Freshness review

Author: spelluru

articles/stream-analytics/sql-database-upsert.md

@@ -3,12 +3,12 @@ title: Update or merge records in Azure SQL Database with Azure Functions
 description: This article describes how to use Azure Functions to update or merge records from Azure Stream Analytics to Azure SQL Database
 ms.service: stream-analytics
 ms.topic: how-to
-ms.date: 12/03/2021
+ms.date: 02/27/2024
 ---
 
 # Update or merge records in Azure SQL Database with Azure Functions
 
-Currently, [Azure Stream Analytics](./index.yml) (ASA) only supports inserting (appending) rows to SQL outputs ([Azure SQL Databases](./sql-database-output.md), and [Azure Synapse Analytics](./azure-synapse-analytics-output.md)). This article discusses workarounds to enable UPDATE, UPSERT, or MERGE on SQL databases, with Azure Functions as the intermediary layer.
+Currently, [Azure Stream Analytics](./index.yml) (ASA) supports only inserting (appending) rows to SQL outputs ([Azure SQL Databases](./sql-database-output.md), and [Azure Synapse Analytics](./azure-synapse-analytics-output.md)). This article discusses workarounds to enable UPDATE, UPSERT, or MERGE on SQL databases, with Azure Functions as the intermediary layer.
 
 Alternative options to Azure Functions are presented at the end.
 
@@ -22,14 +22,14 @@ Writing data in a table can generally be done in the following manner:
 |Replace|[MERGE](/sql/t-sql/statements/merge-transact-sql) (UPSERT)|Unique key|
 |Accumulate|MERGE (UPSERT) with compound assignment [operator](/sql/t-sql/queries/update-transact-sql#arguments) (`+=`, `-=`...)|Unique key and accumulator|
 
-To illustrate the differences, we can look at what happens when ingesting the following two records:
+To illustrate the differences, look at what happens when ingesting the following two records:
 
 |Arrival_Time|Device_Id|Measure_Value|
 |-|-|-|
 |10:00|A|1|
 |10:05|A|20|
 
-In **append** mode, we insert the two records. The equivalent T-SQL statement is:
+In the **append** mode, we insert two records. The equivalent T-SQL statement is:
 
 ```SQL
 INSERT INTO [target] VALUES (...);
@@ -42,7 +42,7 @@ Resulting in:
 |10:00|A|1|
 |10:05|A|20|
 
-In **replace** mode, we get only the last value by key. Here we will use **Device_Id as the key.** The equivalent T-SQL statement is:
+In **replace** mode, we get only the last value by key. Here we use **Device_Id as the key.** The equivalent T-SQL statement is:
 
 ```SQL
 MERGE INTO [target] t
@@ -65,7 +65,7 @@ Resulting in:
 |-|-|-|
 |10:05|A|20|
 
-Finally, in **accumulate** mode we sum `Value` with a compound assignment operator (`+=`). Here also we will use Device_Id as the key:
+Finally, in **accumulate** mode we sum `Value` with a compound assignment operator (`+=`). Here also we use Device_Id as the key:
 
 ```SQL
 MERGE INTO [target] t
@@ -90,15 +90,15 @@ Resulting in:
 
 For **performance** considerations, the ASA SQL database output adapters currently only support append mode natively. These adapters use bulk insert to maximize throughput and limit back pressure.
 
-This article shows how to use Azure Functions to implement Replace and Accumulate modes for ASA. By using a function as an intermediary layer, the potential write performance won't affect the streaming job. In this regard, using Azure Functions will work best with Azure SQL. With Synapse SQL, switching from bulk to row-by-row statements may create greater performance issues.
+This article shows how to use Azure Functions to implement Replace and Accumulate modes for ASA. When you use a function as an intermediary layer, the potential write performance won't affect the streaming job. In this regard, using Azure Functions works best with Azure SQL. With Synapse SQL, switching from bulk to row-by-row statements might create greater performance issues.
 
 ## Azure Functions Output
 
-In our job, we'll replace the ASA SQL output by the [ASA Azure Functions output](./azure-functions-output.md). The UPDATE, UPSERT, or MERGE capabilities will be implemented in the function.
+In our job, we replace the ASA SQL output by the [ASA Azure Functions output](./azure-functions-output.md). The UPDATE, UPSERT, or MERGE capabilities are implemented in the function.
 
 There are currently two options to access a SQL Database in a function. First is the [Azure SQL output binding](../azure-functions/functions-bindings-azure-sql.md). It's currently limited to C#, and only offers replace mode. Second is to compose a SQL query to be submitted via the appropriate [SQL driver](/sql/connect/sql-connection-libraries) ([Microsoft.Data.SqlClient](https://github.com/dotnet/SqlClient) for .NET).
 
-For both samples below, we'll assume the following table schema. The binding option requires **a primary key** to be set on the target table. It's not necessary, but recommended, when using a SQL driver.
+For both the following samples, we assume the following table schema. The binding option requires **a primary key** to be set on the target table. It's not necessary, but recommended, when using a SQL driver.
 
 ```SQL
 CREATE TABLE [dbo].[device_updated](
@@ -130,7 +130,7 @@ This sample was built on:
 
 To better understand the binding approach, it's recommended to follow [this tutorial](https://github.com/Azure/azure-functions-sql-extension#quick-start).
 
