[SPARK-12692][BUILD][SQL] Scala style: Fix the style violation (Space before "," or ":")

Fix the style violation (space before , and :).
This PR is a followup for #10643.

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #10718 from sarutak/SPARK-12692-followup-sql.

30 files changed, 106 insertions, 101 deletions

diff --git a/sql/core/src/main/scala/org/apache/spark/sql/Column.scala b/sql/core/src/main/scala/org/apache/spark/sql/Column.scala
index e8c61d6e01..a434d03332 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/Column.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/Column.scala
@@ -152,7 +152,7 @@ class Column(protected[sql] val expr: Expression) extends Logging {
    * results into the correct JVM types.
    * @since 1.6.0
    */
-  def as[U : Encoder]: TypedColumn[Any, U] = new TypedColumn[Any, U](expr, encoderFor[U])
+  def as[U: Encoder]: TypedColumn[Any, U] = new TypedColumn[Any, U](expr, encoderFor[U])
 
   /**
    * Extracts a value or values from a complex type.
@@ -171,6 +171,7 @@ class Column(protected[sql] val expr: Expression) extends Logging {
     UnresolvedExtractValue(expr, lit(extraction).expr)
   }
 
+  // scalastyle:off whitespacebeforetoken
   /**
    * Unary minus, i.e. negate the expression.
    * {{{
@@ -202,6 +203,7 @@ class Column(protected[sql] val expr: Expression) extends Logging {
    * @since 1.3.0
    */
   def unary_! : Column = withExpr { Not(expr) }
+  // scalastyle:on whitespacebeforetoken
 
   /**
    * Equality test.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
index 60d2f05b86..fac8950aee 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
@@ -204,7 +204,7 @@ class DataFrame private[sql](
    * @since 1.6.0
    */
   @Experimental
-  def as[U : Encoder]: Dataset[U] = new Dataset[U](sqlContext, logicalPlan)
+  def as[U: Encoder]: Dataset[U] = new Dataset[U](sqlContext, logicalPlan)
 
   /**
    * Returns a new [[DataFrame]] with columns renamed. This can be quite convenient in conversion
@@ -227,7 +227,7 @@ class DataFrame private[sql](
     val newCols = logicalPlan.output.zip(colNames).map { case (oldAttribute, newName) =>
       Column(oldAttribute).as(newName)
     }
-    select(newCols : _*)
+    select(newCols: _*)
   }
 
   /**
@@ -579,7 +579,7 @@ class DataFrame private[sql](
    */
   @scala.annotation.varargs
   def sortWithinPartitions(sortCol: String, sortCols: String*): DataFrame = {
-    sortWithinPartitions((sortCol +: sortCols).map(Column(_)) : _*)
+    sortWithinPartitions((sortCol +: sortCols).map(Column(_)): _*)
   }
 
   /**
@@ -608,7 +608,7 @@ class DataFrame private[sql](
    */
   @scala.annotation.varargs
   def sort(sortCol: String, sortCols: String*): DataFrame = {
-    sort((sortCol +: sortCols).map(apply) : _*)
+    sort((sortCol +: sortCols).map(apply): _*)
   }
 
   /**
@@ -631,7 +631,7 @@ class DataFrame private[sql](
    * @since 1.3.0
    */
   @scala.annotation.varargs
-  def orderBy(sortCol: String, sortCols: String*): DataFrame = sort(sortCol, sortCols : _*)
+  def orderBy(sortCol: String, sortCols: String*): DataFrame = sort(sortCol, sortCols: _*)
 
   /**
    * Returns a new [[DataFrame]] sorted by the given expressions.
@@ -640,7 +640,7 @@ class DataFrame private[sql](
    * @since 1.3.0
    */
   @scala.annotation.varargs
-  def orderBy(sortExprs: Column*): DataFrame = sort(sortExprs : _*)
+  def orderBy(sortExprs: Column*): DataFrame = sort(sortExprs: _*)
 
   /**
    * Selects column based on the column name and return it as a [[Column]].
@@ -720,7 +720,7 @@ class DataFrame private[sql](
    * @since 1.3.0
    */
   @scala.annotation.varargs
-  def select(col: String, cols: String*): DataFrame = select((col +: cols).map(Column(_)) : _*)
+  def select(col: String, cols: String*): DataFrame = select((col +: cols).map(Column(_)): _*)
 
   /**
    * Selects a set of SQL expressions. This is a variant of `select` that accepts
@@ -948,7 +948,7 @@ class DataFrame private[sql](
    * @since 1.3.0
    */
   def agg(aggExpr: (String, String), aggExprs: (String, String)*): DataFrame = {
-    groupBy().agg(aggExpr, aggExprs : _*)
+    groupBy().agg(aggExpr, aggExprs: _*)
   }
 
   /**
@@ -986,7 +986,7 @@ class DataFrame private[sql](
    * @since 1.3.0
    */
   @scala.annotation.varargs
-  def agg(expr: Column, exprs: Column*): DataFrame = groupBy().agg(expr, exprs : _*)
+  def agg(expr: Column, exprs: Column*): DataFrame = groupBy().agg(expr, exprs: _*)
 
