Merge pull request #18744 from changeworld/fix/typo2

Fix typo

Author: ktoliver

articles/azure-databricks/databricks-extract-load-sql-data-warehouse.md

@@ -13,15 +13,15 @@ ms.date: 07/26/2018
 ---
 # Tutorial: Extract, transform, and load data using Azure Databricks
 
-In this tutorial, you perform an ETL (extract, transform, and load data) operation using Azure Databricks. You extract data from Azure Data Lake Store into Azure Databricks, run transformations on the data in Azure Databricks, and then load the transformed data into Azure SQL Data Warehouse. 
+In this tutorial, you perform an ETL (extract, transform, and load data) operation using Azure Databricks. You extract data from Azure Data Lake Store into Azure Databricks, run transformations on the data in Azure Databricks, and then load the transformed data into Azure SQL Data Warehouse.
 
 The steps in this tutorial use the SQL Data Warehouse connector for Azure Databricks to transfer data to Azure Databricks. This connector, in turn, uses Azure Blob Storage as temporary storage for the data being transferred between an Azure Databricks cluster and Azure SQL Data Warehouse.
 
 The following illustration shows the application flow:
 
 ![Azure Databricks with Data Lake Store and SQL Data Warehouse](./media/databricks-extract-load-sql-data-warehouse/databricks-extract-transform-load-sql-datawarehouse.png "Azure Databricks with Data Lake Store and SQL Data Warehouse")
 
-This tutorial covers the following tasks: 
+This tutorial covers the following tasks:
 
 > [!div class="checklist"]
 > * Create an Azure Databricks workspace
@@ -58,7 +58,7 @@ In this section, you create an Azure Databricks workspace using the Azure portal
 
     ![Create an Azure Databricks workspace](./media/databricks-extract-load-sql-data-warehouse/create-databricks-workspace.png "Create an Azure Databricks workspace")
 
-    Provide the following values: 
+    Provide the following values:
 
     |Property  |Description  |
     |---------|---------|
@@ -89,14 +89,14 @@ In this section, you create an Azure Databricks workspace using the Azure portal
     Accept all other defaults other than the following values:
 
     * Enter a name for the cluster.
-    * For this article, create a cluster with **4.0** runtime. 
+    * For this article, create a cluster with **4.0** runtime.
     * Make sure you select the **Terminate after \_\_ minutes of inactivity** checkbox. Provide a duration (in minutes) to terminate the cluster, if the cluster is not being used.
 
     Select **Create cluster**. Once the cluster is running, you can attach notebooks to the cluster and run Spark jobs.
 
 ## Create an Azure Data Lake Store account
 
-In this section, you create an Azure Data Lake Store account and associate an Azure Active Directory service principal with it. Later in this tutorial, you use this service principal in Azure Databricks to access Azure Data Lake Store. 
+In this section, you create an Azure Data Lake Store account and associate an Azure Active Directory service principal with it. Later in this tutorial, you use this service principal in Azure Databricks to access Azure Data Lake Store.
 
 1. From the [Azure portal](https://portal.azure.com), select **Create a resource** > **Storage** > **Data Lake Store**.
 3. In the **New Data Lake Store** blade, provide the values as shown in the following screenshot:
@@ -183,7 +183,7 @@ When programmatically logging in, you need to pass the tenant ID with your authe
 
 1. Copy the **Directory ID**. This value is your tenant ID.
 
-   ![tenant ID](./media/databricks-extract-load-sql-data-warehouse/copy-directory-id.png) 
+   ![tenant ID](./media/databricks-extract-load-sql-data-warehouse/copy-directory-id.png)
 
 ## Upload data to Data Lake Store
 
@@ -300,7 +300,7 @@ You have now extracted the data from Azure Data Lake Store into Azure Databricks
 
 ## Transform data in Azure Databricks
 
-The raw sample data **small_radio_json.json** captures the audience for a radio station and has a variety of columns. In this section, you transform the data to only retrieve specific columns in from the dataset. 
+The raw sample data **small_radio_json.json** captures the audience for a radio station and has a variety of columns. In this section, you transform the data to only retrieve specific columns in from the dataset.
 
