Spark shell started with assembly jar cannot resolve decline's cats dependency - scala

Question

I want to use decline to parse command line parameters for a spark application. I use sbt assembly to create a fat jar and use it in the spark-submit. Unfortunately I get an error
java.lang.NoSuchMethodError: cats.kernel.Semigroup$.catsKernelMonoidForList()Lcats/kernel/Monoid; when the parameters get parsed, example below. To reproduce the error you can check out my github repo.
This is my code:
package example
import cats.implicits._
import com.monovore.decline._
object Minimal {
case class Minimal(input: String, count: Int)
val configOpts: Opts[Minimal] = (
Opts.option[String]("input", "the input"),
Opts.option[Int]("count", "the count")
).mapN(Minimal.apply)
def parseMinimalConfig(
args: Array[String]
): Either[Help, Minimal] = {
val command = Command(name = "min-example", header = "my-header")(configOpts)
command.parse(args)
}
}
and this is my build.sbt:
name := "example"
version := "0.1"
scalaVersion := "2.12.10"
libraryDependencies ++= Seq("com.monovore" %% "decline" % "2.3.0")
This is how I reproduce the error locally (spark version is 3.1.2)
~/playground/decline-test » ~/apache/spark-3.1.2-bin-hadoop3.2/bin/spark-shell --jars "target/scala-2.12/example-assembly-0.1.jar"
22/08/31 14:36:41 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context Web UI available at http://airi:4040
Spark context available as 'sc' (master = local[*], app id = local-1661949407775).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 3.1.2
/_/
Using Scala version 2.12.10 (OpenJDK 64-Bit Server VM, Java 1.8.0_345)
Type in expressions to have them evaluated.
Type :help for more information.
scala> import example.Minimal._
import example.Minimal._
scala> parseMinimalConfig(Array("x", "x"))
java.lang.NoSuchMethodError: cats.kernel.Semigroup$.catsKernelMonoidForList()Lcats/kernel/Monoid;
at com.monovore.decline.Help$.optionList(Help.scala:74)
at com.monovore.decline.Help$.detail(Help.scala:105)
at com.monovore.decline.Help$.fromCommand(Help.scala:50)
at com.monovore.decline.Parser.<init>(Parser.scala:21)
at com.monovore.decline.Command.parse(opts.scala:20)
at example.Minimal$.parseMinimalConfig(Minimal.scala:19)
... 49 elided
scala> :quit
Interestingly adding the assembled jar to the scala classpath does not yield the same error but gives the expected help message. My local scala version is 2.12.16 and the spark scala version is 2.12.10, but I'm unsure whether this can be the cause.
~/playground/decline-test » scala -cp "target/scala-2.12/example-assembly-0.1.jar"
Welcome to Scala 2.12.16-20220611-202836-281c3ee (OpenJDK 64-Bit Server VM, Java 1.8.0_345).
Type in expressions for evaluation. Or try :help.
scala> import example.Minimal._
import example.Minimal._
scala> parseMinimalConfig(Array("x", "x"))
res0: Either[com.monovore.decline.Help,example.Minimal.Minimal] =
Left(Unexpected argument: x
Usage: command --input <string> --count <integer>
our command
Options and flags:
--input <string>
the input
--count <integer>
the count)
scala>
I also tried scala 2.13 with spark 3.2.2 and I got the same error, although need to double check on that.
What could I be missing?

Answer 1

Have you tried using ShadeRules to avoid getting stuck in the dependency hell?
assembly / assemblyShadeRules := Seq(
ShadeRule.rename("org.typelevel.cats.**" -> "repackaged.org.typelevel.cats.#1").inAll,
ShadeRule.rename("cats.**" -> "repackaged.cats.#1").inAll,
)