Using Scala classes as UDF with pyspark

Question

I'm trying to offload some computations from Python to Scala when using Apache Spark. I would like to use the class interface from Java to be able to use a persistent variable, like so (this is a nonsensical MWE based on my more complex use case):

package mwe

import org.apache.spark.sql.api.java.UDF1

class SomeFun extends UDF1[Int, Int] {
  private var prop: Int = 0

  override def call(input: Int): Int = {
    if (prop == 0) {
      prop = input
    }
    prop + input
  }
}

Now I'm attempting to use this class from within pyspark:

import pyspark
from pyspark.sql import SQLContext
from pyspark import SparkContext

conf = pyspark.SparkConf()
conf.set("spark.jars", "mwe.jar")
sc = SparkContext.getOrCreate(conf)

sqlContext = SQLContext.getOrCreate(sc)
sqlContext.registerJavaFunction("fun", "mwe.SomeFun")

df0 = sc.parallelize((i,) for i in range(6)).toDF(["num"])
df1 = df0.selectExpr("fun(num) + 3 as new_num")
df1.show()

And get the following exception:

pyspark.sql.utils.AnalysisException: u"cannot resolve '(UDF:fun(num) + 3)' due to data type mismatch: differing types in '(UDF:fun(num) + 3)' (struct<> and int).; line 1 pos 0;\n'Project [(UDF:fun(num#0L) + 3) AS new_num#2]\n+- AnalysisBarrier\n      +- LogicalRDD [num#0L], false\n"

What is the correct way to implement this? Will I have to resort to Java itself for the class? I'd greatly appreciate hints!

zero323 · Accepted Answer · 2018-04-03 15:00:14Z

3

The source of the exception is usage of incompatible types:

First of all o.a.s.sql.api.java.UDF* objects require external Java (not Scala types), so UDF expecting integers should take boxed Integer (java.lang.Integer) not Int.
```
class SomeFun extends UDF1[Integer, Integer] {
  ...
  override def call(input: Integer): Integer = {
    ...
```

Unless you use legacy Python num column uses of LongType not IntegerType:

df0.printSchema()
root
 |-- num: long (nullable = true)

So the actual signature should be

class SomeFun extends UDF1[java.lang.Long, java.lang.Long] {
  ...
  override def call(input: java.lang.Long): java.lang.Long = {
    ...

or data should be casted before applying UDF

df0.selectExpr("fun(cast(num as integer)) + 3 as new_num")

Finally mutable state is not allowed in UDFs. It won't cause an exception but overall behavior will be non-deterministic.

edited Apr 3, 2018 at 15:00

answered Apr 3, 2018 at 14:32

zero323

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1 Comment

matz-e Over a year ago

Thank you! I reproduced this with the MWE and will now have to adapt my other code, as well as see if there is a way around mutable state (determinism is not critical).

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