   /**
    * Returns a new [[DataFrame]] by taking the first `n` rows. The difference between this function
@@ -1118,7 +1118,7 @@ class DataFrame private[sql](
    * @group dfops
    * @since 1.3.0
    */
-  def explode[A <: Product : TypeTag](input: Column*)(f: Row => TraversableOnce[A]): DataFrame = {
+  def explode[A <: Product: TypeTag](input: Column*)(f: Row => TraversableOnce[A]): DataFrame = {
     val schema = ScalaReflection.schemaFor[A].dataType.asInstanceOf[StructType]
 
     val elementTypes = schema.toAttributes.map {
@@ -1147,7 +1147,7 @@ class DataFrame private[sql](
    * @group dfops
    * @since 1.3.0
    */
-  def explode[A, B : TypeTag](inputColumn: String, outputColumn: String)(f: A => TraversableOnce[B])
+  def explode[A, B: TypeTag](inputColumn: String, outputColumn: String)(f: A => TraversableOnce[B])
     : DataFrame = {
     val dataType = ScalaReflection.schemaFor[B].dataType
     val attributes = AttributeReference(outputColumn, dataType)() :: Nil
@@ -1186,7 +1186,7 @@ class DataFrame private[sql](
           Column(field)
         }
       }
-      select(columns : _*)
+      select(columns: _*)
     } else {
       select(Column("*"), col.as(colName))
     }
@@ -1207,7 +1207,7 @@ class DataFrame private[sql](
           Column(field)
         }
       }
-      select(columns : _*)
+      select(columns: _*)
     } else {
       select(Column("*"), col.as(colName, metadata))
     }
@@ -1231,7 +1231,7 @@ class DataFrame private[sql](
           Column(col)
         }
       }
-      select(columns : _*)
+      select(columns: _*)
     } else {
       this
     }
@@ -1244,7 +1244,7 @@ class DataFrame private[sql](
    * @since 1.4.0
    */
   def drop(colName: String): DataFrame = {
-    drop(Seq(colName) : _*)
+    drop(Seq(colName): _*)
   }
 
   /**
@@ -1283,7 +1283,7 @@ class DataFrame private[sql](
     val colsAfterDrop = attrs.filter { attr =>
       attr != expression
     }.map(attr => Column(attr))
-    select(colsAfterDrop : _*)
+    select(colsAfterDrop: _*)
   }
 
   /**
@@ -1479,7 +1479,7 @@ class DataFrame private[sql](
    * @group action
    * @since 1.6.0
    */
-  def takeAsList(n: Int): java.util.List[Row] = java.util.Arrays.asList(take(n) : _*)
+  def takeAsList(n: Int): java.util.List[Row] = java.util.Arrays.asList(take(n): _*)
 
   /**
    * Returns an array that contains all of [[Row]]s in this [[DataFrame]].
@@ -1505,7 +1505,7 @@ class DataFrame private[sql](
    */
   def collectAsList(): java.util.List[Row] = withCallback("collectAsList", this) { _ =>
     withNewExecutionId {
-      java.util.Arrays.asList(rdd.collect() : _*)
+      java.util.Arrays.asList(rdd.collect(): _*)
     }
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala
index 3b30337f1f..4441a634be 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameHolder.scala
@@ -33,5 +33,5 @@ case class DataFrameHolder private[sql](private val df: DataFrame) {
   // `rdd.toDF("1")` as invoking this toDF and then apply on the returned DataFrame.
   def toDF(): DataFrame = df
 
-  def toDF(colNames: String*): DataFrame = df.toDF(colNames : _*)
+  def toDF(colNames: String*): DataFrame = df.toDF(colNames: _*)
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
index f7be5f6b37..43500b09e0 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala
@@ -164,7 +164,7 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
         df.col(f.name)
       }
     }
-    df.select(projections : _*)
+    df.select(projections: _*)
   }
 
   /**
@@ -191,7 +191,7 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
         df.col(f.name)
       }
     }
-    df.select(projections : _*)
+    df.select(projections: _*)
   }
 
   /**
@@ -364,7 +364,7 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
         df.col(f.name)
       }
     }
-    df.select(projections : _*)
+    df.select(projections: _*)
   }
 
   private def fill0(values: Seq[(String, Any)]): DataFrame = {
@@ -395,7 +395,7 @@ final class DataFrameNaFunctions private[sql](df: DataFrame) {
         }
       }.getOrElse(df.col(f.name))
     }
-    df.select(projections : _*)
+    df.select(projections: _*)
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
index d948e48942..1ed451d5a8 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala
@@ -203,7 +203,7 @@ class DataFrameReader private[sql](sqlContext: SQLContext) extends Logging {
       predicates: Array[String],
       connectionProperties: Properties): DataFrame = {
     val parts: Array[Partition] = predicates.zipWithIndex.map { case (part, i) =>
-      JDBCPartition(part, i) : Partition
+      JDBCPartition(part, i): Partition
     }
     jdbc(url, table, parts, connectionProperties)
   }
@@ -262,7 +262,7 @@ class DataFrameReader private[sql](sqlContext: SQLContext) extends Logging {
    *
    * @since 1.6.0
    */
-  def json(paths: String*): DataFrame = format("json").load(paths : _*)
+  def json(paths: String*): DataFrame = format("json").load(paths: _*)
 
