removed commented out code to jupyter-interrupted-fix branch

Author: Jolanrensen

jupyter/src/main/kotlin/org/jetbrains/kotlinx/spark/api/jupyter/SparkStreamingIntegration.kt

@@ -41,63 +41,6 @@ internal class SparkStreamingIntegration : Integration() {
 
         @Language("kts")
         val _1 = listOf(
-//              For when onInterrupt is implemented in the Jupyter kernel
-//            """
-//                 val sscCollection = mutableSetOf<JavaStreamingContext>()
-//            """.trimIndent(),
-//            """
-//                @JvmOverloads
-//                fun withSparkStreaming(
-//                    batchDuration: Duration = Durations.seconds(1L),
-//                    checkpointPath: String? = null,
-//                    hadoopConf: Configuration = SparkHadoopUtil.get().conf(),
-//                    createOnError: Boolean = false,
-//                    props: Map<String, Any> = emptyMap(),
-//                    master: String = SparkConf().get("spark.master", "local[*]"),
-//                    appName: String = "Kotlin Spark Sample",
-//                    timeout: Long = -1L,
-//                    startStreamingContext: Boolean = true,
-//                    func: KSparkStreamingSession.() -> Unit,
-//                ) {
-//
-//                    // will only be set when a new context is created
-//                    var kSparkStreamingSession: KSparkStreamingSession? = null
-//
-//                    val creatingFunc = {
-//                        val sc = SparkConf()
-//                            .setAppName(appName)
-//                            .setMaster(master)
-//                            .setAll(
-//                                props
-//                                    .map { (key, value) -> key X value.toString() }
-//                                    .asScalaIterable()
-//                            )
-//
-//                        val ssc = JavaStreamingContext(sc, batchDuration)
-//                        ssc.checkpoint(checkpointPath)
-//
-//                        kSparkStreamingSession = KSparkStreamingSession(ssc)
-//                        func(kSparkStreamingSession!!)
-//
-//                        ssc
-//                    }
-//
-//                    val ssc = when {
-//                        checkpointPath != null ->
-//                            JavaStreamingContext.getOrCreate(checkpointPath, creatingFunc, hadoopConf, createOnError)
-//
-//                        else -> creatingFunc()
-//                    }
-//                    sscCollection += ssc
-//
-//                    if (startStreamingContext) {
-//                        ssc.start()
-//                        kSparkStreamingSession?.invokeRunAfterStart()
-//                    }
-//                    ssc.awaitTerminationOrTimeout(timeout)
-//                    ssc.stop()
-//                }
-//            """.trimIndent(),
             """
                 println("To start a spark streaming session, simply use `withSparkStreaming { }` inside a cell. To use Spark normally, use `withSpark { }` in a cell, or use `%use spark` to start a Spark session for the whole notebook.")""".trimIndent(),
         ).map(::execute)
@@ -106,22 +49,4 @@ internal class SparkStreamingIntegration : Integration() {
     override fun KotlinKernelHost.onShutdown() = Unit
 
     override fun KotlinKernelHost.afterCellExecution(snippetInstance: Any, result: FieldValue) = Unit
-
-//    For when this feature is implemented in the Jupyter kernel
-//    override fun KotlinKernelHost.onInterrupt() {
-//
-//        @Language("kts")
-//        val _1 = listOf(
-//            """
-//                while (sscCollection.isNotEmpty())
-//                    sscCollection.first().let {
-//                        it.stop()
-//                        sscCollection.remove(it)
-//                    }
-//            """.trimIndent(),
-//            """
-//                println("onInterrupt cleanup!")
-//            """.trimIndent()
-//        ).map(::execute)
-//    }
 }

jupyter/src/test/kotlin/org/jetbrains/kotlinx/spark/api/jupyter/JupyterTests.kt

@@ -28,7 +28,6 @@ import io.kotest.matchers.string.shouldContain
 import io.kotest.matchers.types.shouldBeInstanceOf
 import jupyter.kotlin.DependsOn
 import org.apache.spark.api.java.JavaSparkContext
-import org.apache.spark.streaming.api.java.JavaStreamingContext
 import org.intellij.lang.annotations.Language
 import org.jetbrains.kotlinx.jupyter.EvalRequestData
 import org.jetbrains.kotlinx.jupyter.ReplForJupyter
@@ -264,14 +263,6 @@ class JupyterStreamingTests : ShouldSpec({
     context("Jupyter") {
         withRepl {
 
-            // For when onInterrupt is implemented in the Jupyter kernel
-            xshould("Have sscCollection instance") {
-
-                @Language("kts")
-                val sscCollection = exec("""sscCollection""")
-                sscCollection as? MutableSet<JavaStreamingContext> shouldNotBe null
-            }
-
             should("Not have spark instance") {
                 shouldThrowAny {
                     @Language("kts")