[MINOR][SQL] Fix versions in the SQL migration guide for Spark 3.1

### What changes were proposed in this pull request?
Change _To restore the behavior before Spark **3.0**_ to _To restore the behavior before Spark **3.1**_ in the SQL migration guide while telling about the behaviour before new version 3.1.

### Why are the changes needed?
To have correct info in the SQL migration guide.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
N/A

Closes #29336 from MaxGekk/fix-version-in-sql-migration.

Authored-by: Max Gekk <[email protected]>
Signed-off-by: HyukjinKwon <[email protected]>

Author: MaxGekk

docs/sql-migration-guide.md

@@ -24,9 +24,9 @@ license: |
 
 ## Upgrading from Spark SQL 3.0 to 3.1
 
-  - In Spark 3.1, grouping_id() returns long values. In Spark version 3.0 and earlier, this function returns int values. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.integerGroupingId` to `true`.
+  - In Spark 3.1, grouping_id() returns long values. In Spark version 3.0 and earlier, this function returns int values. To restore the behavior before Spark 3.1, you can set `spark.sql.legacy.integerGroupingId` to `true`.
 
-  - In Spark 3.1, SQL UI data adopts the `formatted` mode for the query plan explain results. To restore the behavior before Spark 3.0, you can set `spark.sql.ui.explainMode` to `extended`.
+  - In Spark 3.1, SQL UI data adopts the `formatted` mode for the query plan explain results. To restore the behavior before Spark 3.1, you can set `spark.sql.ui.explainMode` to `extended`.
 
   - In Spark 3.1, `from_unixtime`, `unix_timestamp`,`to_unix_timestamp`, `to_timestamp` and `to_date` will fail if the specified datetime pattern is invalid. In Spark 3.0 or earlier, they result `NULL`.