[docs] Fix typo and add unsupported example for unsupported config

docs/docs/cdc-ingestion/kafka-cdc.mdx

@@ -233,7 +233,7 @@ To use this feature through `flink run`, run the following shell command.
 This action will build a single combined sink for all tables. For each Kafka topic's table to be synchronized, if the
 corresponding Paimon table does not exist, this action will automatically create the table, and its schema will be derived
 from all specified Kafka topic's tables. If the Paimon table already exists and its schema is different from that parsed
-from Kafka record, this action will try to preform schema evolution.
+from Kafka record, this action will try to perform schema evolution.
 
 Example
 

docs/docs/cdc-ingestion/pulsar-cdc.md

@@ -228,7 +228,7 @@ Only tables with primary keys will be synchronized.
 This action will build a single combined sink for all tables. For each Pulsar topic's table to be synchronized, if the
 corresponding Paimon table does not exist, this action will automatically create the table, and its schema will be derived
 from all specified Pulsar topic's tables. If the Paimon table already exists and its schema is different from that parsed
-from Pulsar record, this action will try to preform schema evolution.
+from Pulsar record, this action will try to perform schema evolution.
 
 Example
 
@@ -312,7 +312,7 @@ There are some useful options to build Flink Pulsar Source, but they are not pro
         <tr>
           <td>pulsar.startCursor.fromMessageId</td>
           <td>EARLIEST</td>
-          <td>Sting</td>
+          <td>String</td>
           <td>Using a unique identifier of a single message to seek the start position. The common format is a triple 
               '&ltlong&gtledgerId,&ltlong&gtentryId,&ltint&gtpartitionIndex'. Specially, you can set it to 
               EARLIEST (-1, -1, -1) or LATEST (Long.MAX_VALUE, Long.MAX_VALUE, -1).

