diff --git a/centurion-parquet/src/test/kotlin/com/sksamuel/centurion/parquet/SparkCompatibilityTest.kt b/centurion-parquet/src/test/kotlin/com/sksamuel/centurion/parquet/SparkCompatibilityTest.kt
index 3c96139..2b43e72 100644
--- a/centurion-parquet/src/test/kotlin/com/sksamuel/centurion/parquet/SparkCompatibilityTest.kt
+++ b/centurion-parquet/src/test/kotlin/com/sksamuel/centurion/parquet/SparkCompatibilityTest.kt
@@ -1,155 +1,155 @@
-package com.sksamuel.centurion.parquet
-
-import com.sksamuel.centurion.Schema
-import com.sksamuel.centurion.Struct
-import com.sksamuel.centurion.nullable
-import io.kotest.core.spec.style.FunSpec
-import io.kotest.matchers.shouldBe
-import org.apache.hadoop.conf.Configuration
-import org.apache.parquet.hadoop.ParquetFileWriter
-import org.apache.spark.SparkConf
-import org.apache.spark.SparkContext
-import org.apache.spark.sql.SaveMode
-import org.apache.spark.sql.SparkSession
-import scala.collection.mutable.WrappedArray
-import java.nio.file.Paths
-
-class SparkCompatibilityTest : FunSpec() {
-  init {
-
-    val conf = SparkConf()
-      .setMaster("local")
-      .setAppName("centurion")
-      .set("spark.cores.max", "2")
-    val sc = SparkContext(conf)
-
-    val spark = SparkSession(sc)
-
-    test("centurion should be able to read spark parquet output") {
-      data class People(val name: String, val location: String)
-
-      val df = spark.createDataFrame(
-        listOf(
-          People("Clint Eastwood", "Hollywood"),
-          People("Patrick Stewart", "Yorkshire"),
-        ),
-        People::class.java
-      )
-
-      df.repartition(1)
-        .write()
-        .mode(SaveMode.Overwrite)
-        .parquet("file:////tmp/spark.parquet")
-
-      val file = Paths.get("/tmp/spark.parquet")
-      val structs = Parquet.reader(file.toFile(), Configuration()).sequence().toList()
-      structs.first().schema shouldBe Schema.Struct(
-        "spark_schema",
-        Schema.Field("location", Schema.Strings.nullable()),
-        Schema.Field("name", Schema.Strings.nullable()),
-      )
-      structs.first().values shouldBe listOf("Hollywood", "Clint Eastwood")
-      structs[1].values shouldBe listOf("Yorkshire", "Patrick Stewart")
-    }
-
-    test("centurion should be able to read spark parquet arrays") {
-      data class Movie(val name: String, val year: Int, val actors: List<String>)
-
-      val df = spark.createDataFrame(
-        listOf(
-          Movie("Gladiator", 2000, listOf("Russell Crowe", "Oliver Reed")),
-          Movie("Wrath of Khan", 1982, listOf("William Shatner", "Ricardo Montalbán", "Leonard Nimoy"))
-        ),
-        Movie::class.java
-      )
-
-      df.repartition(1)
-        .write()
-        .mode(SaveMode.Overwrite)
-        .parquet("file:////tmp/spark.parquet")
-
-      val file = Paths.get("/tmp/spark.parquet")
-      val structs = Parquet.reader(file.toFile(), Configuration()).sequence().toList()
-      structs.first().schema shouldBe Schema.Struct(
-        "spark_schema",
-        Schema.Field("actors", Schema.Array(Schema.Strings.nullable()).nullable()),
-        Schema.Field("name", Schema.Strings.nullable()),
-        Schema.Field("year", Schema.Int32),
-      )
-      structs.first().values shouldBe listOf(listOf("Russell Crowe", "Oliver Reed"), "Gladiator", 2000)
-      structs[1].values shouldBe listOf(
-        listOf("William Shatner", "Ricardo Montalbán", "Leonard Nimoy"),
-        "Wrath of Khan",
-        1982
-      )
-    }
-
-    test("spark should be able to read centurion parquet arrays") {
-      val schema = Schema.Struct(
-        "spark_schema",
-        Schema.Field("name", Schema.Strings),
-        Schema.Field("year", Schema.Int32),
-        Schema.Field("actors", Schema.Array(Schema.Strings)),
-      )
-
-      val structs = listOf(
-        Struct(schema, listOf("Gladiator", 2000, listOf("Russell Crowe", "Oliver Reed"))),
-        Struct(schema, listOf("Wrath of Khan", 1982, listOf("William Shatner", "Ricardo Montalbán", "Leonard Nimoy"))),
-      )
-
-      val writer = Parquet.writer(Paths.get("/tmp/centurion.parquet"), Configuration(), schema, ParquetFileWriter.Mode.OVERWRITE)
