diff --git a/datalake-spark3/src/main/scala/bio/ferlab/datalake/spark3/utils/DeltaUtils.scala b/datalake-spark3/src/main/scala/bio/ferlab/datalake/spark3/utils/DeltaUtils.scala
index 339c131b..96e6b500 100644
--- a/datalake-spark3/src/main/scala/bio/ferlab/datalake/spark3/utils/DeltaUtils.scala
+++ b/datalake-spark3/src/main/scala/bio/ferlab/datalake/spark3/utils/DeltaUtils.scala
@@ -171,10 +171,18 @@ object DeltaUtils {
    * +---------------+-----------------------------------+
    * }}}
    */
-  def getPartitionValues(path: String)(implicit spark: SparkSession): DataFrame = {
+  def getPartitionValues(path: String)(implicit spark: SparkSession): DataFrame =
+    getPartitionValues(getTableStats(path))
+
+  /**
+   * @see Overload of [[getPartitionValues]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getPartitionValues(statsDf: DataFrame)(implicit spark: SparkSession): DataFrame = {
     import spark.implicits._
 
-    getTableStats(path)
+    statsDf
       .select(explode($"partitionValues") as Seq("partitionColumn", "value"))
       .groupBy("partitionColumn")
       .agg(array_sort(collect_set("value")) as "values")
@@ -187,10 +195,18 @@ object DeltaUtils {
    * @param spark Spark session
    * @return The total number of records in the table.
    */
-  def getNumRecords(path: String)(implicit spark: SparkSession): Long = {
+  def getNumRecords(path: String)(implicit spark: SparkSession): Long =
+    getNumRecords(getTableStats(path))
+
+  /**
+   * @see Overload of [[getNumRecords]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getNumRecords(statsDf: DataFrame)(implicit spark: SparkSession): Long = {
     import spark.implicits._
 
-    getTableStats(path)
+    statsDf
       .select(sum("stats.numRecords"))
       .as[Long]
       .head()
@@ -219,9 +235,17 @@ object DeltaUtils {
    * +---------------+--------------+----------+
    * }}}
    */
-  def getNumRecordsPerPartition(path: String)(implicit spark: SparkSession): DataFrame = {
+  def getNumRecordsPerPartition(path: String)(implicit spark: SparkSession): DataFrame =
+    getNumRecordsPerPartition(getTableStats(path))
+
+  /**
+   * @see Overload of [[getNumRecordsPerPartition]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getNumRecordsPerPartition(statsDf: DataFrame)(implicit spark: SparkSession): DataFrame = {
     val numRecords = sum("stats.numRecords") as "numRecords"
-    getStatPerPartition(getTableStats(path), numRecords)
+    getStatPerPartition(statsDf, numRecords)
   }
 
   /**
@@ -240,12 +264,19 @@ object DeltaUtils {
    * )
    * }}}
    */
-  def getMinValues(path: String)(implicit spark: SparkSession): Map[String, Any] = {
-    val statsDf = getTableStats(path).select("stats.minValues.*")
-    val columnNames = statsDf.columns
-    val minValues = statsDf.columns.map(c => min(c) as c)
+  def getMinValues(path: String)(implicit spark: SparkSession): Map[String, Any] =
+    getMinValues(getTableStats(path))
+
+  /**
+   * @see Overload of [[getMinValues]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getMinValues(statsDf: DataFrame)(implicit spark: SparkSession): Map[String, Any] = {
+    val minValuesDf = statsDf.select("stats.minValues.*")
+    val minValues = minValuesDf.columns.map(c => min(c) as c)
 
-    getMap[String](statsDf, minValues)
+    getMap[String](minValuesDf, minValues)
   }
 
   /**
@@ -278,8 +309,15 @@ object DeltaUtils {
    * +---------------+--------------+------------+------------+------------+
    * }}}
    */
-  def getMinValuesPerPartition(path: String)(implicit spark: SparkSession): DataFrame = {
-    val statsDf = getTableStats(path)
+  def getMinValuesPerPartition(path: String)(implicit spark: SparkSession): DataFrame =
+    getMinValuesPerPartition(getTableStats(path))
+
+  /**
+   * @see Overload of [[getMinValuesPerPartition]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getMinValuesPerPartition(statsDf: DataFrame)(implicit spark: SparkSession): DataFrame = {
     val columnNames = statsDf.select("stats.minValues.*").columns
     val minValues = columnNames.map(c => min(s"stats.minValues.$c") as c)
 
