Merging changes synced from https://github.com/MicrosoftDocs/azure-docs-pr (branch live)

Author: Banani-Rath

articles/azure-monitor/monitor-reference.md

@@ -38,7 +38,7 @@ Solutions are based on log queries and views customized for a particular applica
 |:---|:---|
 | [Agent health](insights/solution-agenthealth.md) | Analyze the health and configuration of Log Analytics agents. |
 | [Alert management](platform/alert-management-solution.md) | Analyze alerts collected from System Center Operations Manager, Nagios, or Zabbix. |
-| [Service Map](insights/service-map.md) | Automatically discovers application components on Windows and Linux systems and maps the communication between services. The same functionality is provided in   |
+| [Service Map](insights/service-map.md) | Automatically discovers application components on Windows and Linux systems and maps the communication between services. |
 
 
 

articles/data-factory/concepts-data-flow-performance.md

@@ -6,7 +6,7 @@ ms.topic: conceptual
 ms.author: makromer
 ms.service: data-factory
 ms.custom: seo-lt-2019
-ms.date: 12/19/2019
+ms.date: 01/24/2020
 ---
 
 # Mapping data flows performance and tuning guide
@@ -125,6 +125,12 @@ Setting throughput and batch properties on CosmosDB sinks only take effect durin
 * Throughput: Set a higher throughput setting here to allow documents to write faster to CosmosDB. Please keep in mind the higher RU costs based upon a high throughput setting.
 *	Write Throughput Budget: Use a value which is smaller than total RUs per minute. If you have a data flow with a high number of Spark partitions, setting a a budget throughput will allow more balance across those partitions.
 
+## Join performance
+
+Managing the performance of joins in your data flow is a very common operation that you will perform throughout the lifecycle of your data transformations. In ADF, data flows do not require data to be sorted prior to joins as these operations are performed as hash joins in Spark. However, you can benefit from improved performance with the "Broadcast" Join optimization. This will avoid shuffles by pushing down the contents of either side of your join relationship into the Spark node. This works well for smaller tables that are used for reference lookups. Larger tables that may not fit into the node's memory are not good candidates for broadcast optimization.
+
+Another Join optimization is to build your joins in such a way that it avoids Spark's tendency to implement cross joins. For example, when you include literal values in your join conditions, Spark may see that as a requirement to perform a full cartesian product first, then filter out the joined values. But if you ensure that you have column values on both sides of your join condition, you can avoid this Spark-induced cartesian product and improve the performance of your joins and data flows.
+
 ## Next steps
 
 See other Data Flow articles related to performance:

articles/data-factory/pricing-concepts.md

@@ -151,7 +151,7 @@ To accomplish the scenario, you need to create a pipeline with the following ite
 | Data Flow Assumptions: execution time = 10 min + 10 min TTL | 10 \* 16 cores of General Compute with TTL of 10 |
 | Monitor Pipeline Assumption: Only 1 run occurred | 2 Monitoring run records retried (1 for pipeline run, 1 for activity run) |
 
-**Total Scenario pricing: $0.3011**
+**Total Scenario pricing: $1.4631**
 
 - Data Factory Operations = **$0.0001**
   - Read/Write = 10\*00001 = $0.0001 [1 R/W = $0.50/50000 = 0.00001]

articles/industry/agriculture/overview-azure-farmbeats.md

@@ -29,7 +29,7 @@ With the preview of Azure FarmBeats you can:
 ## Datahub
 
 The Azure FarmBeats Datahub is an API layer, which enables aggregation, normalization, and contextualization of various agriculture datasets across providers. You can use Azure FarmBeats to get:
-- **Sensor data** from two sensor providers [Davis Instruments](https://www.davisinstruments.com/product/enviromonitor-gateway/), [Teralytic](https://teralytic.com/)
+- **Sensor data** from two sensor providers [Davis Instruments](https://www.davisinstruments.com/product/enviromonitor-gateway/), [Teralytic](https://teralytic.com/), [Pessl Instruments](https://metos.at/)
 - **Satellite imagery** from European Space Agency's [Sentinel-2](https://sentinel.esa.int/web/sentinel/home) satellite mission
 - **Drone imagery** from three drone imagery providers [senseFly](https://www.sensefly.com/) , [SlantRange](https://slantrange.com/) , [DJI](https://dji.com/)
 

articles/iot-hub/iot-hub-devguide-query-language.md

@@ -228,7 +228,7 @@ The query object exposes multiple **Next** values, depending on the deserializat
 ### Limitations
 