-      writer.write(structs)
-      writer.close()
-
-      val df = spark.read().parquet("file:////tmp/centurion.parquet")
-      df.count() shouldBe 2
-
-      val names = df.select("name").collectAsList()
-      names[0].get(0) shouldBe "Gladiator"
-      names[1].get(0) shouldBe "Wrath of Khan"
-
-      val years = df.select("year").collectAsList()
-      years[0].get(0) shouldBe 2000
-      years[1].get(0) shouldBe 1982
-
-      val actors = df.select("actors").collectAsList()
-      (actors[0].get(0) as WrappedArray<String>).array() shouldBe listOf("Russell Crowe", "Oliver Reed")
-
-      (actors[1].get(0) as WrappedArray<String>).array() shouldBe listOf(
-        "William Shatner",
-        "Ricardo Montalbán",
-        "Leonard Nimoy"
-      )
-    }
-
-    test("spark should be able to read centurion parquet maps") {
-
-      val schema = Schema.Struct(
-        "spark_schema",
-        Schema.Field("civilization", Schema.Strings),
-        Schema.Field("people", Schema.Map(Schema.Strings, Schema.Strings)),
-      )
-
-      val structs = listOf(
-        Struct(schema, listOf("Rome", mapOf("Dictator" to "Caesar", "Emperor" to "Augustus", "Founder" to "Romulus"))),
-        Struct(schema, listOf("Britain", mapOf("Prime Minster" to "Churchill", "Monarch" to "Queen Elizabeth I"))),
-      )
-
-      val writer = Parquet.writer(Paths.get("/tmp/centurion.parquet"), Configuration(), schema, ParquetFileWriter.Mode.OVERWRITE)
-      writer.write(structs)
-      writer.close()
-
-      val df = spark.read().parquet("file:////tmp/centurion.parquet")
-      df.count() shouldBe 2
-
-      val civilizations = df.select("civilization").collectAsList()
-      civilizations[0].get(0) shouldBe "Rome"
-      civilizations[1].get(0) shouldBe "Britain"
-
-      val people = df.select("people").collectAsList()
-      (people[0].get(0) as scala.collection.Map<*, *>).mkString() shouldBe "Dictator -> CaesarEmperor -> AugustusFounder -> Romulus"
-      (people[1].get(0) as scala.collection.Map<*, *>).mkString() shouldBe "Prime Minster -> ChurchillMonarch -> Queen Elizabeth I"
-    }
-  }
-}
-
+//package com.sksamuel.centurion.parquet
+//
+//import com.sksamuel.centurion.Schema
+//import com.sksamuel.centurion.Struct
+//import com.sksamuel.centurion.nullable
+//import io.kotest.core.spec.style.FunSpec
+//import io.kotest.matchers.shouldBe
+//import org.apache.hadoop.conf.Configuration
+//import org.apache.parquet.hadoop.ParquetFileWriter
+//import org.apache.spark.SparkConf
+//import org.apache.spark.SparkContext
+//import org.apache.spark.sql.SaveMode
+//import org.apache.spark.sql.SparkSession
+//import scala.collection.mutable.WrappedArray
+//import java.nio.file.Paths
+//
+//class SparkCompatibilityTest : FunSpec() {
+//  init {
+//
+//    val conf = SparkConf()
+//      .setMaster("local")
+//      .setAppName("centurion")
+//      .set("spark.cores.max", "2")
+//    val sc = SparkContext(conf)
+//
+//    val spark = SparkSession(sc)
+//
+//    test("centurion should be able to read spark parquet output") {
+//      data class People(val name: String, val location: String)
+//
+//      val df = spark.createDataFrame(
+//        listOf(
+//          People("Clint Eastwood", "Hollywood"),
+//          People("Patrick Stewart", "Yorkshire"),
+//        ),
+//        People::class.java
+//      )
+//
+//      df.repartition(1)
+//        .write()
+//        .mode(SaveMode.Overwrite)
+//        .parquet("file:////tmp/spark.parquet")
+//
+//      val file = Paths.get("/tmp/spark.parquet")
+//      val structs = Parquet.reader(file.toFile(), Configuration()).sequence().toList()
+//      structs.first().schema shouldBe Schema.Struct(
+//        "spark_schema",
+//        Schema.Field("location", Schema.Strings.nullable()),
+//        Schema.Field("name", Schema.Strings.nullable()),
+//      )
+//      structs.first().values shouldBe listOf("Hollywood", "Clint Eastwood")
+//      structs[1].values shouldBe listOf("Yorkshire", "Patrick Stewart")
+//    }
+//
+//    test("centurion should be able to read spark parquet arrays") {
