Create Sparkling Water Cloud in Databricks using Python Notebook

I am trying to launch a Sparkling Water cloud within Spark using Databricks. I've attached the H2O library (3.16.0.2), PySparkling (pysparkling 0.4.6), and the Sparkling Water jar (sparkling-water-assembly_2.11-2.1.10-all.jar) to the cluster I'm running (Spark 2.1, Auto-updating Scala 1.1.1).

I succesfully import the required libraries below:

from pysparkling import *
import h2o

Yet when I try to initialize the Sparkling Water cloud using the following commands:

hc = H2OContext.getOrCreate(spark)

H2OContext.getOrCreate(sc)

I get the same error:

NameError: name 'H2OContext' is not defined

NameError                                 Traceback (most recent call last)
<command-4043510449425708> in <module>()
----> 1 H2OContext.getOrCreate(sc)

NameError: name 'H2OContext' is not defined

For what it's worth I can initialize the Sparkling Water cloud using this Scala documentation:

%scala
import org.apache.spark.h2o._
val h2oConf = new H2OConf(sc).set("spark.ui.enabled", "false")
val h2oContext = H2OContext.getOrCreate(sc, h2oConf)

import org.apache.spark.h2o._
h2oConf: org.apache.spark.h2o.H2OConf =
Sparkling Water configuration:
  backend cluster mode : internal
  workers              : None
  cloudName            : sparkling-water-root_app-20171222131625-0000
  flatfile             : true
  clientBasePort       : 54321
  nodeBasePort         : 54321
  cloudTimeout         : 60000
  h2oNodeLog           : INFO
  h2oClientLog         : WARN
  nthreads             : -1
  drddMulFactor        : 10
h2oContext: org.apache.spark.h2o.H2OContext =

Sparkling Water Context:
 * H2O name: sparkling-water-root_app-20171222131625-0000
 * cluster size: 1
 * list of used nodes:
  (executorId, host, port)
  ------------------------
  (x,xx.xxx.xxx.x,54321)
  ------------------------

  Open H2O Flow in browser: http://xx.xxx.xxx.xxx:54321 (CMD + click in Mac OSX)

but this pipeline may not always use Databricks so it needs to be all in PySpark and Databricks doesn't have a corresponding PySpark example.

Thanks in advance.

Solution

For pysparkling, you need to first create a PyPi library for h2o_pysparkling_2.1 since you are using a Spark 2.1 cluster. The library you attached, pysparkling is something different. Also, you do not need to attach all those other libraries as the h2o_pysparkling_2.1 package will already import the other necessary libraries.

Once you do that you can run:

from pysparkling import *

h2oConf = H2OConf(spark)
h2oConf.set("spark.ui.enabled", False)

h2oContext = H2OContext.getOrCreate(spark, h2oConf)