Web activity failure due to Invoking endpoint failed with HttpStatusCode - 403 -- help?
Hi, I have an Azure Data Factory (ADF) instance that I am using to create a Pipeline to ingest external (cloud based) 3rd party data into my Azure SQL Server database. I am a novice with ADF and have only used it to ingest some external SQL data into my SQL database - it did work. The external source I'm attempting to extract from uses an OAuth 2.0 API and an API is something I've not used before. Using Postman (never used this software before this attempt), I have passed the external source's base_url, client_id, and client_secret, and in return successfully received an access token. This tells me that the base_url, client_id, and client_secret values I passed are correct and accepted by the target source/application. Feeling encourage to implement the same values into ADF, I first created a Linked Service which with a successful test connection returned - see below. This Linked Service uses the same values as the Postman entry which granted an access token. I then created a Pipeline with a Web activity object within it. The General and User Properties don't have any configuration, only the Settings tab does which shown below. Again, the URL, Client ID and Client Secret configured here are the same as those used in Postman (and the Linked Service). I execute the Web object and it returns with a failure - see below. The error states the endpoint refused the request (for an access token). Is this accurate as I was able to receive an access token via Postman when using the same credentials? I don't understand why via Postman I can received an access token but via ADF it errors. I'm wondering if I've completed the ADF parts incorrectly, or if there is more needed just to received an access token, or if it's something else? Are you able to advise what's taking place here? Thanks.
ADF connection issue with Cassandra
Hi, I am trying to connect a cassandra DB hosted in azure cosmos db. I created the linked service but getting below error on test connection. Already checked the cassandra DB and its public network access is set to all networks. Google suggested enabling SSL but there is no such option in linked service. Please help. Failed to connect to the connector. Error code: 'Unknown', message: 'Failed to connect to Cassandra server due to, ErrorCode: InternalError' Failed to connect to the connector. Error code: 'InternalError', message: 'Failed to connect to Cassandra server due to, ErrorCode: InternalError' Failed to connect to Cassandra server due to, ErrorCode: InternalError All hosts tried for query failed (tried 51.107.58.67:10350: SocketException 'A request to send or receive data was disallowed because the socket is not connected and (when sending on a datagram socket using a sendto call) no address was supplied')
How to Flatten Nested Time-Series JSON from API into Azure SQL using ADF Mapping Data Flow?
How to Flatten Nested Time-Series JSON from API into Azure SQL using ADF Mapping Data Flow? Hi Community, I'm trying to extract and load data from API returning the following JSON format into an Azure SQL table using Azure Data Factory. { "2023-07-30": [], "2023-07-31": [], "2023-08-01": [ { "breakdown": "email", "contacts": 2, "customers": 2 } ], "2023-08-02": [], "2023-08-03": [ { "breakdown": "direct", "contacts": 5, "customers": 1 }, { "breakdown": "referral", "contacts": 3, "customers": 0 } ], "2023-08-04": [], "2023-09-01": [ { "breakdown": "direct", "contacts": 76, "customers": 40 } ], "2023-09-02": [], "2023-09-03": [] } Goal: I want to flatten this nested structure and load it into Azure SQL like this: Expand table ReportDate Breakdown Contacts Customers 2023-07-30 (no row) (no row) (no row) 2023-07-31 (no row) (no row) (no row) 2023-08-01 email 2 2 2023-08-02 (no row) (no row) (no row) 2023-08-03 direct 5 1 2023-08-03 referral 3 0 2023-08-04 (no row) (no row) (no row) 2023-09-01 direct 76 40 2023-09-02 (no row) (no row) (no row) 2023-09-03 (no row) (no row) (no row)ADF dataflow data Preview Error
hi All, I have data flow as seen below. all linked service and data set working fine and i can see the data preview but wheb i use the same linked service and dateset in the dataflow It throw error as shown below i am useing managed private endpoint to coonect the blob starga it is owrking for all pipe line. the ADF and the MI has staorgae account contributor role assigned. Error: at Source 'sourcedata': This request is not authorized to perform this operation. When using Managed Identity(MI)/Service Principal(SP) authentication 1. For source: In Storage Explorer, grant the MI/SP at least Execute permission for ALL upstream folders and the file system, along with Read permission for the files to copy. Alternatively, in Access control (IAM), grant the MI/SP at least the Storage Blob Data Reader role. 2. For sink: In Storage Explorer, grant the MI/SP at least Execute permission for ALL upstream folders and the file system, along with Write permission for the sink folder. Alternatively, in Access control (IAM), grant the MI/SP at least the Storage Blob Data Contributor role. Also please ensure that the network firewall settings in the storage account are configured correctly as turning on firewall rules for your storage account blocks incoming requests for data by default, unless the requests originate from a service operating within an Azure Virtual Network (VNet) or from allowed public IP addresses. Any kind of help is highly appreciated
OData Connector for Dynamics Business Central
Hey Guys, I'm trying to connect Dynamics Business Central OData API in ADF but I'm not sure what I'm doing wrong here because the same Endpoint is returning data on Postman but returning an error in ADF LinkedService. https://api.businesscentral.dynamics.com/v2.0/{tenant-id}/Sandbox-UAT/ODataV4/Company('company-name')/Chart_of_AccountsWhat Synapse Serverless SQL pool authentication type for ADF Linked Service?
