[NIT] Fix some typos

spark-extension/src/main/java/org/apache/spark/sql/blaze/BlazeConf.java

@@ -60,7 +60,7 @@ public enum BlazeConf {
     /// partial aggregate skipping ratio
     PARTIAL_AGG_SKIPPING_RATIO("spark.blaze.partialAggSkipping.ratio", 0.9),
 
-    /// mininum number of rows to trigger partial aggregate skipping
+    /// minimum number of rows to trigger partial aggregate skipping
     PARTIAL_AGG_SKIPPING_MIN_ROWS("spark.blaze.partialAggSkipping.minRows", BATCH_SIZE.intConf() * 5),
 
     /// always skip partial aggregate when triggered spilling
@@ -69,7 +69,7 @@ public enum BlazeConf {
     // parquet enable page filtering
     PARQUET_ENABLE_PAGE_FILTERING("spark.blaze.parquet.enable.pageFiltering", false),
 
-    // parqeut enable bloom filter
+    // parquet enable bloom filter
     PARQUET_ENABLE_BLOOM_FILTER("spark.blaze.parquet.enable.bloomFilter", false),
 
     // spark io compression codec

spark-extension/src/main/scala/org/apache/spark/sql/blaze/BlazeConverters.scala

@@ -605,7 +605,7 @@ object BlazeConverters extends Logging {
           assert(NativeHelper.isNative(left), "broadcast join build side is not native")
       }
 
-      // reuse NativeBroadcastJoin with empty equility keys
+      // reuse NativeBroadcastJoin with empty equality keys
       Shims.get.createNativeBroadcastJoinExec(
         addRenameColumnsExec(convertToNative(left)),
         addRenameColumnsExec(convertToNative(right)),
@@ -738,7 +738,7 @@ object BlazeConverters extends Logging {
       } catch {
         case e @ (_: NotImplementedError | _: AssertionError | _: Exception) =>
           logWarning(
-            s"Error projecting resultExpressions, failback to non-native projection: " +
+            s"Error projecting resultExpressions, fallback to non-native projection: " +
               s"${e.getMessage}")
           val proj = ProjectExec(exec.resultExpressions, nativeAggr)
           proj.setTagValue(convertToNonNativeTag, true)
@@ -795,7 +795,7 @@ object BlazeConverters extends Logging {
       } catch {
         case e @ (_: NotImplementedError | _: AssertionError | _: Exception) =>
           logWarning(
-            s"Error projecting resultExpressions, failback to non-native projection: " +
+            s"Error projecting resultExpressions, fallback to non-native projection: " +
               s"${e.getMessage}")
           val proj = ProjectExec(exec.resultExpressions, nativeAggr)
           proj.setTagValue(convertToNonNativeTag, true)

spark-extension/src/main/scala/org/apache/spark/sql/blaze/SparkUDAFWrapperContext.scala

@@ -128,7 +128,7 @@ case class SparkUDAFWrapperContext[B](serialized: ByteBuffer) extends Logging {
       ArrowArray.wrap(importBatchFFIArrayPtr)) { (inputRoot, inputArray) =>
       // import into params root
       Data.importIntoVectorSchemaRoot(ROOT_ALLOCATOR, inputArray, inputRoot, dictionaryProvider)
-      val inputRow = ColumnarHelper.rootRowReuseable(inputRoot)
+      val inputRow = ColumnarHelper.rootRowReusable(inputRoot)
 
       for (zippedIdx <- zippedIndices) {
         val rowIdx = ((zippedIdx >> 32) & 0xffffffff).toInt

spark-extension/src/main/scala/org/apache/spark/sql/blaze/SparkUDTFWrapperContext.scala

@@ -106,7 +106,7 @@ case class SparkUDTFWrapperContext(serialized: ByteBuffer) extends Logging {
         // evaluate expression and write to output root
         val reusedOutputRow = new GenericInternalRow(Array[Any](null, null))
         val outputWriter = ArrowWriter.create(outputRoot)
-        val paramsRow = ColumnarHelper.rootRowReuseable(currentParamsRoot)
+        val paramsRow = ColumnarHelper.rootRowReusable(currentParamsRoot)
 
         while (currentRowIdx < currentParamsRoot.getRowCount
           && allocator.getAllocatedMemory < maxBatchMemorySize

spark-extension/src/main/scala/org/apache/spark/sql/blaze/util/JsonFallbackWrapper.scala

