diff --git a/src/main/scala/com/amazon/deequ/VerificationResult.scala b/src/main/scala/com/amazon/deequ/VerificationResult.scala
index b9b450f2..418a622e 100644
--- a/src/main/scala/com/amazon/deequ/VerificationResult.scala
+++ b/src/main/scala/com/amazon/deequ/VerificationResult.scala
@@ -31,7 +31,7 @@ import com.amazon.deequ.repository.SimpleResultSerde
 import org.apache.spark.sql.Column
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.SparkSession
-import org.apache.spark.sql.functions.{col, monotonically_increasing_id}
+import org.apache.spark.sql.functions.monotonically_increasing_id
 
 import java.util.UUID
 
@@ -96,10 +96,9 @@ object VerificationResult {
       data: DataFrame): DataFrame = {
 
     val columnNamesToMetrics: Map[String, Column] = verificationResultToColumn(verificationResult)
-    val columnsAliased = columnNamesToMetrics.toSeq.map { case (name, col) => col.as(name) }
 
     val dataWithID = data.withColumn(UNIQUENESS_ID, monotonically_increasing_id())
-    dataWithID.select(col("*") +: columnsAliased: _*).drop(UNIQUENESS_ID)
+    dataWithID.withColumns(columnNamesToMetrics).drop(UNIQUENESS_ID)
   }
 
   def checkResultsAsJson(verificationResult: VerificationResult,
diff --git a/src/main/scala/com/amazon/deequ/analyzers/Histogram.scala b/src/main/scala/com/amazon/deequ/analyzers/Histogram.scala
index fbdb5b2b..742b2ba6 100644
--- a/src/main/scala/com/amazon/deequ/analyzers/Histogram.scala
+++ b/src/main/scala/com/amazon/deequ/analyzers/Histogram.scala
@@ -84,26 +84,11 @@ case class Histogram(
       case Some(theState) =>
         val value: Try[Distribution] = Try {
 
-          val countColumnName = theState.frequencies.schema.fields
-            .find(field => field.dataType == LongType && field.name != column)
-            .map(_.name)
-            .getOrElse(throw new IllegalStateException(s"Count column not found in the frequencies DataFrame"))
-
-          val topNRowsDF = theState.frequencies
-            .orderBy(col(countColumnName).desc)
-            .limit(maxDetailBins)
-            .collect()
-
+          val topNRows = theState.frequencies.rdd.top(maxDetailBins)(OrderByAbsoluteCount)
           val binCount = theState.frequencies.count()
 
-          val columnName = theState.frequencies.columns
-            .find(_ == column)
-            .getOrElse(throw new IllegalStateException(s"Column $column not found"))
-
-          val histogramDetails = topNRowsDF
-            .map { row =>
-              val discreteValue = row.getAs[String](columnName)
-              val absolute = row.getAs[Long](countColumnName)
+          val histogramDetails = topNRows
+            .map { case Row(discreteValue: String, absolute: Long) =>
               val ratio = absolute.toDouble / theState.numRows
               discreteValue -> DistributionValue(absolute, ratio)
             }