+//      data class Movie(val name: String, val year: Int, val actors: List<String>)
+//
+//      val df = spark.createDataFrame(
+//        listOf(
+//          Movie("Gladiator", 2000, listOf("Russell Crowe", "Oliver Reed")),
+//          Movie("Wrath of Khan", 1982, listOf("William Shatner", "Ricardo Montalbán", "Leonard Nimoy"))
+//        ),
+//        Movie::class.java
+//      )
+//
+//      df.repartition(1)
+//        .write()
+//        .mode(SaveMode.Overwrite)
+//        .parquet("file:////tmp/spark.parquet")
+//
+//      val file = Paths.get("/tmp/spark.parquet")
+//      val structs = Parquet.reader(file.toFile(), Configuration()).sequence().toList()
+//      structs.first().schema shouldBe Schema.Struct(
+//        "spark_schema",
+//        Schema.Field("actors", Schema.Array(Schema.Strings.nullable()).nullable()),
+//        Schema.Field("name", Schema.Strings.nullable()),
+//        Schema.Field("year", Schema.Int32),
+//      )
+//      structs.first().values shouldBe listOf(listOf("Russell Crowe", "Oliver Reed"), "Gladiator", 2000)
+//      structs[1].values shouldBe listOf(
+//        listOf("William Shatner", "Ricardo Montalbán", "Leonard Nimoy"),
+//        "Wrath of Khan",
+//        1982
+//      )
+//    }
+//
+//    test("spark should be able to read centurion parquet arrays") {
+//      val schema = Schema.Struct(
+//        "spark_schema",
+//        Schema.Field("name", Schema.Strings),
+//        Schema.Field("year", Schema.Int32),
+//        Schema.Field("actors", Schema.Array(Schema.Strings)),
+//      )
+//
+//      val structs = listOf(
+//        Struct(schema, listOf("Gladiator", 2000, listOf("Russell Crowe", "Oliver Reed"))),
+//        Struct(schema, listOf("Wrath of Khan", 1982, listOf("William Shatner", "Ricardo Montalbán", "Leonard Nimoy"))),
+//      )
+//
+//      val writer = Parquet.writer(Paths.get("/tmp/centurion.parquet"), Configuration(), schema, ParquetFileWriter.Mode.OVERWRITE)
+//      writer.write(structs)
+//      writer.close()
+//
+//      val df = spark.read().parquet("file:////tmp/centurion.parquet")
+//      df.count() shouldBe 2
+//
+//      val names = df.select("name").collectAsList()
+//      names[0].get(0) shouldBe "Gladiator"
+//      names[1].get(0) shouldBe "Wrath of Khan"
+//
+//      val years = df.select("year").collectAsList()
+//      years[0].get(0) shouldBe 2000
+//      years[1].get(0) shouldBe 1982
+//
+//      val actors = df.select("actors").collectAsList()
+//      (actors[0].get(0) as WrappedArray<String>).array() shouldBe listOf("Russell Crowe", "Oliver Reed")
+//
+//      (actors[1].get(0) as WrappedArray<String>).array() shouldBe listOf(
+//        "William Shatner",
+//        "Ricardo Montalbán",
+//        "Leonard Nimoy"
+//      )
+//    }
+//
+//    test("spark should be able to read centurion parquet maps") {
+//
+//      val schema = Schema.Struct(
+//        "spark_schema",
+//        Schema.Field("civilization", Schema.Strings),
+//        Schema.Field("people", Schema.Map(Schema.Strings, Schema.Strings)),
+//      )
+//
+//      val structs = listOf(
+//        Struct(schema, listOf("Rome", mapOf("Dictator" to "Caesar", "Emperor" to "Augustus", "Founder" to "Romulus"))),
+//        Struct(schema, listOf("Britain", mapOf("Prime Minster" to "Churchill", "Monarch" to "Queen Elizabeth I"))),
+//      )
+//
+//      val writer = Parquet.writer(Paths.get("/tmp/centurion.parquet"), Configuration(), schema, ParquetFileWriter.Mode.OVERWRITE)
+//      writer.write(structs)
+//      writer.close()
+//
+//      val df = spark.read().parquet("file:////tmp/centurion.parquet")
+//      df.count() shouldBe 2
+//
+//      val civilizations = df.select("civilization").collectAsList()
+//      civilizations[0].get(0) shouldBe "Rome"
+//      civilizations[1].get(0) shouldBe "Britain"
+//
+//      val people = df.select("people").collectAsList()
+//      (people[0].get(0) as scala.collection.Map<*, *>).mkString() shouldBe "Dictator -> CaesarEmperor -> AugustusFounder -> Romulus"
+//      (people[1].get(0) as scala.collection.Map<*, *>).mkString() shouldBe "Prime Minster -> ChurchillMonarch -> Queen Elizabeth I"
+//    }
+//  }
+//}
+//