Hi, I'm relatively new to Azure Data Factory and require your guidance on how to successfully create/test a Linked Service to the Azure Synapse Analytics Serverless SQL pool. In the past, I've successfully created a Linked Service to a third-party (outside our domain) on-premises SQL Server through creating a self-hosted integration runtime on their box and then creating a Linked Service to use that. The Server Name, Database Name, Windows authentication, my username and password all configured by the third-party is what I entered into the Linked Service configuration boxes. All successfully tested. This third-party data was extracted and imported, via ADF Pipelines, into an Azure SQL Server database within our domain. Now I need to extract data from our own (hosted in our domain) Azure Synapse Analytics Serverless SQL pool database. My attempt is this, and it fails: 1) I create a 'Azure Synapse Analytics' Data Store Linked Service. 2) I select the 'AutoResolveIntegrationRuntime' as the runtime to use - I'm thinking this is correct as the Synapse source is within our domain (we're fully MS cloud based). 3) I select 'Enter manually' under the 'Account selection method'. 4) I've got the Azure Synapse Analytics Serverless SQL endpoint - which I place into the 'Fully qualified domain name' field. 5) I entered the data SQL Database name found under the 'SQL database' node/section present on the Data >> Workspace screen in Synapse. 6) I choose 'System-assigned managed identity' as the Authentication type - this is a guess and I was hoping it would recognised my username/account that I am building the Linked Service with, as that account also can query Synapse too and so has Synapse access. 7) I check the 'Trust server certification' box. All else is default. When I click test connection, it fails with the following message: "Cannot connect to SQL Database. Please contact SQL server team for further support. Server: 'xxxxxxxxxxxx-ondemand.sql.azuresynapse.net', Database: 'Synapse_Dynamics_data', User: ''. Check the linked service configuration is correct, and make sure the SQL Database firewall allows the integration runtime to access. Login failed for user '<token-identified principal>'." I've reached out to our I.T. (who are novices with Synapse, ADF, etc.. even though they did install them in our domain) and they don't know how to help me. I'm hoping you can help. 1) Is choosing the 'Azure Synapse Analytics' the correct Data Store to chose when looking extract data from an Azure Synapse Serverless SQL pool SQL database? 2) Is using the AutoResolveIntegrationRuntime correct if Synapse is held within our domain? I've previously confirmed this runtime works (and still does) as when importing the third-party data I had to use that runtime to load the data to our Azure SQL Server database. 3) Have I populated the correct values for the 'Fully qualified domain name' and 'Database name' fields by entering the Azure Synapse Analytics Serverless SQL endpoint and subsequent SQL Database name, respectively? 4) Is choosing 'System-assigned managed identity' as the Authentication type correct? I'm guessing this could be the issue. I selected this as when loading the mentioned third-party data into the Azure SQL Server database, within our domain, this was the authentication type that was used (and works) and so I'm assuming it somehow recognises the user logged in and, through the magic of cloud authentication, says this user has the correct privileges (as I should have the correct privileges so say I.T.) so allow the Linked Service to work. Any guidance you can provide me will be much appreciated. Thanks.
