diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedDeltaBinaryPackedReader.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedDeltaBinaryPackedReader.java
index 62fb5f8c96bbf..7b2aac3118e5f 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedDeltaBinaryPackedReader.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedDeltaBinaryPackedReader.java
@@ -73,10 +73,10 @@ public class VectorizedDeltaBinaryPackedReader extends VectorizedReaderBase {
   private ByteBufferInputStream in;
 
   // temporary buffers used by readByte, readShort, readInteger, and readLong
-  byte byteVal;
-  short shortVal;
-  int intVal;
-  long longVal;
+  private byte byteVal;
+  private short shortVal;
+  private int intVal;
+  private long longVal;
 
   @Override
   public void initFromPage(int valueCount, ByteBufferInputStream in) throws IOException {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRebaseDatetimeSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRebaseDatetimeSuite.scala
index 49251af54193f..dbf7f54f6ff90 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRebaseDatetimeSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRebaseDatetimeSuite.scala
@@ -143,12 +143,12 @@ abstract class ParquetRebaseDatetimeSuite
           val df = Seq.tabulate(N)(rowFunc).toDF("dict", "plain")
             .select($"dict".cast(catalystType), $"plain".cast(catalystType))
           withSQLConf(SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> tsOutputType) {
-          checkDefaultLegacyRead(oldPath)
+            checkDefaultLegacyRead(oldPath)
             withSQLConf(inWriteConf -> CORRECTED.toString) {
-            df.write.mode("overwrite").parquet(path3_x)
+              df.write.mode("overwrite").parquet(path3_x)
             }
             withSQLConf(inWriteConf -> LEGACY.toString) {
-            df.write.parquet(path3_x_rebase)
+              df.write.parquet(path3_x_rebase)
             }
           }
           // For Parquet files written by Spark 3.0, we know the writer info and don't need the
@@ -243,40 +243,41 @@ abstract class ParquetRebaseDatetimeSuite
             SQLConf.PARQUET_INT96_REBASE_MODE_IN_READ.key
           )
         ).foreach { case (outType, tsStr, nonRebased, inWriteConf, inReadConf) =>
-        // Ignore the default JVM time zone and use the session time zone instead of it in rebasing.
-        DateTimeTestUtils.withDefaultTimeZone(DateTimeTestUtils.JST) {
-          withSQLConf(SQLConf.SESSION_LOCAL_TIMEZONE.key -> DateTimeTestUtils.LA.getId) {
-          withClue(s"output type $outType") {
-            withSQLConf(SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> outType) {
-              withTempPath { dir =>
-                val path = dir.getAbsolutePath
-                withSQLConf(inWriteConf -> LEGACY.toString) {
-                  Seq.tabulate(N)(_ => tsStr).toDF("tsS")
-                    .select($"tsS".cast("timestamp").as("ts"))
-                    .repartition(1)
-                    .write
-                    .option("parquet.enable.dictionary", dictionaryEncoding)
-                    .parquet(path)
-                }
+          // Ignore the default JVM time zone and use the session time zone instead of
+          // it in rebasing.
+          DateTimeTestUtils.withDefaultTimeZone(DateTimeTestUtils.JST) {
+            withSQLConf(SQLConf.SESSION_LOCAL_TIMEZONE.key -> DateTimeTestUtils.LA.getId) {
+              withClue(s"output type $outType") {
+                withSQLConf(SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> outType) {
+                  withTempPath { dir =>
+                    val path = dir.getAbsolutePath
+                    withSQLConf(inWriteConf -> LEGACY.toString) {
+                      Seq.tabulate(N)(_ => tsStr).toDF("tsS")
+                        .select($"tsS".cast("timestamp").as("ts"))
+                        .repartition(1)
+                        .write
+                        .option("parquet.enable.dictionary", dictionaryEncoding)
+                        .parquet(path)
+                    }
 
-                withAllParquetReaders {
-                    // The file metadata indicates if it needs rebase or not, so we can always get
-                    // the correct result regardless of the "rebase mode" config.
-                  runInMode(inReadConf, Seq(LEGACY, CORRECTED, EXCEPTION)) { options =>
-                    checkAnswer(
-                        spark.read.options(options).parquet(path).select($"ts".cast("string")),
-                        Seq.tabulate(N)(_ => Row(tsStr)))
-                  }
+                    withAllParquetReaders {
+                      // The file metadata indicates if it needs rebase or not, so we can always get
+                      // the correct result regardless of the "rebase mode" config.
+                      runInMode(inReadConf, Seq(LEGACY, CORRECTED, EXCEPTION)) { options =>
+                        checkAnswer(
+                          spark.read.options(options).parquet(path).select($"ts".cast("string")),
+                          Seq.tabulate(N)(_ => Row(tsStr)))
+                      }
 
-                  // Force to not rebase to prove the written datetime values are rebased
-                  // and we will get wrong result if we don't rebase while reading.
-                  withSQLConf("spark.test.forceNoRebase" -> "true") {
-                    checkAnswer(
-                        spark.read.parquet(path).select($"ts".cast("string")),
-                        Seq.tabulate(N)(_ => Row(nonRebased)))
+                      // Force to not rebase to prove the written datetime values are rebased
+                      // and we will get wrong result if we don't rebase while reading.
+                      withSQLConf("spark.test.forceNoRebase" -> "true") {
+                        checkAnswer(
+                          spark.read.parquet(path).select($"ts".cast("string")),
+                          Seq.tabulate(N)(_ => Row(nonRebased)))
+                      }
                     }
                   }
-                  }
                 }
               }
             }