Merge pull request #89347 from MayMSFT/patch-21

Update how-to-create-register-datasets.md

Author: PRMerger6

articles/machine-learning/service/how-to-create-register-datasets.md

@@ -106,6 +106,16 @@ titanic_ds.take(3).to_pandas_dataframe()
 1|2|1|1|Cumings, Mrs. John Bradley (Florence Briggs Th...|female|38.0|1|0|PC 17599|71.2833|C85|C
 2|3|1|3|Heikkinen, Miss. Laina|female|26.0|0|0|STON/O2. 3101282|7.9250||S
 
+Use the [`from_sql_query()`](https://docs.microsoft.com/python/api/azureml-core/azureml.data.dataset_factory.tabulardatasetfactory?view=azure-ml-py#from-sql-query-query--validate-true--set-column-types-none-) method on `TabularDatasetFactory` class to read from Azure SQL Database.
+
+```Python
+
+from azureml.core import Dataset, Datastore
+
+# create tabular dataset from a SQL database in datastore
+sql_datastore = Datastore.get(workspace, 'mssql')
+sql_ds = Dataset.Tabular.from_sql_query((sql_datastore, 'SELECT * FROM my_table'))
+```
 Use the [`with_timestamp_columns()`](https://docs.microsoft.com/python/api/azureml-core/azureml.data.tabulardataset?view=azure-ml-py#with-timestamp-columns-fine-grain-timestamp--coarse-grain-timestamp-none--validate-false-) method on `TabularDataset` class to enable easy and efficient filtering by time. More examples and details can be found [here](http://aka.ms/azureml-tsd-notebook). 
 
 ```Python