Failure of azure data factory integration runtime with Vnet enabled
I had been using Data Factory's integration runtime with VNet successfully, but it recently stopped connecting to Cosmos DB with the MongoDB API (which is also within a VNet). After setting up a new integration runtime with VNet enabled and selecting the region as 'Auto Resolve,' the pipeline ran successfully with this new runtime. Could you help me understand why the previous integration runtime—configured with VNet enabled and the region set to match that of Azure Data Factory—worked for over a month but then suddenly failed? The new integration runtime with VNet and 'Auto Resolve' region worked, but I'm uncertain if the 'Auto Resolve' region contributed to the success or if something else allowed it to connect. Error:Failure happened on 'Source' side. ErrorCode=MongoDbConnectionTimeout,'Type=Microsoft.DataTransfer.Common.Shared.HybridDeliveryException,Message=>Connection to MongoDB server is timeout.,Source=Microsoft.DataTransfer.Runtime.MongoDbAtlasConnector,''Type=System.TimeoutException,Message=A timeout occured after 30000ms selecting a server using CompositeServerSelector{ Selectors = MongoDB.Driver.MongoClient+AreSessionsSupportedServerSelector, LatencyLimitingServerSelector{ AllowedLatencyRange = 00:00:00.0150000 } }. Client view of cluster state is { ClusterId : "1", ConnectionMode : "ReplicaSet", Type : "ReplicaSet", State : "Disconnected", Servers : [{ ServerId: "{ ClusterId : 1, EndPoint : "Unspecified/cosmontiv01u.mongo.cosmos.azure.com:10255" }", EndPoint:'Cannot connect to SQL Database' error - please help
Hi, Our organisation is new to Azure Data Factory (ADF) and we're facing an intermittent error with our first Pipeline. Being intermittent adds that little bit more complexity to resolving the error. The Pipeline has two activities: 1) Script activity which deletes the contents of the target Azure SQL Server database table that is located within our Azure cloud instance. 2) Copy data activity which simply copies the entire contents from the external (outside of our domain) third-party source SQL View and loads it to our target Azure SQL Server database table. With the source being external to our domain, we have used a Self-Hosted Integration Runtime. The Pipeline executes once per 24 hours at 3am each morning. I have been informed that this timing shouldn't affect/or by affected by any other Azure processes we have. For the first nine days of Pipeline executions, the Pipeline successfully completed its executions. Then for the next nine days it only completed successfully four times. Now it seems to fail every other time. It's the same error message that is received on each failure - the received error message is below (I've replaced our sensitive internal names with Xs). Operation on target scr__Delete stg__XXXXXXXXXX contents failed: Failed to execute script. Exception: ''Type=Microsoft.DataTransfer.Common.Shared.HybridDeliveryException,Message=Cannot connect to SQL Database. Please contact SQL server team for further support. Server: 'XX-azure-sql-server.database.windows.net', Database: 'XX_XXXXXXXXXX_XXXXXXXXXX', User: ''. Check the linked service configuration is correct, and make sure the SQL Database firewall allows the integration runtime to access.,Source=Microsoft.DataTransfer.Connectors.MSSQL,''Type=Microsoft.Data.SqlClient.SqlException,Message=Server provided routing information, but timeout already expired.,Source=Framework Microsoft SqlClient Data Provider,'' To me, if this Pipeline was incorrectly configured then the Pipeline would never have successfully completed, not once. With it being intermittent, but becoming more frequent, suggests it's being caused by something other than its configuration, but I could be wrong - hence requesting help from you. Please can someone advise on what is causing the error and what I can do to verify/resolve the error? Thanks.Some questions on ADF and Azure SQL Server
Hi, My company is looking to implement a data integration method. The project has been assigned to me but I'm not a data engineer and so I would like your guidance on the recommendation. I have the need to ingest several (only twelve at present) 3rd-party data sources into our domain so the data can be reported on. These external data sources are simple RDMS (most likely all to be MS SQL Server) and the volume of data, due to the 3rd-party creating a View for me, is only going to be around 20 columns and 20,000 rows, per data source. It's all structured data. My intention is to use Azure Data Factory (ADF) as the integration tool. The reason for this is we are entirely MS cloud-based and I see the ADF as the most suitable (simple, robust, cheap) MS cloud-based integration tool available - although you may inform me otherwise. I need to decide on the storage to hold the external data. I've had very brief experience with Synapse Serverless Pool, as it was the recommended substitute for Data Export Services (DES) (we use Dynamics 365 as our transactional system), which I found limiting in the SQL commands compatibility. Many of the SQL Views I had wrote upon DES weren't compatible in Synapse - I guess due to Synapse being written in Spark. For this reason, I am reluctant to use Synapse as the data storage. It is for this same reason I am reluctant to use the ADF Storage Account as I believe it is too written in Spark. Please can you advise on the below questions: 1) Is the ADF Storage Account written in Spark and thus prone to the same incompatibility as Synapse Serverless Pool is? 2) What are the benefits to using the ADF Storage Account over Azure SQL Server, and visa versa? 3) I know this question configuration specific but I'll ask anyway. Which is cheaper based on our basic use-case - ADF Storage Account or Azure SQL Server? I have trouble understanding the online pricing calculators. 4) I understand to execute activities/pipelines between Azure storage sources (ADF Storage Account, Azure SQL Server, etc.. Azure products) a 'Azure integration runtime' is needed. I also understand to extract data from an On-Premise SQL Server database a 'Self-Hosted integration runtime' is required - is this correct, and where will this 'Self-Hosted integration runtime' need to be installed (on the box that is running On-Premise SQL Server?)? I think that's all my questions for now. Thanks for your help.
How to handle azure data factory lookup activity with more than 5000 records
Hello Experts, The DataFlow Activity successfully copies data from an Azure Blob Storage .csv file to Dataverse Table Storage. However, an error occurs when performing a Lookup on the Dataverse due to excessive data. This issue is in line with the documentation, which states that the Lookup activity has a limit of 5,000 rows and a maximum size of 4 MB. Also, there is a Workaround mentioned (Micrsofot Documentation): Design a two-level pipeline where the outer pipeline iterates over an inner pipeline, which retrieves data that doesn't exceed the maximum rows or size. How can I do this? Is there a way to define an offset (e.g. only read 1000 rows) Thanks, -Sri
