First, I create a MSSQL data source in ANZO, then import schemas into this.
Second, I ingest data source into ANZO, and auto generate models, mappings, pipeline.
But, when I click pipeline and want to publish jobs, I found it can not be published.
I know a button named 'publishAll', but it gone, I select a job want to publish but it doesn't work.
Please help me, Thanks a lot.
I want to publish these jobs
Related
I want to export my runtime duration of the each pipeline to CSV. How can this be done or achieved?
The below is scheduled Pipeline which run to end, i can use the the Export CSV button to get duration of these pipelines but each execute pipeline got so many individual jobs(In this example will take P_Weekly_RV_Load_1) and how can I get those details of all those individual jobs run in p_weekly_RV_Load_! to csv
Navigate to the Monitoring view in ADF, click on "Pipeline runs" and then "Debug". On the top right you'll see "Export to CSV".
When you say individual jobs I am assuming you mean the activity runs inside of a pipeline. Currently activity level detail is not exported to CSV, just the pipeline details.
To capture activity level detail there are a couple of options:
Use diagnostics settings and send the Activity Runs to storage, Log Analytics, or Event Hubs. See https://learn.microsoft.com/en-us/azure/data-factory/monitor-configure-diagnostics/ on how to set this up.
Use the SDKs via REST, Powershell, etc. to query the activity run endpoints and export the data programmatically. See https://learn.microsoft.com/en-us/rest/api/datafactory/activity-runs/query-by-pipeline-run as an example.
I am currently reviewing between 5-15 pull requests a week on a project being developed using Azure Data Factory (ADF) and Databricks.
Most pull requests contain changes to our ADF pipelines, which gets stored in source code as nested JSON.
What I've found is that, as a reviewer, being able to visually see the changes being made to an ADF pipeline in the pull request make a huge difference in the speed and accuracy at which I can perform my review. Obviously, I can check out the branch and go view the pipelines for that branch directly on ADF, but that does not give me a differential view.
My question is this: Is there a way to parse two ADF pipeline json objects (source and destination branch versions of the same file) and generate a visual representation of each object? Ideally highlighting the differences, but just showing them would be a good first stab.
Bonus points if we can fit this into a Azure DevOps release pipeline and generate it automatically as part of the CI/CD pipeline.
If you are already using Azure DevOps then you should have exactly what you are wanting available in every Pull Request. For any Pull Request you can click on the Files tab and it will show a side by side comparison of every file. It color codes it and includes additions, updates, and removals. It is very helpful for review. Please refer to this screenshot for details and illustration:
So to give you a bit of context we have a service which has been split into two different services ie one for the read and one for the write side operations. The read side is called ProductStore and the write side is called ProductCatalog. The issue were facing was down the write side as the load tests create 100 products in the write side resource web app and then they are transferred to the read side for the load test to then read x number of times. If a build is launched in the product catalog because something new was merged to master then this will cause issues in the product store pipeline if it gets run concurrently.
The question I want to ask is there a way in the ProductStore yaml file to directly query via a specified azure task or via an AzurePowershell script to check if a build is currently running in the ProductCatalog pipeline.
The second part of this would be to loop/wait until that pipeline has successfully finished before resuming the product store pipeline.
Hope this is clear as I'm not sure how to best ask this question as I'm very new to the DevOps pipelines flow but this would massively help if there was a good way of checking this sort of thing.
As a workaround , you can set Pipeline completion trigger in ProductStore pipeline.
To trigger a pipeline upon the completion of another, specify the triggering pipeline as a pipeline resource.
Or configure build completion triggers in the UI, choose Triggers from the settings menu, and navigate to the YAML pane.
I've created a new onetime pipeline in Azure Data Factory using Copy Data wizard.
The pipeline has 4 activities and it was run just fine - all 4 activities succeeded.
Now I'd like to rerun the pipeline. So I do:
Clone the pipeline.
Change name to [name]_rev2.
Remove start and end properties.
Deploy the cloned pipeline.
Now the status of the new cloned pipeline is Running.
But no activities are executed at all.
What's wrong?
Mmmmm. Where to start!
In short. You can't just clone the pipeline. If its a one time data factory that you've created it won't have a schedule attached and therefore won't have any time slices provisioned that now require execution.
If your unsure how time slices in ADF work a recommend some reading around this concept.
Next, I recommend opening up a Visual Studio 2015 solution and downloading the data factory that did run as a project. Check out the various JSON blocks for scheduling and interval availability in the datasets, activities and the time frame in the pipeline.
Here's a handy guide for scheduling and execution to understand how to control your pipelines.
https://learn.microsoft.com/en-us/azure/data-factory/data-factory-scheduling-and-execution
Once you've made all the required changes (not just the name) publish the project to a new ADF service.
Hope this helps
I have a data factory that I would like to publish, however I want to delay one of the pipelines from running as it uses a shared resource that isn't quite ready.
If possible I would like to allow the previous pipelines to run and then enable the downstream pipeline when the resource is ready for it.
How can I disable a pipeline so that I can re-enable it at a later time?
Edit your trigger and make sure Activated is checked NO. And of course don't forget to publish your changes!
Its not really possible in ADF directly. However, I think you have a couple of options to dealing with this.
Option 1.
Chain the datasets in the activities to enforce a fake dependency making the second activity wait. This is a bit clunky and requires the provisioning of fake datasets. But could work.
Option 2.
Manage it at a higher level with something like PowerShell.
For example:
Use the following cmdlet to check the status of the first activity and wait maybe in some sort of looping process.
Get-AzureRmDataFactoryActivityWindow
Next, use the following cmdlet to pause/unpause the downstream pipeline as required.
Suspend-AzureRmDataFactoryPipeline
Hope this helps.
You mentioned publishing, so if you are publishing trough Visual Studio, it is possible to disable a pipeline by setting its property "isPaused" to true in .json pipeline configuration file.
Property for making pipeline paused
You can disable pipeline by clicking Monitor & Manage in Data Factory you are using. Then click on the pipeline and in the upper left corner you have two options:
Pause: Will not terminate current running job, but will not start next
Terminate: Terminates all job instances (as well as not starting future ones)
GUI disabling pipeline
(TIP: Paused and Terminated pipeline have orange color, resumed have green color)
Use the powershell cmdlet to check the status of the activity
Get-AzureRmDataFactoryActivityWindow
Use the powershell cmdlet to pause/unpause a pipeline as required.
Suspend-AzureRmDataFactoryPipeline
Right click on the pipeline in the "Monitor and Manage" application and select "Pause Pipeline".
In case you're using ADF V2 and your pipeline is scheduled to run using a trigger, check which trigger your pipeline uses. Then go to the Manage tab and click on Author->Triggers. There you will get an option to stop the trigger. Publish the changes once you've stopped the trigger.