Running custom Java class in PySpark

Question

I'm trying to run a custom HDFS reader class in PySpark. This class is written in Java and I need to access it from PySpark, either from the shell or with spark-submit.

In PySpark, I retrieve the JavaGateway from the SparkContext (sc._gateway).

Say I have a class:

package org.foo.module

public class Foo {

    public int fooMethod() {
        return 1;
    }

}

I've tried to package it into a jar and pass it with the --jar option to pyspark and then running:

from py4j.java_gateway import java_import

jvm = sc._gateway.jvm
java_import(jvm, "org.foo.module.*")

foo = jvm.org.foo.module.Foo()

But I get the error:

Py4JError: Trying to call a package.

Can someone help with this? Thanks.

Answer 1

In PySpark try the following

from py4j.java_gateway import java_import
java_import(sc._gateway.jvm,"org.foo.module.Foo")

func = sc._gateway.jvm.Foo()
func.fooMethod()

Make sure that you have compiled your Java code into a runnable jar and submit the spark job like so

spark-submit --driver-class-path "name_of_your_jar_file.jar" --jars "name_of_your_jar_file.jar" name_of_your_python_file.py