diff --git a/core/src/main/scala/ai/h2o/sparkling/backend/Writer.scala b/core/src/main/scala/ai/h2o/sparkling/backend/Writer.scala
index 8a5f468827..78e3e027cc 100644
--- a/core/src/main/scala/ai/h2o/sparkling/backend/Writer.scala
+++ b/core/src/main/scala/ai/h2o/sparkling/backend/Writer.scala
@@ -33,8 +33,7 @@ import org.apache.spark.sql.Row
 import org.apache.spark.sql.types._
 import org.apache.spark.{ExposeUtils, TaskContext, ml, mllib}
 
-private[backend] class Writer(nodeDesc: NodeDesc, metadata: WriterMetadata, chunkId: Int)
-  extends Closeable {
+private[backend] class Writer(nodeDesc: NodeDesc, metadata: WriterMetadata, chunkId: Int) extends Closeable {
 
   private val outputStream = H2OChunk.putChunk(
     nodeDesc,
@@ -104,9 +103,9 @@ private[backend] object Writer {
     H2OFrame(metadata.frameId)
   }
 
-  private def perDataFramePartition(
-      metadata: WriterMetadata,
-      uploadPlan: UploadPlan)(context: TaskContext, it: Iterator[Row]): (Int, Long) = {
+  private def perDataFramePartition(metadata: WriterMetadata, uploadPlan: UploadPlan)(
+      context: TaskContext,
+      it: Iterator[Row]): (Int, Long) = {
     val chunkIdx = context.partitionId()
     var numRows = 0
     val domainBuilder = new CategoricalDomainBuilder(metadata.expectedTypes)
diff --git a/core/src/test/scala/ai/h2o/sparkling/backend/converters/DataFrameConverterTestSuite.scala b/core/src/test/scala/ai/h2o/sparkling/backend/converters/DataFrameConverterTestSuite.scala
index c76a5a95db..3d62b83319 100644
--- a/core/src/test/scala/ai/h2o/sparkling/backend/converters/DataFrameConverterTestSuite.scala
+++ b/core/src/test/scala/ai/h2o/sparkling/backend/converters/DataFrameConverterTestSuite.scala
@@ -255,7 +255,9 @@ class DataFrameConverterTestSuite extends FunSuite with SharedH2OTestContext {
   test("DataFrame is evaluated only once during conversion to H2OFrame") {
     val numberOfEvaluationsAccumulator = spark.sparkContext.longAccumulator("NumberOfEvaluationsAccumulator")
     val baseDF = spark.range(1000).repartition(1)
-    val finalDF = baseDF.mapPartitions { partitions => numberOfEvaluationsAccumulator.add(1); partitions }
+    val finalDF = baseDF.mapPartitions { partitions =>
+      numberOfEvaluationsAccumulator.add(1); partitions
+    }
 
     val h2oFrame = hc.asH2OFrame(finalDF)
     h2oFrame.delete()
diff --git a/extensions/src/main/scala/ai/h2o/sparkling/extensions/rest/api/ChunkServlet.scala b/extensions/src/main/scala/ai/h2o/sparkling/extensions/rest/api/ChunkServlet.scala
index ed41ebab76..fc36e91ccb 100644
--- a/extensions/src/main/scala/ai/h2o/sparkling/extensions/rest/api/ChunkServlet.scala
+++ b/extensions/src/main/scala/ai/h2o/sparkling/extensions/rest/api/ChunkServlet.scala
@@ -187,11 +187,7 @@ final class ChunkServlet extends ServletBase {
       withResource(request.getInputStream) { inputStream =>
         withResource(Compression.decompress(parameters.compression, inputStream)) { decompressed =>
           withResource(new ChunkAutoBufferReader(decompressed)) { reader =>
-            reader.readChunk(
-              parameters.frameName,
-              parameters.chunkId,
-              parameters.expectedTypes,
-              parameters.maxVecSizes)
+            reader.readChunk(parameters.frameName, parameters.chunkId, parameters.expectedTypes, parameters.maxVecSizes)
           }
         }
       }
diff --git a/extensions/src/main/scala/ai/h2o/sparkling/extensions/serde/ChunkAutoBufferReader.scala b/extensions/src/main/scala/ai/h2o/sparkling/extensions/serde/ChunkAutoBufferReader.scala
index c6c021e0e8..9a1b523c9e 100644
--- a/extensions/src/main/scala/ai/h2o/sparkling/extensions/serde/ChunkAutoBufferReader.scala
+++ b/extensions/src/main/scala/ai/h2o/sparkling/extensions/serde/ChunkAutoBufferReader.scala
@@ -29,11 +29,7 @@ final class ChunkAutoBufferReader(val inputStream: InputStream) extends Closeabl
   private val buffer = new AutoBuffer(inputStream)
   private var isLastNAVar: Boolean = false
 
-  def readChunk(
-      frameName: String,
-      chunkId: Int,
-      expectedTypes: Array[ExpectedType],
-      maxVecSizes: Array[Int]): Unit = {
+  def readChunk(frameName: String, chunkId: Int, expectedTypes: Array[ExpectedType], maxVecSizes: Array[Int]): Unit = {
     val vecTypes = SerdeUtils.expectedTypesToVecTypes(expectedTypes, maxVecSizes)
     val elementSizes = getElementSizes(expectedTypes, maxVecSizes)
     val startPositions = getStartPositions(elementSizes)