diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
index f7aa6da0a5bdc..8a4fca750d7e4 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
@@ -147,6 +147,21 @@ class SimpleTestOptimizer extends Optimizer(
     new SimpleCatalystConf(caseSensitiveAnalysis = true)),
   new SimpleCatalystConf(caseSensitiveAnalysis = true))
 
+/**
+ * Pushes projects down beneath Sample to enable column pruning with sampling.
+ */
+object PushProjectThroughSample extends Rule[LogicalPlan] {
+  def apply(plan: LogicalPlan): LogicalPlan = plan transform {
+    // Push down projection into sample
+    case proj @ Project(projectList, Sample(lb, up, replace, seed, child)) =>
+      if (!replace || !projectList.exists(_.find(!_.deterministic).nonEmpty)) {
+        Sample(lb, up, replace, seed, Project(projectList, child))()
+      } else {
+        proj
+      }
+  }
+}
+
 /**
  * Removes the Project only conducting Alias of its child node.
  * It is created mainly for removing extra Project added in EliminateSerialization rule,
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 6da99ce0dd683..434d9496a1fbc 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
@@ -1534,15 +1534,15 @@ class Dataset[T] private[sql](
    * Returns a new Dataset by sampling a fraction of rows.
    *
    * @param withReplacement Sample with replacement or not.
-   * @param fraction Fraction of rows to generate.
+   * @param fraction Fraction of rows to generate and the range is 0.0 <= `fraction` <= 1.0.
    * @param seed Seed for sampling.
    *
    * @group typedrel
    * @since 1.6.0
    */
   def sample(withReplacement: Boolean, fraction: Double, seed: Long): Dataset[T] = {
-    require(fraction >= 0,
-      s"Fraction must be nonnegative, but got ${fraction}")
+    require(fraction >= 0 && fraction <= 1.0,
+      s"Fraction range must be 0.0 <= `fraction` <= 1.0, but got ${fraction}")
 
     withTypedPlan {
       Sample(0.0, fraction, withReplacement, seed, logicalPlan)()
@@ -1553,7 +1553,7 @@ class Dataset[T] private[sql](
    * Returns a new Dataset by sampling a fraction of rows, using a random seed.
    *
    * @param withReplacement Sample with replacement or not.
-   * @param fraction Fraction of rows to generate.
+   * @param fraction Fraction of rows to generate and the range is 0.0 <= `fraction` <= 1.0.
    *
    * @group typedrel
    * @since 1.6.0
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
index ad8a71689895b..17708a195f6c9 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
@@ -266,6 +266,7 @@ case class SampleExec(
     if (withReplacement) {
       val samplerClass = classOf[PoissonSampler[UnsafeRow]].getName
       val initSampler = ctx.freshName("initSampler")
+      ctx.copyResult = true
       ctx.addMutableState(s"$samplerClass<UnsafeRow>", sampler,
         s"$initSampler();")
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
index 499f3180379c2..983fbd68d6812 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
@@ -1578,4 +1578,26 @@ class DataFrameSuite extends QueryTest with SharedSQLContext {
     val df = spark.createDataFrame(rdd, StructType(schemas), false)
     assert(df.persist.take(1).apply(0).toSeq(100).asInstanceOf[Long] == 100)
   }
+
+  test("cannot push projects down beneath sample when amplifying data") {
+    val df = Seq((1, 0), (2, 0), (3, 0)).toDF("a", "b")
+    val amplifyDf = df.sample(true, 0.99)
+    def checkQuery(c: Column): Unit = {
+      val d = amplifyDf.withColumn("c", c).select($"c").collect
+      assert(d.size == d.distinct.size)
+    }
+    checkQuery(monotonically_increasing_id)
+    checkQuery(rand)
+  }
+
+  test("sampling fraction must be greate than 0.0 and less than 1.0") {
+    def checkException(v: Double): Unit = {
+      val e = intercept[AnalysisException] {
+        Seq((1, 0), (2, 0), (3, 0)).toDF("a", "b").sample(true, 2.0)
+      }
+      assert(e.getMessage.startsWith("A valid range is 0.0 < `fraction` <= 1.0"))
+    }
+    checkException(1.1)
+    checkException(-1.2)
+  }
 }