[MINOR][DOC] spark.executor.memoryOverhead is not cluster-mode only

### What changes were proposed in this pull request?

Remove "in cluster mode" from the description of `spark.executor.memoryOverhead`

### Why are the changes needed?

fix correctness issue in documentaion

### Does this PR introduce _any_ user-facing change?

yes, users may not get confused about the description `spark.executor.memoryOverhead`

### How was this patch tested?

pass GA doc generation

Closes #30311 from yaooqinn/minordoc.

Authored-by: Kent Yao <[email protected]>
Signed-off-by: Takeshi Yamamuro <[email protected]>

Author: yaooqinn

core/src/main/scala/org/apache/spark/internal/config/package.scala

@@ -302,8 +302,8 @@ package object config {
     .createWithDefaultString("1g")
 
   private[spark] val EXECUTOR_MEMORY_OVERHEAD = ConfigBuilder("spark.executor.memoryOverhead")
-    .doc("The amount of non-heap memory to be allocated per executor in cluster mode, " +
-      "in MiB unless otherwise specified.")
+    .doc("The amount of non-heap memory to be allocated per executor, in MiB unless otherwise" +
+      " specified.")
     .version("2.3.0")
     .bytesConf(ByteUnit.MiB)
     .createOptional

docs/configuration.md

@@ -274,10 +274,9 @@ of the most common options to set are:
  <td><code>spark.executor.memoryOverhead</code></td>
   <td>executorMemory * 0.10, with minimum of 384 </td>
   <td>
-    Amount of additional memory to be allocated per executor process in cluster mode, in MiB unless
-    otherwise specified. This is memory that accounts for things like VM overheads, interned strings,
-    other native overheads, etc. This tends to grow with the executor size (typically 6-10%).
-    This option is currently supported on YARN and Kubernetes.
+    Amount of additional memory to be allocated per executor process, in MiB unless otherwise specified.
+    This is memory that accounts for things like VM overheads, interned strings, other native overheads, etc.
+    This tends to grow with the executor size (typically 6-10%). This option is currently supported on YARN and Kubernetes.
     <br/>
     <em>Note:</em> Additional memory includes PySpark executor memory 
     (when <code>spark.executor.pyspark.memory</code> is not configured) and memory used by other