 > [!IMPORTANT]
-> Query results can have a few minutes of delay with respect to the latest values in device twins. If querying individual device twins by ID, use the retrieve device twin API. This API always contains the latest values and has higher throttling limits.
+> Query results can have a few minutes of delay with respect to the latest values in device twins. If querying individual device twins by ID, use the [get twin REST API](https://docs.microsoft.com/rest/api/iothub/service/gettwin). This API always returns the latest values and has higher throttling limits. You can issue the REST API directly or use the equivalent functionality in one of the [Azure IoT Hub Service SDKs](iot-hub-devguide-sdks.md#azure-iot-hub-service-sdks).
 
 Currently, comparisons are supported only between primitive types (no objects), for instance `... WHERE properties.desired.config = properties.reported.config` is supported only if those properties have primitive values.
 

articles/logic-apps/logic-apps-track-b2b-messages-omsportal.md

@@ -3,9 +3,7 @@ title: Track B2B messages with Azure Monitor logs
 description: Track B2B communication for integration accounts and Azure Logic Apps with Azure Log Analytics
 services: logic-apps
 ms.suite: integration
-author: divyaswarnkar
-ms.author: divswa
-ms.reviewer: jonfan, estfan, logicappspm
+ms.reviewer: jonfan, divswa, logicappspm
 ms.topic: article
 ms.date: 10/19/2018
 ---
@@ -142,8 +140,8 @@ select those messages, and choose **Download**. When you're prompted,
 save the .zip file to your local computer, and then extract that file. 
 
    The extracted folder includes a folder for each selected message. 
-   If you set up acknowledgements, 
-   the message folder also includes files with acknowledgement details. 
+   If you set up acknowledgments, 
+   the message folder also includes files with acknowledgment details. 
    Each message folder has at least these files: 
 
    * Human-readable files with the input payload and output payload details
@@ -207,7 +205,7 @@ Here are the name formats for each downloaded AS2 message folder and files.
 | Folder or file | Name format |
 | :------------- | :---------- |
 | Message folder | [sender]\_[receiver]\_AS2\_[correlation-ID]\_[message-ID]\_[timestamp] |
-| Input, output, and if set up, acknowledgement files | **Input payload**: [sender]\_[receiver]\_AS2\_[correlation-ID]\_input_payload.txt </p>**Output payload**: [sender]\_[receiver]\_AS2\_[correlation-ID]\_output\_payload.txt </p></p>**Inputs**: [sender]\_[receiver]\_AS2\_[correlation-ID]\_inputs.txt </p></p>**Outputs**: [sender]\_[receiver]\_AS2\_[correlation-ID]\_outputs.txt |
+| Input, output, and if set up, acknowledgment files | **Input payload**: [sender]\_[receiver]\_AS2\_[correlation-ID]\_input_payload.txt </p>**Output payload**: [sender]\_[receiver]\_AS2\_[correlation-ID]\_output\_payload.txt </p></p>**Inputs**: [sender]\_[receiver]\_AS2\_[correlation-ID]\_inputs.txt </p></p>**Outputs**: [sender]\_[receiver]\_AS2\_[correlation-ID]\_outputs.txt |
 |          |             |
 
 <a name="x12-message-properties"></a>
@@ -240,7 +238,7 @@ Here are the name formats for each downloaded X12 message folder and files.
 | Folder or file | Name format |
 | :------------- | :---------- |
 | Message folder | [sender]\_[receiver]\_X12\_[interchange-control-number]\_[global-control-number]\_[transaction-set-control-number]\_[timestamp] |
-| Input, output, and if set up, acknowledgement files | **Input payload**: [sender]\_[receiver]\_X12\_[interchange-control-number]\_input_payload.txt </p>**Output payload**: [sender]\_[receiver]\_X12\_[interchange-control-number]\_output\_payload.txt </p></p>**Inputs**: [sender]\_[receiver]\_X12\_[interchange-control-number]\_inputs.txt </p></p>**Outputs**: [sender]\_[receiver]\_X12\_[interchange-control-number]\_outputs.txt |
+| Input, output, and if set up, acknowledgment files | **Input payload**: [sender]\_[receiver]\_X12\_[interchange-control-number]\_input_payload.txt </p>**Output payload**: [sender]\_[receiver]\_X12\_[interchange-control-number]\_output\_payload.txt </p></p>**Inputs**: [sender]\_[receiver]\_X12\_[interchange-control-number]\_inputs.txt </p></p>**Outputs**: [sender]\_[receiver]\_X12\_[interchange-control-number]\_outputs.txt |
 |          |             |
 