@@ -302,12 +340,19 @@ object DeltaUtils {
    * )
    * }}}
    */
-  def getMaxValues(path: String)(implicit spark: SparkSession): Map[String, Any] = {
-    val statsDf = getTableStats(path).select("stats.maxValues.*")
-    val columnNames = statsDf.columns
-    val maxValues = columnNames.map(c => max(c) as c)
+  def getMaxValues(path: String)(implicit spark: SparkSession): Map[String, Any] =
+    getMaxValues(getTableStats(path))
+
+  /**
+   * @see Overload of [[getMaxValues]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getMaxValues(statsDf: DataFrame)(implicit spark: SparkSession): Map[String, Any] = {
+    val maxValuesDf = statsDf.select("stats.maxValues.*")
+    val maxValues = maxValuesDf.columns.map(c => max(c) as c)
 
-    getMap[Any](statsDf, maxValues)
+    getMap[Any](maxValuesDf, maxValues)
   }
 
   /**
@@ -340,9 +385,15 @@ object DeltaUtils {
    * +---------------+--------------+------------+------------+------------+
    * }}}
    */
-  def getMaxValuesPerPartition(path: String)(implicit spark: SparkSession): DataFrame = {
+  def getMaxValuesPerPartition(path: String)(implicit spark: SparkSession): DataFrame =
+    getMaxValuesPerPartition(getTableStats(path))
 
-    val statsDf = getTableStats(path)
+  /**
+   * @see Overload of [[getMaxValuesPerPartition]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getMaxValuesPerPartition(statsDf: DataFrame)(implicit spark: SparkSession): DataFrame = {
     val columnNames = statsDf.select("stats.maxValues.*").columns
     val maxValues = columnNames.map(c => max(s"stats.maxValues.$c") as c)
 
@@ -365,12 +416,19 @@ object DeltaUtils {
    * )
    * }}}
    */
-  def getNullCounts(path: String)(implicit spark: SparkSession): Map[String, Long] = {
-    val statsDf = getTableStats(path).select("stats.nullCount.*")
-    val columnNames = statsDf.columns
-    val nullCounts = columnNames.map(c => sum(c) as c)
+  def getNullCounts(path: String)(implicit spark: SparkSession): Map[String, Long] =
+    getNullCounts(getTableStats(path))
+
+  /**
+   * @see Overload of [[getNullCounts]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getNullCounts(statsDf: DataFrame)(implicit spark: SparkSession): Map[String, Long] = {
+    val nullCountsDf = statsDf.select("stats.nullCount.*")
+    val nullCounts = nullCountsDf.columns.map(c => sum(c) as c)
 
-    getMap[Long](statsDf, nullCounts)
+    getMap[Long](nullCountsDf, nullCounts)
   }
 
   /**
@@ -403,9 +461,15 @@ object DeltaUtils {
    * +---------------+--------------+-----+---+------------+
    * }}}
    */
-  def getNullCountsPerPartition(path: String)(implicit spark: SparkSession): DataFrame = {
+  def getNullCountsPerPartition(path: String)(implicit spark: SparkSession): DataFrame =
+    getNullCountsPerPartition(getTableStats(path))
 
-    val statsDf = getTableStats(path)
+  /**
+   * @see Overload of [[getNullCountsPerPartition]].
+   * @param statsDf Pre-computed stats DataFrame from [[getTableStats]]. Pass this to reuse
+   *                an already-loaded snapshot across multiple calls.
+   */
+  def getNullCountsPerPartition(statsDf: DataFrame)(implicit spark: SparkSession): DataFrame = {
     val columnNames = statsDf.select("stats.nullCount.*").columns
     val nullCounts = columnNames.map(c => sum(s"stats.nullCount.$c") as c)