Update connector-microsoft-fabric-warehouse.md

Author: KrishnakumarRukmangathan

articles/data-factory/connector-microsoft-fabric-warehouse.md

@@ -524,7 +524,7 @@ Settings specific to Microsoft Fabric Warehouse are available in the Source Opti
 
 | Name                     | Description                                                  | Required | Allowed Values | Data flow script property |
 | :--------------------------- | :----------------------------------------------------------- | :------- |:-------------------- |:------- |
-| Input                          | Select whether you point your source at a table (equivalent of Select * from <tablename>) or enter a custom SQL query or retrieve data from a Stored Procedure. Query: If you select Query in the input field, enter a SQL query for your source. This setting overrides any table that you've chosen in the dataset. **Order By** clauses aren't supported here, but you can set a full SELECT FROM statement. You can also use user-defined table functions. **select * from udfGetData()** is a UDF in SQL that returns a table. This query will produce a source table that you can use in your data flow. Using queries is also a great way to reduce rows for testing or for lookups.SQL Example: ```Select * from MyTable where customerId > 1000 and customerId < 2000``` | Yes      | Table or Query or Stored Procedure    | format: 'table' |
+| Input                          | Select whether you point your source at a table (equivalent of Select * from tablename) or enter a custom SQL query or retrieve data from a Stored Procedure. Query: If you select Query in the input field, enter a SQL query for your source. This setting overrides any table that you've chosen in the dataset. **Order By** clauses aren't supported here, but you can set a full SELECT FROM statement. You can also use user-defined table functions. **select * from udfGetData()** is a UDF in SQL that returns a table. This query will produce a source table that you can use in your data flow. Using queries is also a great way to reduce rows for testing or for lookups.SQL Example: ```Select * from MyTable where customerId > 1000 and customerId < 2000``` | Yes      | Table or Query or Stored Procedure    | format: 'table' |
 | Batch size               | Enter a batch size to chunk large data into reads. In data flows, this setting will be used to set Spark columnar caching. This is an option field, which will use Spark defaults if it is left blank. | No       | Numeral values | batchSize: 1234|
 | Isolation Level          | The default for SQL sources in mapping data flow is read uncommitted. You can change the isolation level here to one of these values:•	Read Committed  • Read Uncommitted • Repeatable Read • Serializable • None (ignore isolation level) | Yes       | •	Read Committed  • Read Uncommitted • Repeatable Read • Serializable • None (ignore isolation level) | isolationLevel|