[SPARK-27870][PYTHON][FOLLOW-UP] Rename spark.sql.pandas.udf.buffer.size to spark.sql.execution.pandas.udf.buffer.size

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

This PR renames `spark.sql.pandas.udf.buffer.size` to `spark.sql.execution.pandas.udf.buffer.size` to be more consistent with other pandas configuration prefixes, given:
-  `spark.sql.execution.pandas.arrowSafeTypeConversion`
- `spark.sql.execution.pandas.respectSessionTimeZone`
- `spark.sql.legacy.execution.pandas.groupedMap.assignColumnsByName`
- other configurations like `spark.sql.execution.arrow.*`.

### Why are the changes needed?

To make configuration names consistent.

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

No because this configuration was not released yet.

### How was this patch tested?

Existing tests should cover.

Closes #27450 from HyukjinKwon/SPARK-27870-followup.

Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>

python/pyspark/sql/tests/test_pandas_udf_scalar.py

@@ -868,7 +868,7 @@ class ScalarPandasUDFTests(ReusedSQLTestCase):
 
             with QuietTest(self.sc):
                 with self.sql_conf({"spark.sql.execution.arrow.maxRecordsPerBatch": 1,
-                                    "spark.sql.pandas.udf.buffer.size": 4}):
+                                    "spark.sql.execution.pandas.udf.buffer.size": 4}):
                     self.spark.range(10).repartition(1) \
                         .select(test_close(col("id"))).limit(2).collect()
                     # wait here because python udf worker will take some time to detect

sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala

@@ -1600,7 +1600,7 @@ object SQLConf {
       .createWithDefault(10000)
 
   val PANDAS_UDF_BUFFER_SIZE =
-    buildConf("spark.sql.pandas.udf.buffer.size")
+    buildConf("spark.sql.execution.pandas.udf.buffer.size")
       .doc(
         s"Same as ${BUFFER_SIZE} but only applies to Pandas UDF executions. If it is not set, " +
         s"the fallback is ${BUFFER_SIZE}. Note that Pandas execution requires more than 4 bytes. " +