[MINOR] Fix typos

hudi-client/hudi-client-common/src/main/java/org/apache/hudi/index/bloom/HoodieBaseBloomIndexCheckFunction.java

@@ -49,8 +49,8 @@ public HoodieBaseBloomIndexCheckFunction(HoodieTable hoodieTable, HoodieWriteCon
   }
 
   @Override
-  public Iterator<List<KeyLookupResult>> apply(Iterator<Pair<String, HoodieKey>> fileParitionRecordKeyTripletItr) {
-    return new LazyKeyCheckIterator(fileParitionRecordKeyTripletItr);
+  public Iterator<List<KeyLookupResult>> apply(Iterator<Pair<String, HoodieKey>> filePartitionRecordKeyTripletItr) {
+    return new LazyKeyCheckIterator(filePartitionRecordKeyTripletItr);
   }
 
   class LazyKeyCheckIterator extends LazyIterableIterator<Pair<String, HoodieKey>, List<KeyLookupResult>> {

hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkValidatorUtils.java

@@ -138,7 +138,7 @@ public static Dataset<Row> readRecordsForBaseFiles(SQLContext sqlContext, List<S
   }
 
   /**
-   * Get reads from paritions modified including any inflight commits.
+   * Get reads from partitions modified including any inflight commits.
    * Note that this only works for COW tables
    */
   public static Dataset<Row> getRecordsFromPendingCommits(SQLContext sqlContext, 

hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/index/bloom/HoodieBloomIndexCheckFunction.java

@@ -53,8 +53,8 @@ public HoodieBloomIndexCheckFunction(HoodieTable hoodieTable, HoodieWriteConfig
 
   @Override
   public Iterator<List<KeyLookupResult>> call(Integer partition,
-      Iterator<Tuple2<String, HoodieKey>> fileParitionRecordKeyTripletItr) {
-    return new LazyKeyCheckIterator(fileParitionRecordKeyTripletItr);
+      Iterator<Tuple2<String, HoodieKey>> filePartitionRecordKeyTripletItr) {
+    return new LazyKeyCheckIterator(filePartitionRecordKeyTripletItr);
   }
 
   class LazyKeyCheckIterator extends LazyIterableIterator<Tuple2<String, HoodieKey>, List<KeyLookupResult>> {

hudi-spark-datasource/hudi-spark/src/main/scala/org/apache/spark/sql/catalyst/catalog/HoodieCatalogTable.scala

@@ -98,7 +98,7 @@ class HoodieCatalogTable(val spark: SparkSession, val table: CatalogTable) exten
   lazy val tableTypeName: String = tableType.name()
 
   /**
-   * Recored Field List(Primary Key List)
+   * Record Field List(Primary Key List)
    */
   lazy val primaryKeys: Array[String] = tableConfig.getRecordKeyFields.orElse(Array.empty)
 
@@ -108,7 +108,7 @@ class HoodieCatalogTable(val spark: SparkSession, val table: CatalogTable) exten
   lazy val preCombineKey: Option[String] = Option(tableConfig.getPreCombineField)
 
   /**
-   * Paritition Fields
+   * Partition Fields
    */
   lazy val partitionFields: Array[String] = tableConfig.getPartitionFields.orElse(Array.empty)
 

hudi-spark-datasource/hudi-spark/src/test/java/org/apache/hudi/functional/TestHoodieDatasetBulkInsertHelper.java

@@ -186,14 +186,14 @@ public void testBulkInsertPreCombine(boolean enablePreCombine) {
     }
 
     int metadataRecordKeyIndex = resultSchema.fieldIndex(HoodieRecord.RECORD_KEY_METADATA_FIELD);
-    int metadataParitionPathIndex = resultSchema.fieldIndex(HoodieRecord.PARTITION_PATH_METADATA_FIELD);
+    int metadataPartitionPathIndex = resultSchema.fieldIndex(HoodieRecord.PARTITION_PATH_METADATA_FIELD);
     int metadataCommitTimeIndex = resultSchema.fieldIndex(HoodieRecord.COMMIT_TIME_METADATA_FIELD);
     int metadataCommitSeqNoIndex = resultSchema.fieldIndex(HoodieRecord.COMMIT_SEQNO_METADATA_FIELD);
     int metadataFilenameIndex = resultSchema.fieldIndex(HoodieRecord.FILENAME_METADATA_FIELD);
 
     result.toJavaRDD().foreach(entry -> {
       assertTrue(entry.get(metadataRecordKeyIndex).equals(entry.getAs("_row_key")));
-      assertTrue(entry.get(metadataParitionPathIndex).equals(entry.getAs("partition")));
+      assertTrue(entry.get(metadataPartitionPathIndex).equals(entry.getAs("partition")));
       assertTrue(entry.get(metadataCommitSeqNoIndex).equals(""));
       assertTrue(entry.get(metadataCommitTimeIndex).equals(""));
       assertTrue(entry.get(metadataFilenameIndex).equals(""));

hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestCOWDataSource.scala

@@ -245,12 +245,12 @@ class TestCOWDataSource extends HoodieClientTestBase {
     spark.sql(String.format("select count(*) from tmpTable")).show()
 