docs/docs/iceberg/rest-catalog.mdx

@@ -110,7 +110,7 @@ the query results:
 */
 ```
 
-**Schema compatabilty and Partition evolution:**
+**Schema compatibility and Partition evolution:**
 
 There is a fundamental difference between Paimon and Iceberg regarding the starting fieldId. Paimon uses fieldId 0, while Iceberg uses fieldId 1. If we create an Iceberg table using a Paimon schema directly, it will shift all fieldIds by +1, causing field disorder. However, it is possible to update the schema after table creation and start the schema from fieldId 0.
 

docs/docs/primary-key-table/pk-clustering-override.md

@@ -97,4 +97,4 @@ values, so queries like `WHERE id = 12345` remain efficient.
 
 - Merge engine: `partial-update` or `aggregation`.
 - Changelog producer: `lookup` or `full-compaction`.
-- Configue: `sequence.fields` or `record-level.expire-time`.
+- Configure: `sequence.fields` or `record-level.expire-time`.

paimon-api/src/main/java/org/apache/paimon/CoreOptions.java

@@ -491,7 +491,7 @@ public InlineElement getDescription() {
                     .booleanType()
                     .defaultValue(true)
                     .withDescription(
-                            "The legacy partition name is using `toString` fpr all types. If false, using "
+                            "The legacy partition name is using `toString` for all types. If false, using "
                                     + "cast to string for all types.");
 
     public static final ConfigOption<Integer> SNAPSHOT_NUM_RETAINED_MIN =

paimon-api/src/main/java/org/apache/paimon/types/DataTypeCasts.java

@@ -179,7 +179,7 @@ public final class DataTypeCasts {
 
     /**
      * allowExplicit false : Returns whether the source type can be safely cast to the target type
-     * without loosing information. Implicit casts are used for type widening and type
+     * without losing information. Implicit casts are used for type widening and type
      * generalization (finding a common supertype for a set of types). Implicit casts are similar to
      * the Java semantics (e.g. this is not possible: {@code int x = (String) z}).
      *

paimon-core/src/main/java/org/apache/paimon/operation/ChangelogDeletion.java

@@ -85,7 +85,7 @@ public void cleanUnusedManifests(Changelog changelog, Set<String> skippingSet) {
             }
         }
 
-        // the index and statics manifest list should handle by snapshot deletion.
+        // the index and statistics manifest list should handle by snapshot deletion.
     }
 
     @Override

paimon-core/src/main/java/org/apache/paimon/schema/SchemaManager.java

@@ -510,7 +510,7 @@ protected void updateLastColumn(
                                             && CastExecutors.resolve(sourceRootType, targetRootType)
                                                     != null,
                                     String.format(
-                                            "Column type %s[%s] cannot be converted to %s without loosing information.",
+                                            "Column type %s[%s] cannot be converted to %s without losing information.",
                                             field.name(), sourceRootType, targetRootType));
                             return new DataField(
                                     field.id(),

paimon-core/src/main/java/org/apache/paimon/utils/SnapshotManager.java

@@ -319,7 +319,7 @@ public boolean earliestFileNotExists() {
     }
 
     /**
-     * Returns a {@link Snapshot} whoes commit time is later than or equal to given timestamp mills.
+     * Returns a {@link Snapshot} whose commit time is later than or equal to given timestamp mills.
      * If there is no such a snapshot, returns null.
      */
     public @Nullable Snapshot laterOrEqualTimeMills(long timestampMills) {

paimon-core/src/test/java/org/apache/paimon/catalog/CatalogTestBase.java

@@ -2136,7 +2136,7 @@ private void baseAlterTable(Map<String, String> initOptions) throws Exception {
                 .satisfies(
                         anyCauseMatches(
                                 IllegalStateException.class,
-                                "Column type col1[DOUBLE] cannot be converted to DATE without loosing information."));
+                                "Column type col1[DOUBLE] cannot be converted to DATE without losing information."));
 
         // Alter table update a column type throws ColumnNotExistException when column does not
         // exist

paimon-core/src/test/java/org/apache/paimon/table/SchemaEvolutionTest.java

@@ -563,7 +563,7 @@ public void testUpdateFieldType() throws Exception {
                                                         "f0", DataTypes.STRING()))))
                 .isInstanceOf(IllegalStateException.class)
                 .hasMessage(
-                        "Column type f0[BIGINT] cannot be converted to STRING without loosing information.");
+                        "Column type f0[BIGINT] cannot be converted to STRING without losing information.");
         schemaManager.commitChanges(
                 Collections.singletonList(
                         SchemaChange.setOption("disable-explicit-type-casting", "false")));

paimon-flink/paimon-flink-cdc/src/test/java/org/apache/paimon/flink/action/cdc/kafka/KafkaSyncTableActionITCase.java

@@ -234,7 +234,7 @@ protected void runSingleTableSchemaEvolutionWithSchemaIncludeRecord(
                         "+I[105, hammer, 14oz carpenter's hammer, 0.875, 24]");
         waitForResult(expected, table, rowType, primaryKeys);
 
-        // column type covert exception (int64 -> string)
+        // column type convert exception (int64 -> string)
         writeRecordsToKafka(
                 topic, "kafka/%s/table/schema/%s/%s-data-5.txt", format, sourceDir, format);
 

paimon-flink/paimon-flink-common/src/test/java/org/apache/paimon/flink/SchemaChangeITCase.java

@@ -273,7 +273,7 @@ public void testModifyColumnTypeBooleanAndNumeric() {
         assertThatThrownBy(() -> sql("ALTER TABLE T MODIFY (f BOOLEAN)"))
                 .hasRootCauseInstanceOf(IllegalStateException.class)
                 .hasRootCauseMessage(
-                        "Column type f[DOUBLE] cannot be converted to BOOLEAN without loosing information.");
