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 1a1d73f6607f2..78e560746c851 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
@@ -160,37 +160,6 @@ class ParquetFileFormat
     val datetimeRebaseModeInRead = parquetOptions.datetimeRebaseModeInRead
     val int96RebaseModeInRead = parquetOptions.int96RebaseModeInRead
 
-    hadoopConf.set(ParquetInputFormat.READ_SUPPORT_CLASS, readSupportClass)
-    hadoopConf.set(
-      ParquetReadSupport.SPARK_ROW_REQUESTED_SCHEMA,
-      rowWithSchema)
-    hadoopConf.set(
-      ParquetWriteSupport.SPARK_ROW_SCHEMA,
-      rowWithSchema)
-    hadoopConf.set(
-      SQLConf.SESSION_LOCAL_TIMEZONE.key,
-      localTimezone)
-    hadoopConf.setBoolean(
-      SQLConf.NESTED_SCHEMA_PRUNING_ENABLED.key,
-      nestedSchemaPruningEnabled)
-    hadoopConf.setBoolean(
-      SQLConf.CASE_SENSITIVE.key,
-      sparkSession.sessionState.conf.caseSensitiveAnalysis)
-
-    // Sets flags for `ParquetToSparkSchemaConverter`
-    hadoopConf.setBoolean(
-      SQLConf.PARQUET_BINARY_AS_STRING.key,
-      isParquetBinaryAsString)
-    hadoopConf.setBoolean(
-      SQLConf.PARQUET_INT96_AS_TIMESTAMP.key,
-      isParquetINT96AsTimestamp)
-    hadoopConf.setBoolean(
-      SQLConf.PARQUET_INFER_TIMESTAMP_NTZ_ENABLED.key,
-      parquetInferTimestampNTZEnabled)
-    hadoopConf.setBoolean(
-      SQLConf.LEGACY_PARQUET_NANOS_AS_LONG.key,
-      legacyParquetNanosAsLong)
-
     val broadcastedHadoopConf = options.map(_ =>
       sparkSession.sparkContext.broadcast(new SerializableConfiguration(hadoopConf)))
 
@@ -215,50 +184,49 @@ class ParquetFileFormat
       val filePath = file.toPath
       val split = new FileSplit(filePath, file.start, file.length, Array.empty[String])
 
-      val sharedConf = if (!broadcastedHadoopConf.isEmpty) {
+      val conf = if (!broadcastedHadoopConf.isEmpty) {
         broadcastedHadoopConf.head.value.value
       } else {
-        val conf = SparkHadoopUtil.get.newConfiguration(sparkConf)
-        conf.set(ParquetInputFormat.READ_SUPPORT_CLASS, readSupportClass)
-        conf.set(
-          ParquetReadSupport.SPARK_ROW_REQUESTED_SCHEMA,
-          rowWithSchema)
-        conf.set(
-          ParquetWriteSupport.SPARK_ROW_SCHEMA,
-          rowWithSchema)
-        conf.set(
-          SQLConf.SESSION_LOCAL_TIMEZONE.key,
-          localTimezone)
-        conf.setBoolean(
-          SQLConf.NESTED_SCHEMA_PRUNING_ENABLED.key,
-          nestedSchemaPruningEnabled)
-        conf.setBoolean(
-          SQLConf.CASE_SENSITIVE.key,
-          isCaseSensitive)
-
-        // Sets flags for `ParquetToSparkSchemaConverter`
-        conf.setBoolean(
-          SQLConf.PARQUET_BINARY_AS_STRING.key,
-          isParquetBinaryAsString)
-        conf.setBoolean(
-          SQLConf.PARQUET_INT96_AS_TIMESTAMP.key,
-          isParquetINT96AsTimestamp)
-        conf.setBoolean(
-          SQLConf.PARQUET_INFER_TIMESTAMP_NTZ_ENABLED.key,
-          parquetInferTimestampNTZEnabled)
-        conf.setBoolean(
-          SQLConf.LEGACY_PARQUET_NANOS_AS_LONG.key,
-          legacyParquetNanosAsLong)
-        conf
+        SparkHadoopUtil.get.newConfiguration(sparkConf)
       }
+      conf.set(ParquetInputFormat.READ_SUPPORT_CLASS, readSupportClass)
+      conf.set(
+        ParquetReadSupport.SPARK_ROW_REQUESTED_SCHEMA,
+        rowWithSchema)
+      conf.set(
+        ParquetWriteSupport.SPARK_ROW_SCHEMA,
+        rowWithSchema)
+      conf.set(
+        SQLConf.SESSION_LOCAL_TIMEZONE.key,
+        localTimezone)
+      conf.setBoolean(
+        SQLConf.NESTED_SCHEMA_PRUNING_ENABLED.key,
+        nestedSchemaPruningEnabled)
+      conf.setBoolean(
+        SQLConf.CASE_SENSITIVE.key,
+        isCaseSensitive)
+
+      // Sets flags for `ParquetToSparkSchemaConverter`
+      conf.setBoolean(
+        SQLConf.PARQUET_BINARY_AS_STRING.key,
+        isParquetBinaryAsString)
+      conf.setBoolean(
+        SQLConf.PARQUET_INT96_AS_TIMESTAMP.key,
+        isParquetINT96AsTimestamp)
+      conf.setBoolean(
+        SQLConf.PARQUET_INFER_TIMESTAMP_NTZ_ENABLED.key,
+        parquetInferTimestampNTZEnabled)
+      conf.setBoolean(
+        SQLConf.LEGACY_PARQUET_NANOS_AS_LONG.key,
+        legacyParquetNanosAsLong)
 
       val fileFooter = if (enableVectorizedReader) {
         // When there are vectorized reads, we can avoid reading the footer twice by reading
         // all row groups in advance and filter row groups according to filters that require
         // push down (no need to read the footer metadata again).
-        ParquetFooterReader.readFooter(sharedConf, file, ParquetFooterReader.WITH_ROW_GROUPS)
+        ParquetFooterReader.readFooter(conf, file, ParquetFooterReader.WITH_ROW_GROUPS)
       } else {
-        ParquetFooterReader.readFooter(sharedConf, file, ParquetFooterReader.SKIP_ROW_GROUPS)
+        ParquetFooterReader.readFooter(conf, file, ParquetFooterReader.SKIP_ROW_GROUPS)
       }
 
       val footerFileMetaData = fileFooter.getFileMetaData
@@ -300,7 +268,7 @@ class ParquetFileFormat
 
       val convertTz =
         if (timestampConversion && !isCreatedByParquetMr) {
-          Some(DateTimeUtils.getZoneId(sharedConf.get(SQLConf.SESSION_LOCAL_TIMEZONE.key)))
+          Some(DateTimeUtils.getZoneId(conf.get(SQLConf.SESSION_LOCAL_TIMEZONE.key)))
         } else {
           None
         }
@@ -308,7 +276,7 @@ class ParquetFileFormat
 
       val attemptId = new TaskAttemptID(new TaskID(new JobID(), TaskType.MAP, 0), 0)
       val hadoopAttemptContext =
-        new TaskAttemptContextImpl(sharedConf, attemptId)
+        new TaskAttemptContextImpl(conf, attemptId)
 
       // Try to push down filters when filter push-down is enabled.
       // Notice: This push-down is RowGroups level, not individual records.