diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala
index fad2ccff6021b..6d2ea464ec7bb 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala
@@ -20,6 +20,7 @@ package org.apache.spark.sql
 import java.math.MathContext
 import java.sql.{Date, Timestamp}
 import java.time.{Duration, Instant, LocalDate, LocalDateTime, Period, ZoneId}
+import java.time.temporal.ChronoUnit
 
 import scala.collection.mutable
 import scala.util.{Random, Try}
@@ -272,17 +273,8 @@ object RandomDataGenerator {
         val ns = rand.nextLong()
         new CalendarInterval(months, days, ns)
       })
-      case DayTimeIntervalType => Some(() => {
-        val maxSeconds = Duration.ofDays(106751991).getSeconds
-        val seconds = rand.nextLong() % maxSeconds
-        val nanoAdjustment = rand.nextLong() % 999999000
-        Duration.ofSeconds(seconds, nanoAdjustment)
-      })
-      case YearMonthIntervalType => Some(() => {
-        val years = rand.nextInt() % 178956970
-        val months = rand.nextInt() % 12
-        Period.of(years, months, 0)
-      })
+      case DayTimeIntervalType => Some(() => Duration.of(rand.nextLong(), ChronoUnit.MICROS))
+      case YearMonthIntervalType => Some(() => Period.ofMonths(rand.nextInt()).normalized())
       case DecimalType.Fixed(precision, scale) => Some(
         () => BigDecimal.apply(
           rand.nextLong() % math.pow(10, precision).toLong,
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGeneratorSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGeneratorSuite.scala
index cb335e5f435a3..69dca2cb7384b 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGeneratorSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGeneratorSuite.scala
@@ -143,4 +143,18 @@ class RandomDataGeneratorSuite extends SparkFunSuite with SQLHelper {
     assert(!Arrays.equals(array1, arrayExpected))
     assert(Arrays.equals(array2, arrayExpected))
   }
+
+  test("SPARK-35116: The generated data fits the precision of DayTimeIntervalType in spark") {
+    Seq(DayTimeIntervalType, YearMonthIntervalType).foreach { dt =>
+      for (seed <- 1 to 1000) {
+        val generator = RandomDataGenerator.forType(dt, false, new Random(seed)).get
+        val toCatalyst = CatalystTypeConverters.createToCatalystConverter(dt)
+        val toScala = CatalystTypeConverters.createToScalaConverter(dt)
+        val data = generator.apply()
+        val catalyst = toCatalyst(data)
+        val convertedBack = toScala(catalyst)
+        assert(data == convertedBack)
+      }
+    }
+  }
 }