@@ -40,7 +40,7 @@ case class JsonFallbackWrapper(jsonPath: String) extends Logging {
       ArrowArray.wrap(jsonsStrArrayPtr),
       ArrowArray.wrap(outputArrayPtr)) { case (inputRoot, outputRoot, inputArray, outputArray) =>
       Data.importIntoVectorSchemaRoot(ROOT_ALLOCATOR, inputArray, inputRoot, dictionaryProvider)
-      val inputRow = ColumnarHelper.rootRowReuseable(inputRoot)
+      val inputRow = ColumnarHelper.rootRowReusable(inputRoot)
       val nullOutputRow = new GenericInternalRow(1)
       val outputRow = new GenericInternalRow(1)
       val outputWriter = ArrowWriter.create(outputRoot)

spark-extension/src/main/scala/org/apache/spark/sql/execution/blaze/columnar/ColumnarHelper.scala

@@ -21,15 +21,15 @@ import org.apache.arrow.vector.VectorSchemaRoot
 
 object ColumnarHelper {
   def rootRowsIter(root: VectorSchemaRoot): Iterator[BlazeColumnarBatchRow] = {
-    val row = rootRowReuseable(root)
+    val row = rootRowReusable(root)
     val numRows = root.getRowCount
     Range(0, numRows).iterator.map { rowId =>
       row.rowId = rowId
       row
     }
   }
 
-  def rootRowReuseable(root: VectorSchemaRoot): BlazeColumnarBatchRow = {
+  def rootRowReusable(root: VectorSchemaRoot): BlazeColumnarBatchRow = {
     val vectors = root.getFieldVectors.asScala.toArray
     new BlazeColumnarBatchRow(
       vectors.map(new BlazeArrowColumnVector(_).asInstanceOf[BlazeColumnVector]))

spark-extension/src/main/scala/org/apache/spark/sql/execution/blaze/plan/NativeBroadcastExchangeBase.scala

@@ -121,7 +121,7 @@ abstract class NativeBroadcastExchangeBase(mode: BroadcastMode, override val chi
       .map(_.copy())
       .toArray
 
-    val broadcast = relationFuture.get // bloadcast must be resolved
+    val broadcast = relationFuture.get // broadcast must be resolved
     val v = mode.transform(dataRows)
     val dummyBroadcasted = new Broadcast[Any](-1) {
       override protected def getValue(): Any = v

spark-extension/src/main/scala/org/apache/spark/sql/execution/blaze/plan/NativeParquetInsertIntoHiveTableBase.scala

@@ -78,7 +78,7 @@ abstract class NativeParquetInsertIntoHiveTableBase(
     val encryptEnabled: Boolean = hadoopConf.getBoolean("parquet.encrypt.enable", false)
 
     assert(outputFormatClassName.endsWith("mapredparquetoutputformat"), "not parquet format")
-    assert(!encryptEnabled, "not supported writting encrypted table")
+    assert(!encryptEnabled, "not supported writing encrypted table")
   }
   check()
 

spark-extension/src/main/scala/org/apache/spark/sql/hive/execution/blaze/plan/NativePaimonTableScanExec.scala

@@ -162,11 +162,11 @@ case class NativePaimonTableScanExec(basedHiveScan: HiveTableScanExec)
         def toRow(
             values: Seq[String],
             partitionSchema: StructType,
-            defaultTimeZondId: String): InternalRow = {
+            defaultTimeZoneId: String): InternalRow = {
           val caseInsensitiveProperties = CaseInsensitiveMap(
             relation.tableMeta.storage.properties)
           val timeZoneId =
-            caseInsensitiveProperties.getOrElse(DateTimeUtils.TIMEZONE_OPTION, defaultTimeZondId)
+            caseInsensitiveProperties.getOrElse(DateTimeUtils.TIMEZONE_OPTION, defaultTimeZoneId)
           InternalRow.fromSeq(partitionSchema.zipWithIndex.map { case (field, index) =>
             val partValue = if (values(index) == ExternalCatalogUtils.DEFAULT_PARTITION_NAME) {
               null