature Store & Sparkling Water integration

Python Sparkling Water

1. In a Python environment, pip install the featurestore client.
2. Download spark and pysparkling by following the instructions from the Sparkling Water documentation.
3. Start the pysparkling session with the Spark dependencies.

./bin/pysparkling --jars <spark dependency jar file>

Example:

from featurestore import Client
ref = fs.retrieve()
data_frame = ref.as_spark_frame(spark)

# sparklingwater
from pysparkling import *
hc = H2OContext.getOrCreate()
from pysparkling.ml import H2OGLM
estimator = H2OGLM(labelCol = "RainTomorrow")
model = estimator.fit(data_frame)

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