address comments

Author: clockfly

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala

@@ -42,7 +42,7 @@ import org.apache.spark.sql.types._
  *                             a array of percentage values. Each percentage value must be between
  *                             0.0 and 1.0.
  * @param accuracyExpression Integer literal expression of approximation accuracy. Higher value
- *                           yield better accuracy, the default value is
+ *                           yields better accuracy, the default value is
  *                           DEFAULT_PERCENTILE_ACCURACY.
  */
 @ExpressionDescription(
@@ -51,14 +51,14 @@ import org.apache.spark.sql.types._
       _FUNC_(col, percentage [, accuracy]) - Returns the approximate percentile value of numeric
       column `col` at the given percentage. The value of percentage must be between 0.0
       and 1.0. The `accuracy` parameter (default: 10000) is a positive integer literal which
-      controls approximation accuracy at the cost of memory. Higher value of `accuracy` yield
+      controls approximation accuracy at the cost of memory. Higher value of `accuracy` yields
       better accuracy, `1.0/accuracy` is the relative error of the approximation.
 
       _FUNC_(col, array(percentage1 [, percentage2]...) [, accuracy]) - Returns the approximate
       percentile array of column `col` at the given percentage array. Each value of the
       percentage array must be between 0.0 and 1.0. The `accuracy` parameter (default: 10000) is
        a positive integer literal which controls approximation accuracy at the cost of memory.
-       Higher value of `accuracy` yield better accuracy, `1.0/accuracy` is the relative error of
+       Higher value of `accuracy` yields better accuracy, `1.0/accuracy` is the relative error of
        the approximation.
     """)
 case class ApproximatePercentile(
@@ -92,7 +92,7 @@ case class ApproximatePercentile(
       case (_, num: Double) => (false, Array(num))
       case (ArrayType(baseType: NumericType, _), arrayData: ArrayData) =>
          val numericArray = arrayData.toObjectArray(baseType)
-        (true, numericArray.map {x =>
+        (true, numericArray.map { x =>
           baseType.numeric.toDouble(x.asInstanceOf[baseType.InternalType])
         })
       case other =>