I'm just starting out on PySpark (and on the pipeline platform Dataiku) and debugging via both Dataiku and PySpark documentation has been quite the challenge. After a lot of searching, it's hard to tell really where the problem can best be fixed. So I want to convert a table from a Redshift/SQL server, that I defined in my Dataiku workflow into a PySpark dataframe. Very simple right? Well...
All of these codes are conjured by default by clicking the PySpark recipe.
First importing:
import pyspark
import dataiku
from dataiku import spark as dkuspark
from pyspark import SparkContext
from pyspark.sql import SQLContext
Then I create the necessary context:
sc = SparkContext.getOrCreate()
sqlContext = SQLContext(sc)
Here is where the issue arises:
some_table = dataiku.Dataset("some_table")
df = dkuspark.get_dataframe(sqlContext, some_table)
After running this last "get_dataframe" method, Py4J now throws me the error:
An error occurred while calling o27.classForName. Trace:
py4j.Py4JException: Method classForName([class java.lang.String]) does not exist
at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:318)
at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:326)
at py4j.Gateway.invoke(Gateway.java:274)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
I spent a couple of hours here trying to understand what could have happened, and it appears that maybe PySpark is having some trouble reading in the column type? Or I'm not sure. I have no idea how this would translate to either PySpark or Dataiku platform, so any help would be tremendous.