   /**
    * Loads an `JavaRDD[String]` storing JSON objects (one object per record) and
@@ -355,7 +355,7 @@ class DataFrameReader private[sql](sqlContext: SQLContext) extends Logging {
    * @since 1.6.0
    */
   @scala.annotation.varargs
-  def text(paths: String*): DataFrame = format("text").load(paths : _*)
+  def text(paths: String*): DataFrame = format("text").load(paths: _*)
 
   ///////////////////////////////////////////////////////////////////////////////////////
   // Builder pattern config options
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala b/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
index 42f01e9359..9ffb5b94b2 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
@@ -131,7 +131,7 @@ class Dataset[T] private[sql](
    * along with `alias` or `as` to rearrange or rename as required.
    * @since 1.6.0
    */
-  def as[U : Encoder]: Dataset[U] = {
+  def as[U: Encoder]: Dataset[U] = {
     new Dataset(sqlContext, queryExecution, encoderFor[U])
   }
 
@@ -318,7 +318,7 @@ class Dataset[T] private[sql](
    * Returns a new [[Dataset]] that contains the result of applying `func` to each element.
    * @since 1.6.0
    */
-  def map[U : Encoder](func: T => U): Dataset[U] = mapPartitions(_.map(func))
+  def map[U: Encoder](func: T => U): Dataset[U] = mapPartitions(_.map(func))
 
   /**
    * (Java-specific)
@@ -333,7 +333,7 @@ class Dataset[T] private[sql](
    * Returns a new [[Dataset]] that contains the result of applying `func` to each partition.
    * @since 1.6.0
    */
-  def mapPartitions[U : Encoder](func: Iterator[T] => Iterator[U]): Dataset[U] = {
+  def mapPartitions[U: Encoder](func: Iterator[T] => Iterator[U]): Dataset[U] = {
     new Dataset[U](
       sqlContext,
       MapPartitions[T, U](
@@ -360,7 +360,7 @@ class Dataset[T] private[sql](
    * and then flattening the results.
    * @since 1.6.0
    */
-  def flatMap[U : Encoder](func: T => TraversableOnce[U]): Dataset[U] =
+  def flatMap[U: Encoder](func: T => TraversableOnce[U]): Dataset[U] =
     mapPartitions(_.flatMap(func))
 
   /**
@@ -432,7 +432,7 @@ class Dataset[T] private[sql](
    * Returns a [[GroupedDataset]] where the data is grouped by the given key `func`.
    * @since 1.6.0
    */
-  def groupBy[K : Encoder](func: T => K): GroupedDataset[K, T] = {
+  def groupBy[K: Encoder](func: T => K): GroupedDataset[K, T] = {
     val inputPlan = logicalPlan
     val withGroupingKey = AppendColumns(func, resolvedTEncoder, inputPlan)
     val executed = sqlContext.executePlan(withGroupingKey)
@@ -566,14 +566,14 @@ class Dataset[T] private[sql](
    * Returns a new [[Dataset]] by sampling a fraction of records.
    * @since 1.6.0
    */
-  def sample(withReplacement: Boolean, fraction: Double, seed: Long) : Dataset[T] =
+  def sample(withReplacement: Boolean, fraction: Double, seed: Long): Dataset[T] =
     withPlan(Sample(0.0, fraction, withReplacement, seed, _))
 
   /**
    * Returns a new [[Dataset]] by sampling a fraction of records, using a random seed.
    * @since 1.6.0
    */
-  def sample(withReplacement: Boolean, fraction: Double) : Dataset[T] = {
+  def sample(withReplacement: Boolean, fraction: Double): Dataset[T] = {
     sample(withReplacement, fraction, Utils.random.nextLong)
   }
 
@@ -731,7 +731,7 @@ class Dataset[T] private[sql](
    * a very large `num` can crash the driver process with OutOfMemoryError.
    * @since 1.6.0
    */
-  def takeAsList(num: Int): java.util.List[T] = java.util.Arrays.asList(take(num) : _*)
+  def takeAsList(num: Int): java.util.List[T] = java.util.Arrays.asList(take(num): _*)
 
   /**
     * Persist this [[Dataset]] with the default storage level (`MEMORY_AND_DISK`).
@@ -786,7 +786,7 @@ class Dataset[T] private[sql](
   private[sql] def withPlan(f: LogicalPlan => LogicalPlan): Dataset[T] =
     new Dataset[T](sqlContext, sqlContext.executePlan(f(logicalPlan)), tEncoder)
 
-  private[sql] def withPlan[R : Encoder](
+  private[sql] def withPlan[R: Encoder](
       other: Dataset[_])(
       f: (LogicalPlan, LogicalPlan) => LogicalPlan): Dataset[R] =
     new Dataset[R](sqlContext, f(logicalPlan, other.logicalPlan))
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala b/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
index c74ef2c035..f5cbf013bc 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/GroupedData.scala
@@ -229,7 +229,7 @@ class GroupedData protected[sql](
    */
   @scala.annotation.varargs
   def mean(colNames: String*): DataFrame = {
-    aggregateNumericColumns(colNames : _*)(Average)
+    aggregateNumericColumns(colNames: _*)(Average)
   }
 