 1. Start by retrieving only the columns *firstName*, *lastName*, *gender*, *location*, and *level* from the dataframe you already created.
 
@@ -334,7 +334,7 @@ The raw sample data **small_radio_json.json** captures the audience for a radio
         |  Margaux|     Smith|     F|Atlanta-Sandy Spr...| free|
         +---------+----------+------+--------------------+-----+
 
-2.  You can further transform this data to rename the column **level** to **subscription_type**.
+2. You can further transform this data to rename the column **level** to **subscription_type**.
 
         val renamedColumnsDf = specificColumnsDf.withColumnRenamed("level", "subscription_type")
         renamedColumnsDf.show()
@@ -376,7 +376,7 @@ As mentioned earlier, the SQL date warehouse connector uses Azure Blob Storage a
 
         val blobStorage = "<STORAGE ACCOUNT NAME>.blob.core.windows.net"
         val blobContainer = "<CONTAINER NAME>"
-        val blobAccessKey =  "<ACCESS KEY>"
+        val blobAccessKey = "<ACCESS KEY>"
 
 2. Specify a temporary folder that will be used while moving data between Azure Databricks and Azure SQL Data Warehouse.
 
@@ -391,23 +391,23 @@ As mentioned earlier, the SQL date warehouse connector uses Azure Blob Storage a
 
         //SQL Data Warehouse related settings
         val dwDatabase = "<DATABASE NAME>"
-        val dwServer = "<DATABASE SERVER NAME>" 
+        val dwServer = "<DATABASE SERVER NAME>"
         val dwUser = "<USER NAME>"
         val dwPass = "<PASSWORD>"
-        val dwJdbcPort =  "1433"
+        val dwJdbcPort = "1433"
         val dwJdbcExtraOptions = "encrypt=true;trustServerCertificate=true;hostNameInCertificate=*.database.windows.net;loginTimeout=30;"
         val sqlDwUrl = "jdbc:sqlserver://" + dwServer + ".database.windows.net:" + dwJdbcPort + ";database=" + dwDatabase + ";user=" + dwUser+";password=" + dwPass + ";$dwJdbcExtraOptions"
         val sqlDwUrlSmall = "jdbc:sqlserver://" + dwServer + ".database.windows.net:" + dwJdbcPort + ";database=" + dwDatabase + ";user=" + dwUser+";password=" + dwPass
 
-5. Run the following snippet to load the transformed dataframe, **renamedColumnsDf**, as a table in SQL data warehouse. This snippet creates a table called **SampleTable** in the SQL database. Please note that Azure SQL DW requires a master key.  You can create a master key by executing "CREATE MASTER KEY;" command in SQL Server Management Studio.
+5. Run the following snippet to load the transformed dataframe, **renamedColumnsDf**, as a table in SQL data warehouse. This snippet creates a table called **SampleTable** in the SQL database. Please note that Azure SQL DW requires a master key. You can create a master key by executing "CREATE MASTER KEY;" command in SQL Server Management Studio.
 
         spark.conf.set(
           "spark.sql.parquet.writeLegacyFormat",
           "true")
         
         renamedColumnsDf.write
             .format("com.databricks.spark.sqldw")
-            .option("url", sqlDwUrlSmall) 
+            .option("url", sqlDwUrlSmall)
             .option("dbtable", "SampleTable")
             .option( "forward_spark_azure_storage_credentials","True")
             .option("tempdir", tempDir)
@@ -428,9 +428,9 @@ After you have finished running the tutorial, you can terminate the cluster. To
 
 ![Stop a Databricks cluster](./media/databricks-extract-load-sql-data-warehouse/terminate-databricks-cluster.png "Stop a Databricks cluster")
 
-If you do not manually terminate the cluster it will automatically stop, provided you selected the **Terminate after __ minutes of inactivity** checkbox while creating the cluster. In such a case, the cluster automatically stops if it has been inactive for the specified time.
+If you do not manually terminate the cluster it will automatically stop, provided you selected the **Terminate after \_\_ minutes of inactivity** checkbox while creating the cluster. In such a case, the cluster automatically stops if it has been inactive for the specified time.
 
-## Next steps 
+## Next steps
 In this tutorial, you learned how to:
 
 > [!div class="checklist"]