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1. #Azure data factory foreach file in folder verification#
2. #Azure data factory foreach file in folder code#
3. #Azure data factory foreach file in folder download#

Error message from storage execution: Requested value ‘AppendBlob’ was not found. When running the Azure Data Factory copy activity against an Append Blob you will see the following error:Ĭopy activity met storage operation failure at ‘Source’ side.

#Azure data factory foreach file in folder verification#

After a lot of verification and testing, it turns out Append Blobs are not supported in Azure Data Factory. This was where I began to run into issues. Once I had some sample Append Blobs in my container my next step was to setup the Azure Data Factory copy activity to get that data transferred to the on premise sql server staging tables. Since the Azure Blob Storage api has the ability to store Append Blobs, I was able to follow a similar pattern as I followed using the Azure Data Lake Store and append the Salesforce data to a blob as I fetched the data. If you have seen some of my other posts I have used Azure Data Lake Store to land my data, with this pipeline I decided to use Azure Blob Storage.

In order to accomplish this task, I decided to use Azure Data Factory, with the on premise gateway to connect to the local sql database. Once the data is copied locally another job within the financial system will process the staged data.

#Azure data factory foreach file in folder download#

The integration workflow is to first download the newest entries of a specific object from salesforce, then to push that into an on premise sql server staging table. The first job I began to tackle was an integration job between Salesforce and a local financial system. I was recently tasked with migrating local integration jobs into the cloud. Continue reading “Running an Azure Data Factory Pipeline on a Weekday Schedule Using an Azure Function” However, I thought it would be more fun to utilize Azure Functions to kick off a pipeline on a weekday schedule to provide a fully cloud based solution.

#Azure data factory foreach file in folder code#

You may not have that requirement specifically, but let’s say you want to only run a pipeline during the weekday or another specific schedule, this can be accomplished by utilizing the same code from my prior post and scheduling a local console app. Net, I outline the need to kick off a pipeline after a local job has completed and how this can be attained by utilizing the SDK to programmatically set the pipelines Start/End dates. In my post Starting an Azure Data Factory Pipeline from C#. With that being said there are certainly ways to adapt and get more control of an Azure Data Factory pipeline execution. One major drawback I have found with Azure Data Factory is the scheduling system, it’s not as flexible as I and many others would like it to be. I use it as the main workhorse of my data integration and ETL projects. I have written a few posts about different aspects of Azure Data Factory.