   /**
@@ -241,7 +241,7 @@ class GroupedData protected[sql](
    */
   @scala.annotation.varargs
   def max(colNames: String*): DataFrame = {
-    aggregateNumericColumns(colNames : _*)(Max)
+    aggregateNumericColumns(colNames: _*)(Max)
   }
 
   /**
@@ -253,7 +253,7 @@ class GroupedData protected[sql](
    */
   @scala.annotation.varargs
   def avg(colNames: String*): DataFrame = {
-    aggregateNumericColumns(colNames : _*)(Average)
+    aggregateNumericColumns(colNames: _*)(Average)
   }
 
   /**
@@ -265,7 +265,7 @@ class GroupedData protected[sql](
    */
   @scala.annotation.varargs
   def min(colNames: String*): DataFrame = {
-    aggregateNumericColumns(colNames : _*)(Min)
+    aggregateNumericColumns(colNames: _*)(Min)
   }
 
   /**
@@ -277,7 +277,7 @@ class GroupedData protected[sql](
    */
   @scala.annotation.varargs
   def sum(colNames: String*): DataFrame = {
-    aggregateNumericColumns(colNames : _*)(Sum)
+    aggregateNumericColumns(colNames: _*)(Sum)
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala b/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala
index a819ddceb1..12179367fa 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala
@@ -73,7 +73,7 @@ class GroupedDataset[K, V] private[sql](
    *
    * @since 1.6.0
    */
-  def keyAs[L : Encoder]: GroupedDataset[L, V] =
+  def keyAs[L: Encoder]: GroupedDataset[L, V] =
     new GroupedDataset(
       encoderFor[L],
       unresolvedVEncoder,
@@ -110,7 +110,7 @@ class GroupedDataset[K, V] private[sql](
    *
    * @since 1.6.0
    */
-  def flatMapGroups[U : Encoder](f: (K, Iterator[V]) => TraversableOnce[U]): Dataset[U] = {
+  def flatMapGroups[U: Encoder](f: (K, Iterator[V]) => TraversableOnce[U]): Dataset[U] = {
     new Dataset[U](
       sqlContext,
       MapGroups(
@@ -158,7 +158,7 @@ class GroupedDataset[K, V] private[sql](
    *
    * @since 1.6.0
    */
-  def mapGroups[U : Encoder](f: (K, Iterator[V]) => U): Dataset[U] = {
+  def mapGroups[U: Encoder](f: (K, Iterator[V]) => U): Dataset[U] = {
     val func = (key: K, it: Iterator[V]) => Iterator(f(key, it))
     flatMapGroups(func)
   }
@@ -302,7 +302,7 @@ class GroupedDataset[K, V] private[sql](
    *
    * @since 1.6.0
    */
-  def cogroup[U, R : Encoder](
+  def cogroup[U, R: Encoder](
       other: GroupedDataset[K, U])(
       f: (K, Iterator[V], Iterator[U]) => TraversableOnce[R]): Dataset[R] = {
     new Dataset[R](
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
index e827427c19..61c74f8340 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
@@ -409,7 +409,7 @@ class SQLContext private[sql](
    * @since 1.3.0
    */
   @Experimental
-  def createDataFrame[A <: Product : TypeTag](rdd: RDD[A]): DataFrame = {
+  def createDataFrame[A <: Product: TypeTag](rdd: RDD[A]): DataFrame = {
     SQLContext.setActive(self)
     val schema = ScalaReflection.schemaFor[A].dataType.asInstanceOf[StructType]
     val attributeSeq = schema.toAttributes
@@ -425,7 +425,7 @@ class SQLContext private[sql](
    * @since 1.3.0
    */
   @Experimental
-  def createDataFrame[A <: Product : TypeTag](data: Seq[A]): DataFrame = {
+  def createDataFrame[A <: Product: TypeTag](data: Seq[A]): DataFrame = {
     SQLContext.setActive(self)
     val schema = ScalaReflection.schemaFor[A].dataType.asInstanceOf[StructType]
     val attributeSeq = schema.toAttributes
@@ -498,7 +498,7 @@ class SQLContext private[sql](
   }
 
 
-  def createDataset[T : Encoder](data: Seq[T]): Dataset[T] = {
+  def createDataset[T: Encoder](data: Seq[T]): Dataset[T] = {
     val enc = encoderFor[T]
     val attributes = enc.schema.toAttributes
     val encoded = data.map(d => enc.toRow(d).copy())
@@ -507,7 +507,7 @@ class SQLContext private[sql](
     new Dataset[T](this, plan)
   }
 
-  def createDataset[T : Encoder](data: RDD[T]): Dataset[T] = {
+  def createDataset[T: Encoder](data: RDD[T]): Dataset[T] = {
     val enc = encoderFor[T]
     val attributes = enc.schema.toAttributes
     val encoded = data.map(d => enc.toRow(d))
@@ -516,7 +516,7 @@ class SQLContext private[sql](
     new Dataset[T](this, plan)
   }
 
-  def createDataset[T : Encoder](data: java.util.List[T]): Dataset[T] = {
+  def createDataset[T: Encoder](data: java.util.List[T]): Dataset[T] = {
     createDataset(data.asScala)
   }
 