+                        "Column type f[DOUBLE] cannot be converted to BOOLEAN without losing information.");
     }
 
     @Test
@@ -1605,13 +1605,13 @@ public void testDisableExplicitTypeCasting(String formatType) {
         assertThat(sql("SELECT * FROM T")).containsExactlyInAnyOrder(Row.of(1, 10), Row.of(2, 20));
         assertThatCode(() -> sql("ALTER TABLE T MODIFY v SMALLINT"))
                 .hasStackTraceContaining(
-                        "Column type v[INT] cannot be converted to SMALLINT without loosing information");
+                        "Column type v[INT] cannot be converted to SMALLINT without losing information");
         sql("ALTER TABLE T MODIFY v BIGINT");
         assertThat(sql("SELECT * FROM T"))
                 .containsExactlyInAnyOrder(Row.of(1, 10L), Row.of(2, 20L));
         assertThatCode(() -> sql("ALTER TABLE T MODIFY v INT"))
                 .hasStackTraceContaining(
-                        "Column type v[BIGINT] cannot be converted to INT without loosing information");
+                        "Column type v[BIGINT] cannot be converted to INT without losing information");
         // disable explicit type casting
         sql("ALTER TABLE T SET ('disable-explicit-type-casting' = 'false')");
         sql("ALTER TABLE T MODIFY v INT");

paimon-hive/paimon-hive-connector-common/src/test/java/org/apache/paimon/iceberg/IcebergHiveMetadataCommitterITCaseBase.java

@@ -123,7 +123,7 @@ public void testPrimaryKeyTable() throws Exception {
                         .toString()
                         .contains("iceberg/test_db"));
 
-        // specify a dedicated hive database and table for paimon iceberg commiter
+        // specify a dedicated hive database and table for paimon iceberg committer
         tEnv.executeSql(
                 "CREATE TABLE my_paimon.test_db.t1 ( pt INT, id INT, data STRING, PRIMARY KEY (pt, id) NOT ENFORCED ) "
                         + "PARTITIONED BY (pt) WITH "
@@ -216,7 +216,7 @@ public void testAppendOnlyTable() throws Exception {
                         tEnv.executeSql(
                                 "SELECT data, id, pt FROM my_iceberg.test_db.t WHERE id > 1 ORDER BY pt, id")));
 
-        // specify a dedicated hive database and table for paimon iceberg commiter
+        // specify a dedicated hive database and table for paimon iceberg committer
         tEnv.executeSql(
                 "CREATE TABLE my_paimon.test_db.t1 ( pt INT, id INT, data STRING ) PARTITIONED BY (pt) WITH "
                         + "( 'metadata.iceberg.storage' = 'hive-catalog', 'metadata.iceberg.uri' = '', 'file.format' = 'avro', "

paimon-spark/paimon-spark-common/src/main/scala/org/apache/paimon/spark/commands/PaimonSparkWriter.scala

@@ -434,7 +434,7 @@ case class PaimonSparkWriter(
     postCommit(commitMessages)
   }
 
-  /** Boostrap and repartition for cross partition mode. */
+  /** Bootstrap and repartition for cross partition mode. */
   private def bootstrapAndRepartitionByKeyHash(
       data: DataFrame,
       parallelism: Int,

paimon-spark/paimon-spark-common/src/main/scala/org/apache/spark/sql/catalyst/parser/extensions/RewritePaimonFunctionCommands.scala

@@ -68,7 +68,7 @@ case class RewritePaimonFunctionCommands(spark: SparkSession)
             ifExists,
             replace) =>
         if (isPaimonBuildInFunction(funcIdent)) {
-          throw new UnsupportedOperationException(s"Can't create build-in function: $funcIdent")
+          throw new UnsupportedOperationException(s"Can't create built-in function: $funcIdent")
         }
         val v1Function = CatalogFunction(funcIdent, className, resources)
         CreatePaimonV1FunctionCommand(v1FunctionCatalog, v1Function, ifExists, replace)
@@ -77,7 +77,7 @@ case class RewritePaimonFunctionCommands(spark: SparkSession)
             CatalogAndFunctionIdentifier(v1FunctionCatalog: SupportV1Function, funcIdent, false),
             ifExists) =>
         if (isPaimonBuildInFunction(funcIdent)) {
-          throw new UnsupportedOperationException(s"Can't drop build-in function: $funcIdent")
+          throw new UnsupportedOperationException(s"Can't drop built-in function: $funcIdent")
         }
         // The function may be v1 function or not, anyway it can be safely deleted here.
         DropPaimonV1FunctionCommand(v1FunctionCatalog, funcIdent, ifExists)

paimon-spark/paimon-spark-ut/src/test/scala/org/apache/paimon/spark/sql/DataFrameWriteTestBase.scala

@@ -888,7 +888,7 @@ abstract class DataFrameWriteTestBase extends PaimonSparkTestBase {
       .option("write.merge-schema", "true")
       .save(location)
 
-    // Case 2: colum b and d are absent in the coming data
+    // Case 2: column b and d are absent in the coming data
     val df3 = Seq((4, 45.6d), (5, 56.7d))
       .toDF("a", "c")
     df3.write

paimon-spark/paimon-spark-ut/src/test/scala/org/apache/paimon/spark/sql/PaimonV1FunctionTestBase.scala

@@ -95,7 +95,7 @@ abstract class PaimonV1FunctionTestBase extends PaimonSparkTestWithRestCatalogBa
     }
   }
 
-  test("Paimon V1 Function: select with build-in function") {
+  test("Paimon V1 Function: select with built-in function") {
     withUserDefinedFunction("udf_add2" -> false) {
       sql(s"""
              |CREATE FUNCTION udf_add2 AS '$UDFExampleAdd2Class'
@@ -144,18 +144,18 @@ abstract class PaimonV1FunctionTestBase extends PaimonSparkTestWithRestCatalogBa
   }
 
   test("Paimon V1 Function: unsupported operation") {
-    // create a build-in function
+    // create a built-in function
     assert(intercept[Exception] {
       sql(s"""
              |CREATE FUNCTION sys.max_pt AS '$UDFExampleAdd2Class'
              |USING JAR '$testUDFJarPath'
              |""".stripMargin)
-    }.getMessage.contains("Can't create build-in function"))
+    }.getMessage.contains("Can't create built-in function"))
 
-    // drop a build-in function
+    // drop a built-in function
     assert(intercept[Exception] {
       sql("DROP FUNCTION sys.max_pt")
-    }.getMessage.contains("Can't drop build-in function"))
+    }.getMessage.contains("Can't drop built-in function"))
   }
 
   test("Paimon V1 Function: user defined aggregate function") {