     // step4: Query the rows count from hoodie table for partition1 DEFAULT_FIRST_PARTITION_PATH
-    val recordCountForParititon1 = spark.sql(String.format("select count(*) from tmpTable where partition = '%s'", HoodieTestDataGenerator.DEFAULT_FIRST_PARTITION_PATH)).collect()
-    assertEquals("6", recordCountForParititon1(0).get(0).toString)
+    val recordCountForPartition1 = spark.sql(String.format("select count(*) from tmpTable where partition = '%s'", HoodieTestDataGenerator.DEFAULT_FIRST_PARTITION_PATH)).collect()
+    assertEquals("6", recordCountForPartition1(0).get(0).toString)
 
     // step5: Query the rows count from hoodie table for partition2 DEFAULT_SECOND_PARTITION_PATH
-    val recordCountForParititon2 = spark.sql(String.format("select count(*) from tmpTable where partition = '%s'", HoodieTestDataGenerator.DEFAULT_SECOND_PARTITION_PATH)).collect()
-    assertEquals("7", recordCountForParititon2(0).get(0).toString)
+    val recordCountForPartition2 = spark.sql(String.format("select count(*) from tmpTable where partition = '%s'", HoodieTestDataGenerator.DEFAULT_SECOND_PARTITION_PATH)).collect()
+    assertEquals("7", recordCountForPartition2(0).get(0).toString)
 
     // step6: Query the rows count from hoodie table for partition2 DEFAULT_SECOND_PARTITION_PATH using spark.collect and then filter mode
     val recordsForPartitionColumn = spark.sql(String.format("select partition from tmpTable")).collect()
@@ -292,12 +292,12 @@ class TestCOWDataSource extends HoodieClientTestBase {
     spark.sql(String.format("select count(*) from tmpTable")).show()
 
     // step3: Query the rows count from hoodie table for partition1 DEFAULT_FIRST_PARTITION_PATH
-    val recordCountForParititon1 = spark.sql(String.format("select count(*) from tmpTable where partition = '%s'", HoodieTestDataGenerator.DEFAULT_FIRST_PARTITION_PATH)).collect()
-    assertEquals("0", recordCountForParititon1(0).get(0).toString)
+    val recordCountForPartition1 = spark.sql(String.format("select count(*) from tmpTable where partition = '%s'", HoodieTestDataGenerator.DEFAULT_FIRST_PARTITION_PATH)).collect()
+    assertEquals("0", recordCountForPartition1(0).get(0).toString)
 
     // step4: Query the rows count from hoodie table for partition2 DEFAULT_SECOND_PARTITION_PATH
-    val recordCountForParititon2 = spark.sql(String.format("select count(*) from tmpTable where partition = '%s'", HoodieTestDataGenerator.DEFAULT_SECOND_PARTITION_PATH)).collect()
-    assertEquals("7", recordCountForParititon2(0).get(0).toString)
+    val recordCountForPartition2 = spark.sql(String.format("select count(*) from tmpTable where partition = '%s'", HoodieTestDataGenerator.DEFAULT_SECOND_PARTITION_PATH)).collect()
+    assertEquals("7", recordCountForPartition2(0).get(0).toString)
 
     // step5: Query the rows count from hoodie table
     val recordCount = spark.sql(String.format("select count(*) from tmpTable")).collect()
@@ -417,7 +417,7 @@ class TestCOWDataSource extends HoodieClientTestBase {
       .mode(SaveMode.Overwrite)
   }
 
-  @Test def testSparkPartitonByWithCustomKeyGenerator(): Unit = {
+  @Test def testSparkPartitionByWithCustomKeyGenerator(): Unit = {
     // Without fieldType, the default is SIMPLE
     var writer = getDataFrameWriter(classOf[CustomKeyGenerator].getName)
     writer.partitionBy("current_ts")
@@ -465,7 +465,7 @@ class TestCOWDataSource extends HoodieClientTestBase {
     }
   }
 
