Modify some description information and comments

Author: huyuanfeng

docs/layouts/shortcodes/generated/auto_scaler_configuration.html

@@ -192,7 +192,7 @@
             <td><h5>job.autoscaler.scaling.key-group.partitions.adjust.mode</h5></td>
             <td style="word-wrap: break-word;">DEFAULT</td>
             <td><p>Enum</p></td>
-            <td>How to adjust the parallelism of Source vertex or upstream shuffle is keyBy<br /><br />Possible values:<ul><li>"DEFAULT": This mode ensures that the parallelism adjustment attempts to evenly distribute data across subtasks. It is particularly effective for source vertices that are aware of partition counts or vertices after 'keyBy' operation. The goal is to have the number of key groups or partitions be divisible by the set parallelism, ensuring even data distribution and reducing data skew.</li><li>"MAXIMIZE_UTILISATION": This model is to maximize resource utilization. In this mode, an attempt is made to set the minimum degree of parallelism that meets the current consumption rate requirements. Unlike the default mode, it is not enforced that the number of key groups or partitions is divisible by the degree of parallelism.</li></ul></td>
+            <td>How to adjust the parallelism of Source vertex or upstream shuffle is keyBy<br /><br />Possible values:<ul><li>"DEFAULT": This mode ensures that the parallelism adjustment attempts to evenly distribute data across subtasks. It is particularly effective for source vertices that are aware of partition counts or vertices after 'keyBy' operation. The goal is to have the number of key groups or partitions be divisible by the set parallelism, ensuring even data distribution and reducing data skew.</li><li>"MAXIMIZE_UTILISATION": This model is to maximize resource utilization. In this mode, an attempt is made to set the minimum parallelism that meets the current consumption rate requirements. Unlike the default mode, it is not enforced that the number of key groups or partitions is divisible by the degree of parallelism.</li></ul></td>
         </tr>
         <tr>
             <td><h5>job.autoscaler.stabilization.interval</h5></td>

flink-autoscaler/src/main/java/org/apache/flink/autoscaler/JobVertexScaler.java

@@ -355,8 +355,8 @@ private boolean detectIneffectiveScaleUp(
      * maxParallelism).
      *
      * <p>Also, if we know the number of partitions or key groups corresponding to the current
-     * vertex, the degree of parallelism will be adjusted accordingly. For specific logic, please
-     * refer to {@link ParallelismAdjuster}.
+     * vertex, the parallelism will be adjusted accordingly. For specific logic, please refer to
+     * {@link ParallelismAdjuster}.
      */
     @VisibleForTesting
     protected static <KEY, Context extends JobAutoScalerContext<KEY>> int scale(

flink-autoscaler/src/main/java/org/apache/flink/autoscaler/ParallelismAdjuster.java

@@ -83,7 +83,7 @@ public static <KEY, Context extends JobAutoScalerContext<KEY>> int adjust(
         }
 
         // When adjusting the parallelism after rounding up cannot
-        // find the right degree of parallelism to meet requirements,
+        // find the right parallelism to meet requirements,
         // Try to find the smallest parallelism that can satisfy the current consumption rate.
         int p =
                 calculateMinimumParallelism(
@@ -124,14 +124,14 @@ private static int calculateMinimumParallelism(
 
     /** The mode of the key group or parallelism adjustment. */
     public enum KeyGroupOrPartitionsAdjustMode implements DescribedEnum {
-        DEFAULT(
+        ABSOLUTELY_EVENLY_DISTRIBUTION(
                 "This mode ensures that the parallelism adjustment attempts to evenly distribute data across subtasks"
                         + ". It is particularly effective for source vertices that are aware of partition counts or vertices after "
                         + "'keyBy' operation. The goal is to have the number of key groups or partitions be divisible by the set parallelism, ensuring even data distribution and reducing data skew."),
 
         MAXIMIZE_UTILISATION(
                 "This model is to maximize resource utilization. In this mode, an attempt is made to set"
-                        + " the minimum degree of parallelism that meets the current consumption rate requirements. Unlike the default mode, it is not enforced that the number of key groups or partitions is divisible by the degree of parallelism."),
+                        + " the parallelism that meets the current consumption rate requirements. Unlike the default mode, it is not enforced that the number of key groups or partitions is divisible by the parallelism."),
         ;
 
         private final InlineElement description;

flink-autoscaler/src/main/java/org/apache/flink/autoscaler/config/AutoScalerOptions.java

@@ -358,7 +358,8 @@ private static ConfigOptions.OptionBuilder autoScalerConfig(String key) {
                     autoScalerConfig("scaling.key-group.partitions.adjust.mode")
                             .enumType(ParallelismAdjuster.KeyGroupOrPartitionsAdjustMode.class)
                             .defaultValue(
-                                    ParallelismAdjuster.KeyGroupOrPartitionsAdjustMode.DEFAULT)
+                                    ParallelismAdjuster.KeyGroupOrPartitionsAdjustMode
+                                            .ABSOLUTELY_EVENLY_DISTRIBUTION)
                             .withFallbackKeys(
                                     oldOperatorConfigKey(
                                             "scaling.key-group.partitions.adjust.mode"))