-First, create a default HttpTrigger function app by following this [tutorial](../azure-functions/create-first-function-vs-code-csharp.md?tabs=in-process). The following information will be used:
+First, create a default HttpTrigger function app by following this [tutorial](../azure-functions/create-first-function-vs-code-csharp.md?tabs=in-process). The following information is used:
 
 - Language: `C#`
 - Runtime: `.NET 6` (under function/runtime v4)
@@ -233,7 +233,7 @@ Update the `Device` class and mapping section to match your own schema:
         public DateTime Timestamp { get; set; }
 ```
 
-You can now test the wiring between the local function and the database by debugging (F5 in VS Code). The SQL database needs to be reachable from your machine. [SSMS](/sql/ssms/sql-server-management-studio-ssms) can be used to check connectivity. Then a tool like [Postman](https://www.postman.com/) can be used to issue POST requests to the local endpoint. A request with an empty body should return http 204. A request with an actual payload should be persisted in the destination table (in replace / update mode). Here's a sample payload corresponding to the schema used in this sample:
+You can now test the wiring between the local function and the database by debugging (F5 in Visual Studio Code). The SQL database needs to be reachable from your machine. [SSMS](/sql/ssms/sql-server-management-studio-ssms) can be used to check connectivity. Then a tool like [Postman](https://www.postman.com/) can be used to issue POST requests to the local endpoint. A request with an empty body should return http 204. A request with an actual payload should be persisted in the destination table (in replace / update mode). Here's a sample payload corresponding to the schema used in this sample:
 
 ```JSON
 [{"DeviceId":3,"Value":13.4,"Timestamp":"2021-11-30T03:22:12.991Z"},{"DeviceId":4,"Value":41.4,"Timestamp":"2021-11-30T03:22:12.991Z"}]
@@ -256,7 +256,7 @@ This sample was built on:
 - [.NET 6.0](/dotnet/core/whats-new/dotnet-6)
 - Microsoft.Data.SqlClient [4.0.0](https://www.nuget.org/packages/Microsoft.Data.SqlClient/)
 
-First, create a default HttpTrigger function app by following this [tutorial](../azure-functions/create-first-function-vs-code-csharp.md?tabs=in-process). The following information will be used:
+First, create a default HttpTrigger function app by following this [tutorial](../azure-functions/create-first-function-vs-code-csharp.md?tabs=in-process). The following information is used:
 
 - Language: `C#`
 - Runtime: `.NET 6` (under function/runtime v4)
@@ -371,11 +371,11 @@ The function can then be defined as an output in the ASA job, and used to replac
 
 ## Alternatives
 
-Outside of Azure Functions, there are multiple ways to achieve the expected result. We'll mention the most likely solutions below.
+Outside of Azure Functions, there are multiple ways to achieve the expected result. This section provides some of them. 
 
 ### Post-processing in the target SQL Database
 
-A background task will operate once the data is inserted in the database via the standard ASA SQL outputs.
+A background task operates once the data is inserted in the database via the standard ASA SQL outputs.
 
 For Azure SQL, `INSTEAD OF` [DML triggers](/sql/relational-databases/triggers/dml-triggers?view=azuresqldb-current&preserve-view=true) can be used to intercept the INSERT commands issued by ASA:
 
@@ -402,13 +402,13 @@ END;
 
 For Synapse SQL, ASA can insert into a [staging table](../synapse-analytics/sql/data-loading-best-practices.md#load-to-a-staging-table). A recurring task can then transform the data as needed into an intermediary table. Finally the [data is moved](../synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-partition.md#partition-switching) to the production table.
 
-### Pre-processing in Azure Cosmos DB
+### Preprocessing in Azure Cosmos DB
 
 Azure Cosmos DB [supports UPSERT natively](./stream-analytics-documentdb-output.md#upserts-from-stream-analytics). Here only append/replace is possible. Accumulations must be managed client-side in Azure Cosmos DB.
 
 If the requirements match, an option is to replace the target SQL database by an Azure Cosmos DB instance. Doing so requires an important change in the overall solution architecture.
 
-For Synapse SQL, Azure Cosmos DB can be used as an intermediary layer via [Azure Synapse Link for Azure Cosmos DB](../cosmos-db/synapse-link.md). Synapse Link can be used to create an [analytical store](../cosmos-db/analytical-store-introduction.md). This data store can then be queried directly in Synapse SQL.
+For Synapse SQL, Azure Cosmos DB can be used as an intermediary layer via [Azure Synapse Link for Azure Cosmos DB](../cosmos-db/synapse-link.md). Azure Synapse Link can be used to create an [analytical store](../cosmos-db/analytical-store-introduction.md). This data store can then be queried directly in Synapse SQL.
 
 ### Comparison of the alternatives
 
@@ -422,7 +422,7 @@ Each approach offers different value proposition and capabilities:
 |Pre-Processing|||||
 ||Azure Functions|Replace, Accumulate|+|- (row-by-row performance)|
 ||Azure Cosmos DB replacement|Replace|N/A|N/A|
-||Azure Cosmos DB Synapse Link|Replace|N/A|+|
+||Azure Cosmos DB Azure Synapse Link|Replace|N/A|+|
 
 ## Get support