diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala
index d8f47eec952d..d1f9e11ed422 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala
@@ -342,6 +342,7 @@ class ParquetFileFormat
       sparkSession.sessionState.conf.parquetFilterPushDown
     // Whole stage codegen (PhysicalRDD) is able to deal with batches directly
     val returningBatch = supportBatch(sparkSession, resultSchema)
+    val pushDownDate = sqlConf.parquetFilterPushDownDate
 
     (file: PartitionedFile) => {
       assert(file.partitionValues.numFields == partitionSchema.size)
@@ -352,7 +353,7 @@ class ParquetFileFormat
           // Collects all converted Parquet filter predicates. Notice that not all predicates can be
           // converted (`ParquetFilters.createFilter` returns an `Option`). That's why a `flatMap`
           // is used here.
-          .flatMap(ParquetFilters.createFilter(requiredSchema, _))
+          .flatMap(new ParquetFilters(pushDownDate).createFilter(requiredSchema, _))
           .reduceOption(FilterApi.and)
       } else {
         None
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala
index ccc8306866d6..310626197a76 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilters.scala
@@ -25,14 +25,13 @@ import org.apache.parquet.io.api.Binary
 
 import org.apache.spark.sql.catalyst.util.DateTimeUtils
 import org.apache.spark.sql.catalyst.util.DateTimeUtils.SQLDate
-import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.sources
 import org.apache.spark.sql.types._
 
 /**
  * Some utility function to convert Spark data source filters to Parquet filters.
  */
-private[parquet] object ParquetFilters {
+private[parquet] class ParquetFilters(pushDownDate: Boolean) {
 
   private def dateToDays(date: Date): SQLDate = {
     DateTimeUtils.fromJavaDate(date)
@@ -59,7 +58,7 @@ private[parquet] object ParquetFilters {
       (n: String, v: Any) => FilterApi.eq(
         binaryColumn(n),
         Option(v).map(b => Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]])).orNull)
-    case DateType if SQLConf.get.parquetFilterPushDownDate =>
+    case DateType if pushDownDate =>
       (n: String, v: Any) => FilterApi.eq(
         intColumn(n),
         Option(v).map(date => dateToDays(date.asInstanceOf[Date]).asInstanceOf[Integer]).orNull)
@@ -85,7 +84,7 @@ private[parquet] object ParquetFilters {
       (n: String, v: Any) => FilterApi.notEq(
         binaryColumn(n),
         Option(v).map(b => Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]])).orNull)
-    case DateType if SQLConf.get.parquetFilterPushDownDate =>
+    case DateType if pushDownDate =>
       (n: String, v: Any) => FilterApi.notEq(
         intColumn(n),
         Option(v).map(date => dateToDays(date.asInstanceOf[Date]).asInstanceOf[Integer]).orNull)
@@ -108,7 +107,7 @@ private[parquet] object ParquetFilters {
     case BinaryType =>
       (n: String, v: Any) =>
         FilterApi.lt(binaryColumn(n), Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]]))
-    case DateType if SQLConf.get.parquetFilterPushDownDate =>
+    case DateType if pushDownDate =>
       (n: String, v: Any) => FilterApi.lt(
         intColumn(n),
         Option(v).map(date => dateToDays(date.asInstanceOf[Date]).asInstanceOf[Integer]).orNull)
@@ -131,7 +130,7 @@ private[parquet] object ParquetFilters {
     case BinaryType =>
       (n: String, v: Any) =>
         FilterApi.ltEq(binaryColumn(n), Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]]))
-    case DateType if SQLConf.get.parquetFilterPushDownDate =>
+    case DateType if pushDownDate =>
       (n: String, v: Any) => FilterApi.ltEq(
         intColumn(n),
         Option(v).map(date => dateToDays(date.asInstanceOf[Date]).asInstanceOf[Integer]).orNull)
@@ -154,7 +153,7 @@ private[parquet] object ParquetFilters {
     case BinaryType =>
       (n: String, v: Any) =>
         FilterApi.gt(binaryColumn(n), Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]]))
-    case DateType if SQLConf.get.parquetFilterPushDownDate =>
+    case DateType if pushDownDate =>
       (n: String, v: Any) => FilterApi.gt(
         intColumn(n),
         Option(v).map(date => dateToDays(date.asInstanceOf[Date]).asInstanceOf[Integer]).orNull)
@@ -177,7 +176,7 @@ private[parquet] object ParquetFilters {
     case BinaryType =>
       (n: String, v: Any) =>
         FilterApi.gtEq(binaryColumn(n), Binary.fromReusedByteArray(v.asInstanceOf[Array[Byte]]))
-    case DateType if SQLConf.get.parquetFilterPushDownDate =>
+    case DateType if pushDownDate =>
       (n: String, v: Any) => FilterApi.gtEq(
         intColumn(n),
         Option(v).map(date => dateToDays(date.asInstanceOf[Date]).asInstanceOf[Integer]).orNull)
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
index 1d3476e74704..667e0b1760e3 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
@@ -55,6 +55,8 @@ import org.apache.spark.util.{AccumulatorContext, AccumulatorV2}
  */
 class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContext {
 
+  private lazy val parquetFilters = new ParquetFilters(conf.parquetFilterPushDownDate)
+
   override def beforeEach(): Unit = {
     super.beforeEach()
     // Note that there are many tests here that require record-level filtering set to be true.
@@ -99,7 +101,7 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
         assert(selectedFilters.nonEmpty, "No filter is pushed down")
 
         selectedFilters.foreach { pred =>
-          val maybeFilter = ParquetFilters.createFilter(df.schema, pred)
+          val maybeFilter = parquetFilters.createFilter(df.schema, pred)
           assert(maybeFilter.isDefined, s"Couldn't generate filter predicate for $pred")
           // Doesn't bother checking type parameters here (e.g. `Eq[Integer]`)
           maybeFilter.exists(_.getClass === filterClass)
@@ -517,7 +519,7 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
       lt(intColumn("a"), 10: Integer),
       gt(doubleColumn("c"), 1.5: java.lang.Double)))
     ) {
-      ParquetFilters.createFilter(
+      parquetFilters.createFilter(
         schema,
         sources.And(
           sources.LessThan("a", 10),
@@ -525,7 +527,7 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
     }
 
     assertResult(None) {
-      ParquetFilters.createFilter(
+      parquetFilters.createFilter(
         schema,
         sources.And(
           sources.LessThan("a", 10),
@@ -533,7 +535,7 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
     }
 
     assertResult(None) {
-      ParquetFilters.createFilter(
+      parquetFilters.createFilter(
         schema,
         sources.Not(
           sources.And(