@@ -945,7 +945,7 @@ class SQLContext private[sql](
     }
   }
 
-  // Register a succesfully instantiatd context to the singleton. This should be at the end of
+  // Register a successfully instantiated context to the singleton. This should be at the end of
   // the class definition so that the singleton is updated only if there is no exception in the
   // construction of the instance.
   sparkContext.addSparkListener(new SparkListener {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLImplicits.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLImplicits.scala
index ab414799f1..a7f7997df1 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SQLImplicits.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLImplicits.scala
@@ -37,7 +37,7 @@ abstract class SQLImplicits {
   protected def _sqlContext: SQLContext
 
   /** @since 1.6.0 */
-  implicit def newProductEncoder[T <: Product : TypeTag]: Encoder[T] = ExpressionEncoder()
+  implicit def newProductEncoder[T <: Product: TypeTag]: Encoder[T] = ExpressionEncoder()
 
   /** @since 1.6.0 */
   implicit def newIntEncoder: Encoder[Int] = ExpressionEncoder()
@@ -67,7 +67,7 @@ abstract class SQLImplicits {
    * Creates a [[Dataset]] from an RDD.
    * @since 1.6.0
    */
-  implicit def rddToDatasetHolder[T : Encoder](rdd: RDD[T]): DatasetHolder[T] = {
+  implicit def rddToDatasetHolder[T: Encoder](rdd: RDD[T]): DatasetHolder[T] = {
     DatasetHolder(_sqlContext.createDataset(rdd))
   }
 
@@ -75,7 +75,7 @@ abstract class SQLImplicits {
    * Creates a [[Dataset]] from a local Seq.
    * @since 1.6.0
    */
-  implicit def localSeqToDatasetHolder[T : Encoder](s: Seq[T]): DatasetHolder[T] = {
+  implicit def localSeqToDatasetHolder[T: Encoder](s: Seq[T]): DatasetHolder[T] = {
     DatasetHolder(_sqlContext.createDataset(s))
   }
 
@@ -89,7 +89,7 @@ abstract class SQLImplicits {
    * Creates a DataFrame from an RDD of Product (e.g. case classes, tuples).
    * @since 1.3.0
    */
-  implicit def rddToDataFrameHolder[A <: Product : TypeTag](rdd: RDD[A]): DataFrameHolder = {
+  implicit def rddToDataFrameHolder[A <: Product: TypeTag](rdd: RDD[A]): DataFrameHolder = {
     DataFrameHolder(_sqlContext.createDataFrame(rdd))
   }
 
@@ -97,7 +97,7 @@ abstract class SQLImplicits {
    * Creates a DataFrame from a local Seq of Product.
    * @since 1.3.0
    */
-  implicit def localSeqToDataFrameHolder[A <: Product : TypeTag](data: Seq[A]): DataFrameHolder =
+  implicit def localSeqToDataFrameHolder[A <: Product: TypeTag](data: Seq[A]): DataFrameHolder =
   {
     DataFrameHolder(_sqlContext.createDataFrame(data))
   }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
index d912aeb70d..a8e6a40169 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
@@ -39,7 +39,7 @@ private[r] object SQLUtils {
     new JavaSparkContext(sqlCtx.sparkContext)
   }
 
-  def createStructType(fields : Seq[StructField]): StructType = {
+  def createStructType(fields: Seq[StructField]): StructType = {
     StructType(fields)
   }
 
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala
index 6b10057707..058d147c7d 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala
@@ -223,7 +223,7 @@ case class Exchange(
     new ShuffledRowRDD(shuffleDependency, specifiedPartitionStartIndices)
   }
 
-  protected override def doExecute(): RDD[InternalRow] = attachTree(this , "execute") {
+  protected override def doExecute(): RDD[InternalRow] = attachTree(this, "execute") {
     coordinator match {
       case Some(exchangeCoordinator) =>
         val shuffleRDD = exchangeCoordinator.postShuffleRDD(this)
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/Queryable.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/Queryable.scala
index 38263af0f7..bb55161477 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Queryable.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Queryable.scala
@@ -71,7 +71,7 @@ private[sql] trait Queryable {
   private[sql] def formatString (
       rows: Seq[Seq[String]],
       numRows: Int,
-      hasMoreData : Boolean,
+      hasMoreData: Boolean,
       truncate: Boolean = true): String = {
     val sb = new StringBuilder
     val numCols = schema.fieldNames.length
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TypedAggregateExpression.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TypedAggregateExpression.scala
index 1df38f7ff5..b5ac530444 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TypedAggregateExpression.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TypedAggregateExpression.scala
@@ -29,7 +29,7 @@ import org.apache.spark.sql.expressions.Aggregator
 import org.apache.spark.sql.types._
 