 <a name="EDIFACT-message-properties"></a>
@@ -273,7 +271,7 @@ Here are the name formats for each downloaded EDIFACT message folder and files.
 | Folder or file | Name format |
 | :------------- | :---------- |
 | Message folder | [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_[global-control-number]\_[transaction-set-control-number]\_[timestamp] |
-| Input, output, and if set up, acknowledgement files | **Input payload**: [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_input_payload.txt </p>**Output payload**: [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_output\_payload.txt </p></p>**Inputs**: [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_inputs.txt </p></p>**Outputs**: [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_outputs.txt |
+| Input, output, and if set up, acknowledgment files | **Input payload**: [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_input_payload.txt </p>**Output payload**: [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_output\_payload.txt </p></p>**Inputs**: [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_inputs.txt </p></p>**Outputs**: [sender]\_[receiver]\_EDIFACT\_[interchange-control-number]\_outputs.txt |
 |          |             |
 
 ## Next steps

articles/storage/files/storage-sync-files-troubleshoot.md

@@ -1105,7 +1105,7 @@ If files fail to be recalled:
 | 0x80c86002 | -2134351870 | ECS_E_AZURE_RESOURCE_NOT_FOUND | The file failed to recall because it's not accessible in the Azure file share. | To resolve this issue, verify the file exists in the Azure file share. If the file exists in the Azure file share, upgrade to the latest Azure File Sync [agent version](https://docs.microsoft.com/azure/storage/files/storage-files-release-notes#supported-versions). |
 | 0x80c8305f | -2134364065 | ECS_E_EXTERNAL_STORAGE_ACCOUNT_AUTHORIZATION_FAILED | The file failed to recall due to authorization failure to the storage account. | To resolve this issue, verify [Azure File Sync has access to the storage account](https://docs.microsoft.com/azure/storage/files/storage-sync-files-troubleshoot?tabs=portal1%2Cazure-portal#troubleshoot-rbac). |
 | 0x80c86030 | -2134351824 | ECS_E_AZURE_FILE_SHARE_NOT_FOUND | The file failed to recall because the Azure file share is not accessible. | Verify the file share exists and is accessible. If the file share was deleted and recreated, perform the steps documented in the [Sync failed because the Azure file share was deleted and recreated](https://docs.microsoft.com/azure/storage/files/storage-sync-files-troubleshoot?tabs=portal1%2Cazure-portal#-2134375810) section to delete and recreate the sync group. |
-| 0x800705aa | -2147023446 | ERROR_NO_SYSTEM_RESOURCES | The file failed to recall due to insuffcient system resources. | If the error persists, investigate which application or kernel-mode driver is exhausting system resources. |
+| 0x800705aa | -2147023446 | ERROR_NO_SYSTEM_RESOURCES | The file failed to recall due to insufficient system resources. | If the error persists, investigate which application or kernel-mode driver is exhausting system resources. |
 | 0x8007000e | -2147024882 | ERROR_OUTOFMEMORY | The file failed to recall due to insuffcient memory. | If the error persists, investigate which application or kernel-mode driver is causing the low memory condition. |
 | 0x80070070 | -2147024784 | ERROR_DISK_FULL | The file failed to recall due to insufficient disk space. | To resolve this issue, free up space on the volume by moving files to a different volume, increase the size of the volume, or force files to tier by using the Invoke-StorageSyncCloudTiering cmdlet. |
 

articles/virtual-desktop/manage-resources-using-ui-powershell.md

@@ -159,4 +159,4 @@ If you come across any issues with the management tool or other Windows Virtual
 
 ## Next steps
 
-Now that you've learned how to deploy and connect to the management tool, you can learn how to use Azure Service help to monitor service issues and health advisories. To learn more, see our [Set up service alerts tutorial](./set-up-service-alerts.md).
+Now that you've learned how to deploy and connect to the management tool, you can learn how to use Azure Service Health to monitor service issues and health advisories. To learn more, see our [Set up service alerts tutorial](./set-up-service-alerts.md).