-  @Test def testSparkPartitonByWithSimpleKeyGenerator() {
+  @Test def testSparkPartitionByWithSimpleKeyGenerator() {
     // Use the `driver` field as the partition key
     var writer = getDataFrameWriter(classOf[SimpleKeyGenerator].getName)
     writer.partitionBy("driver")
@@ -484,7 +484,7 @@ class TestCOWDataSource extends HoodieClientTestBase {
     assertTrue(recordsReadDF.filter(col("_hoodie_partition_path") =!= lit("default")).count() == 0)
   }
 
-  @Test def testSparkPartitonByWithComplexKeyGenerator() {
+  @Test def testSparkPartitionByWithComplexKeyGenerator() {
     // Use the `driver` field as the partition key
     var writer = getDataFrameWriter(classOf[ComplexKeyGenerator].getName)
     writer.partitionBy("driver")
@@ -503,7 +503,7 @@ class TestCOWDataSource extends HoodieClientTestBase {
     assertTrue(recordsReadDF.filter(col("_hoodie_partition_path") =!= concat(col("driver"), lit("/"), col("rider"))).count() == 0)
   }
 
-  @Test def testSparkPartitonByWithTimestampBasedKeyGenerator() {
+  @Test def testSparkPartitionByWithTimestampBasedKeyGenerator() {
     val writer = getDataFrameWriter(classOf[TimestampBasedKeyGenerator].getName)
     writer.partitionBy("current_ts")
       .option(Config.TIMESTAMP_TYPE_FIELD_PROP, "EPOCHMILLISECONDS")
@@ -517,7 +517,7 @@ class TestCOWDataSource extends HoodieClientTestBase {
     assertTrue(recordsReadDF.filter(col("_hoodie_partition_path") =!= udf_date_format(col("current_ts"))).count() == 0)
   }
 
-  @Test def testSparkPartitonByWithGlobalDeleteKeyGenerator() {
+  @Test def testSparkPartitionByWithGlobalDeleteKeyGenerator() {
     val writer = getDataFrameWriter(classOf[GlobalDeleteKeyGenerator].getName)
     writer.partitionBy("driver")
       .mode(SaveMode.Overwrite)
@@ -528,7 +528,7 @@ class TestCOWDataSource extends HoodieClientTestBase {
     assertTrue(recordsReadDF.filter(col("_hoodie_partition_path") =!= lit("")).count() == 0)
   }
 
-  @Test def testSparkPartitonByWithNonpartitionedKeyGenerator() {
+  @Test def testSparkPartitionByWithNonpartitionedKeyGenerator() {
     // Empty string column
     var writer = getDataFrameWriter(classOf[NonpartitionedKeyGenerator].getName)
     writer.partitionBy("")

hudi-sync/hudi-hive-sync/src/main/java/org/apache/hudi/hive/HiveStylePartitionValueExtractor.java

@@ -22,7 +22,7 @@
 import java.util.List;
 
 /**
- * Extractor for Hive Style Partitioned tables, when the parition folders are key value pairs.
+ * Extractor for Hive Style Partitioned tables, when the partition folders are key value pairs.
  *
  * <p>This implementation extracts the partition value of yyyy-mm-dd from the path of type datestr=yyyy-mm-dd.
  */

hudi-utilities/src/main/java/org/apache/hudi/utilities/sources/helpers/DatePartitionPathSelector.java

@@ -131,9 +131,9 @@ public Pair<Option<String>, String> getNextFilePathsAndMaxModificationTime(JavaS
     long lastCheckpointTime = lastCheckpointStr.map(Long::parseLong).orElse(Long.MIN_VALUE);
     HoodieSparkEngineContext context = new HoodieSparkEngineContext(sparkContext);
     SerializableConfiguration serializedConf = new SerializableConfiguration(fs.getConf());
-    List<String> prunedParitionPaths = pruneDatePartitionPaths(context, fs, props.getString(ROOT_INPUT_PATH_PROP), currentDate);
+    List<String> prunedPartitionPaths = pruneDatePartitionPaths(context, fs, props.getString(ROOT_INPUT_PATH_PROP), currentDate);
 
-    List<FileStatus> eligibleFiles = context.flatMap(prunedParitionPaths,
+    List<FileStatus> eligibleFiles = context.flatMap(prunedPartitionPaths,
         path -> {
           FileSystem fs = new Path(path).getFileSystem(serializedConf.get());
           return listEligibleFiles(fs, new Path(path), lastCheckpointTime).stream();