 object TypedAggregateExpression {
-  def apply[A, B : Encoder, C : Encoder](
+  def apply[A, B: Encoder, C: Encoder](
       aggregator: Aggregator[A, B, C]): TypedAggregateExpression = {
     new TypedAggregateExpression(
       aggregator.asInstanceOf[Aggregator[Any, Any, Any]],
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/SqlNewHadoopRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/SqlNewHadoopRDD.scala
index d45d2db62f..d5e0d80076 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/SqlNewHadoopRDD.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/SqlNewHadoopRDD.scala
@@ -256,7 +256,7 @@ private[spark] class SqlNewHadoopRDD[V: ClassTag](
           val infos = c.newGetLocationInfo.invoke(split).asInstanceOf[Array[AnyRef]]
           Some(HadoopRDD.convertSplitLocationInfo(infos))
         } catch {
-          case e : Exception =>
+          case e: Exception =>
             logDebug("Failed to use InputSplit#getLocationInfo.", e)
             None
         }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/CatalystSchemaConverter.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/CatalystSchemaConverter.scala
index fb97a03df6..c4b125e9d5 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/CatalystSchemaConverter.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/CatalystSchemaConverter.scala
@@ -557,7 +557,7 @@ private[parquet] object CatalystSchemaConverter {
     }
   }
 
-  private def computeMinBytesForPrecision(precision : Int) : Int = {
+  private def computeMinBytesForPrecision(precision: Int): Int = {
     var numBytes = 1
     while (math.pow(2.0, 8 * numBytes - 1) < math.pow(10.0, precision)) {
       numBytes += 1
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/CartesianProduct.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/CartesianProduct.scala
index 93d32e1fb9..a567457dba 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/CartesianProduct.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/CartesianProduct.scala
@@ -34,7 +34,7 @@ import org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter
   * materialize the right RDD (in case of the right RDD is nondeterministic).
   */
 private[spark]
-class UnsafeCartesianRDD(left : RDD[UnsafeRow], right : RDD[UnsafeRow], numFieldsOfRight: Int)
+class UnsafeCartesianRDD(left: RDD[UnsafeRow], right: RDD[UnsafeRow], numFieldsOfRight: Int)
   extends CartesianRDD[UnsafeRow, UnsafeRow](left.sparkContext, left, right) {
 
   override def compute(split: Partition, context: TaskContext): Iterator[(UnsafeRow, UnsafeRow)] = {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/metric/SQLMetrics.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/metric/SQLMetrics.scala
index 52735c9d7f..8c68d9ee0a 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/metric/SQLMetrics.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/metric/SQLMetrics.scala
@@ -64,7 +64,7 @@ private[sql] trait SQLMetricValue[T] extends Serializable {
 /**
  * A wrapper of Long to avoid boxing and unboxing when using Accumulator
  */
-private[sql] class LongSQLMetricValue(private var _value : Long) extends SQLMetricValue[Long] {
+private[sql] class LongSQLMetricValue(private var _value: Long) extends SQLMetricValue[Long] {
 
   def add(incr: Long): LongSQLMetricValue = {
     _value += incr
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
index a191759813..a4cb54e2bf 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala
@@ -94,7 +94,7 @@ private[sql] object FrequentItems extends Logging {
       (name, originalSchema.fields(index).dataType)
     }.toArray
 
-    val freqItems = df.select(cols.map(Column(_)) : _*).rdd.aggregate(countMaps)(
+    val freqItems = df.select(cols.map(Column(_)): _*).rdd.aggregate(countMaps)(
       seqOp = (counts, row) => {
         var i = 0
         while (i < numCols) {
@@ -115,7 +115,7 @@ private[sql] object FrequentItems extends Logging {
       }
     )
     val justItems = freqItems.map(m => m.baseMap.keys.toArray)
-    val resultRow = Row(justItems : _*)
+    val resultRow = Row(justItems: _*)
     // append frequent Items to the column name for easy debugging
     val outputCols = colInfo.map { v =>
       StructField(v._1 + "_freqItems", ArrayType(v._2, false))
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/expressions/Window.scala b/sql/core/src/main/scala/org/apache/spark/sql/expressions/Window.scala
index e9b60841fc..05a9f377b9 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/expressions/Window.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/expressions/Window.scala
@@ -44,7 +44,7 @@ object Window {
    */
   @scala.annotation.varargs
   def partitionBy(colName: String, colNames: String*): WindowSpec = {
-    spec.partitionBy(colName, colNames : _*)
+    spec.partitionBy(colName, colNames: _*)
   }
 
   /**
@@ -53,7 +53,7 @@ object Window {
    */
   @scala.annotation.varargs
   def partitionBy(cols: Column*): WindowSpec = {
-    spec.partitionBy(cols : _*)
+    spec.partitionBy(cols: _*)
   }
 
   /**
@@ -62,7 +62,7 @@ object Window {
    */
   @scala.annotation.varargs
   def orderBy(colName: String, colNames: String*): WindowSpec = {
-    spec.orderBy(colName, colNames : _*)
+    spec.orderBy(colName, colNames: _*)
   }
 
   /**
@@ -71,7 +71,7 @@ object Window {
    */
   @scala.annotation.varargs
   def orderBy(cols: Column*): WindowSpec = {
-    spec.orderBy(cols : _*)
+    spec.orderBy(cols: _*)
   }
 
   private def spec: WindowSpec = {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
index 592d79df31..1ac62883a6 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
@@ -306,7 +306,7 @@ object functions extends LegacyFunctions {
    */
   @scala.annotation.varargs
   def countDistinct(columnName: String, columnNames: String*): Column =
-    countDistinct(Column(columnName), columnNames.map(Column.apply) : _*)
+    countDistinct(Column(columnName), columnNames.map(Column.apply): _*)
 
   /**
    * Aggregate function: returns the first value in a group.
@@ -768,7 +768,7 @@ object functions extends LegacyFunctions {
    */
   @scala.annotation.varargs
   def array(colName: String, colNames: String*): Column = {
-    array((colName +: colNames).map(col) : _*)
+    array((colName +: colNames).map(col): _*)
   }
 
   /**
@@ -977,7 +977,7 @@ object functions extends LegacyFunctions {
    */
   @scala.annotation.varargs
   def struct(colName: String, colNames: String*): Column = {
-    struct((colName +: colNames).map(col) : _*)
+    struct((colName +: colNames).map(col): _*)
   }
 
   /**
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/AggregatedDialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/AggregatedDialect.scala
index 467d8d62d1..d2c31d6e04 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/AggregatedDialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/AggregatedDialect.scala
@@ -30,7 +30,7 @@ private class AggregatedDialect(dialects: List[JdbcDialect]) extends JdbcDialect
 
   require(dialects.nonEmpty)
 
-  override def canHandle(url : String): Boolean =
+  override def canHandle(url: String): Boolean =
     dialects.map(_.canHandle(url)).reduce(_ && _)
 
   override def getCatalystType(
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
index ca2d909e2c..8d58321d48 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
@@ -31,7 +31,7 @@ import org.apache.spark.sql.types._
  *                     send a null value to the database.
  */
 @DeveloperApi
-case class JdbcType(databaseTypeDefinition : String, jdbcNullType : Int)
+case class JdbcType(databaseTypeDefinition: String, jdbcNullType: Int)
 
 /**
  * :: DeveloperApi ::
@@ -60,7 +60,7 @@ abstract class JdbcDialect extends Serializable {
    * @return True if the dialect can be applied on the given jdbc url.
    * @throws NullPointerException if the url is null.
    */
-  def canHandle(url : String): Boolean
+  def canHandle(url: String): Boolean
 
   /**
    * Get the custom datatype mapping for the given jdbc meta information.
@@ -130,7 +130,7 @@ object JdbcDialects {
    *
    * @param dialect The new dialect.
    */
-  def registerDialect(dialect: JdbcDialect) : Unit = {
+  def registerDialect(dialect: JdbcDialect): Unit = {
     dialects = dialect :: dialects.filterNot(_ == dialect)
   }
 
@@ -139,7 +139,7 @@ object JdbcDialects {
    *
    * @param dialect The jdbc dialect.
    */
-  def unregisterDialect(dialect : JdbcDialect) : Unit = {
+  def unregisterDialect(dialect: JdbcDialect): Unit = {
     dialects = dialects.filterNot(_ == dialect)
   }
 
@@ -169,5 +169,5 @@ object JdbcDialects {
  * NOOP dialect object, always returning the neutral element.
  */
 private object NoopDialect extends JdbcDialect {
-  override def canHandle(url : String): Boolean = true
+  override def canHandle(url: String): Boolean = true
 }
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/MySQLDialect.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/MySQLDialect.scala
index e1717049f3..faae54e605 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/MySQLDialect.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/MySQLDialect.scala
@@ -23,10 +23,13 @@ import org.apache.spark.sql.types.{BooleanType, DataType, LongType, MetadataBuil
 
 private case object MySQLDialect extends JdbcDialect {
 
-  override def canHandle(url : String): Boolean = url.startsWith("jdbc:mysql")
+  override def canHandle(url: String): Boolean = url.startsWith("jdbc:mysql")
 
   override def getCatalystType(
-      sqlType: Int, typeName: String, size: Int, md: MetadataBuilder): Option[DataType] = {
+      sqlType: Int,
+      typeName: String,
+      size: Int,
+      md: MetadataBuilder): Option[DataType] = {
     if (sqlType == Types.VARBINARY && typeName.equals("BIT") && size != 1) {
       // This could instead be a BinaryType if we'd rather return bit-vectors of up to 64 bits as
       // byte arrays instead of longs.
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetAggregatorSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DatasetAggregatorSuite.scala
index 3258f3782d..f952fc07fd 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetAggregatorSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetAggregatorSuite.scala
@@ -24,7 +24,7 @@ import org.apache.spark.sql.functions._
 import org.apache.spark.sql.test.SharedSQLContext
 
 /** An `Aggregator` that adds up any numeric type returned by the given function. */
-class SumOf[I, N : Numeric](f: I => N) extends Aggregator[I, N, N] {
+class SumOf[I, N: Numeric](f: I => N) extends Aggregator[I, N, N] {
   val numeric = implicitly[Numeric[N]]
 
   override def zero: N = numeric.zero
@@ -113,7 +113,7 @@ class DatasetAggregatorSuite extends QueryTest with SharedSQLContext {
 
   import testImplicits._
 
-  def sum[I, N : Numeric : Encoder](f: I => N): TypedColumn[I, N] =
+  def sum[I, N: Numeric: Encoder](f: I => N): TypedColumn[I, N] =
     new SumOf(f).toColumn
 
   test("typed aggregation: TypedAggregator") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala
index 3a283a4e1f..848f1af655 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala
@@ -27,7 +27,7 @@ class DatasetCacheSuite extends QueryTest with SharedSQLContext {
   import testImplicits._
 
   test("persist and unpersist") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS().select(expr("_2 + 1").as[Int])
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS().select(expr("_2 + 1").as[Int])
     val cached = ds.cache()
     // count triggers the caching action. It should not throw.
     cached.count()
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
index 53b5f45c2d..a3ed2e0616 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
@@ -30,7 +30,7 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
   import testImplicits._
 
   test("toDS") {
-    val data = Seq(("a", 1) , ("b", 2), ("c", 3))
+    val data = Seq(("a", 1), ("b", 2), ("c", 3))
     checkAnswer(
       data.toDS(),
       data: _*)
@@ -87,7 +87,7 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
   }
 
   test("as case class / collect") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDF("a", "b").as[ClassData]
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDF("a", "b").as[ClassData]
     checkAnswer(
       ds,
       ClassData("a", 1), ClassData("b", 2), ClassData("c", 3))
@@ -105,7 +105,7 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
   }
 
   test("map") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     checkAnswer(
       ds.map(v => (v._1, v._2 + 1)),
       ("a", 2), ("b", 3), ("c", 4))
@@ -124,23 +124,23 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
   }
 
   test("select") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     checkAnswer(
       ds.select(expr("_2 + 1").as[Int]),
       2, 3, 4)
   }
 
   test("select 2") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     checkAnswer(
       ds.select(
         expr("_1").as[String],
-        expr("_2").as[Int]) : Dataset[(String, Int)],
+        expr("_2").as[Int]): Dataset[(String, Int)],
       ("a", 1), ("b", 2), ("c", 3))
   }
 
   test("select 2, primitive and tuple") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     checkAnswer(
       ds.select(
         expr("_1").as[String],
@@ -149,7 +149,7 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
   }
 
   test("select 2, primitive and class") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     checkAnswer(
       ds.select(
         expr("_1").as[String],
@@ -158,7 +158,7 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
   }
 
   test("select 2, primitive and class, fields reordered") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     checkDecoding(
       ds.select(
         expr("_1").as[String],
@@ -167,28 +167,28 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
   }
 
   test("filter") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     checkAnswer(
       ds.filter(_._1 == "b"),
       ("b", 2))
   }
 
   test("foreach") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     val acc = sparkContext.accumulator(0)
     ds.foreach(v => acc += v._2)
     assert(acc.value == 6)
   }
 
   test("foreachPartition") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     val acc = sparkContext.accumulator(0)
     ds.foreachPartition(_.foreach(v => acc += v._2))
     assert(acc.value == 6)
   }
 
   test("reduce") {
-    val ds = Seq(("a", 1) , ("b", 2), ("c", 3)).toDS()
+    val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
     assert(ds.reduce((a, b) => ("sum", a._2 + b._2)) == ("sum", 6))
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala
index 4ab148065a..860e07c68c 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonSuite.scala
@@ -206,7 +206,7 @@ class JsonSuite extends QueryTest with SharedSQLContext with TestJsonData {
       StructType(
         StructField("f1", IntegerType, true) ::
         StructField("f2", IntegerType, true) :: Nil),
-      StructType(StructField("f1", LongType, true) :: Nil) ,
+      StructType(StructField("f1", LongType, true) :: Nil),
       StructType(
         StructField("f1", LongType, true) ::
         StructField("f2", IntegerType, true) :: Nil))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala
index ab48e971b5..f2e0a868f4 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala
@@ -72,7 +72,7 @@ class ParquetIOSuite extends QueryTest with ParquetTest with SharedSQLContext {
   /**
    * Writes `data` to a Parquet file, reads it back and check file contents.
    */
-  protected def checkParquetFile[T <: Product : ClassTag: TypeTag](data: Seq[T]): Unit = {
+  protected def checkParquetFile[T <: Product: ClassTag: TypeTag](data: Seq[T]): Unit = {
     withParquetDataFrame(data)(r => checkAnswer(r, data.map(Row.fromTuple)))
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
index 1fa22e2933..984e3fbc05 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala
@@ -46,7 +46,7 @@ class JDBCSuite extends SparkFunSuite
   val testBytes = Array[Byte](99.toByte, 134.toByte, 135.toByte, 200.toByte, 205.toByte)
 
   val testH2Dialect = new JdbcDialect {
-    override def canHandle(url: String) : Boolean = url.startsWith("jdbc:h2")
+    override def canHandle(url: String): Boolean = url.startsWith("jdbc:h2")
     override def getCatalystType(
         sqlType: Int, typeName: String, size: Int, md: MetadataBuilder): Option[DataType] =
       Some(StringType)
@@ -489,7 +489,7 @@ class JDBCSuite extends SparkFunSuite
 
   test("Aggregated dialects") {
     val agg = new AggregatedDialect(List(new JdbcDialect {
-      override def canHandle(url: String) : Boolean = url.startsWith("jdbc:h2:")
+      override def canHandle(url: String): Boolean = url.startsWith("jdbc:h2:")
       override def getCatalystType(
           sqlType: Int, typeName: String, size: Int, md: MetadataBuilder): Option[DataType] =
         if (sqlType % 2 == 0) {