Job level email alert is possible in databricks. I would like to implement task level email alert in databricks ( running in GCP). Do we have any feature available in databricks to sent email in case of task failure immidiately instead of waiting for the entire job to complete.
e,g for the below job , can we set alert for failure in order)ingest before completing the entire job?
Related
I need to develop a event driven pipeline which should get trigger on file arrival in ADLS2 i.e. ABFS. On file arrival I need to trigger 4 subsequent Spark jobs on Azure Databricks cluster.
For orchestrating the Spark Jobs I can use Databricks jobs as an option so that jobs could get triggered in a pipeline.
But the first job should get triggered only after the file arrival.
I am currently exploring ways to achieve this but need expert advice to design this in a best possible manner w.r.t cost.
One solution could be to use Azure Data Factory for orchestrating the entire flow based on Storage Event Trigger component but going for ADF just because of event based trigger don't look feasible to me as the rest part of the application i.e. Spark jobs can be pipelined from Databricks Job feature. Also, in terms of cost ADF can be expensive. Another solution could be to use Azure Functions Blob Trigger to know the file arrival but I am not able to understand how can I trigger Azure Databricks jobs from Azure Functions. As going with Functions can be cost effective as the function would not be running/active until the file has arrived.
Note:There can be multiple files arriving in an hour. No fixed duration on file arrival.
Also, trigger file is different than data files. i.e. On arrival of trigger files, Spark pipeline would consume actual data files.
Data files and Trigger files have different extensions and both are arriving in ABFS.
Your worry about ADF cost is misplaced. The Pipelines are extremely cheap. The activities that actually move data and use CPU are where most of the cost is. For instance Data Flows are run on managed Spark clusters, which is reflected in the pricing. See Data Factory Pricing. Using a Pipeline to orchestrate Databricks jobs is a common, simple, and (at least for ADF) very inexpensive.
If you want to kick off a Databricks job from an Azure Function, there's an API. Also check out the Databricks Autoloader, but running your Databricks cluster continuously can be expensive.
I have pipeline need to run at every one hour.
Using tumbling window trigger.
If pipeline is successfull it should continue to run every one hour.
If pipeline fails with some reason, next instance, I mean pipline should not run for next hour.
How can we stop trigger if pipeline fails.
Currently, this feature is not available in the Azure data factory. You can raise a feature request from the Azure data factory feedback.
Alternatively, you can add a web activity in your pipeline upon the failure of the previous activity. In web activity, you can make a call to an HTTP request to Stop the trigger.
Refer to this document to Stop a trigger.
I have a published and scheduled pipeline running at regular intervals. Some times, the pipeline may fail (for example if the datastore is offline for maintenance). Is there a way to specify the scheduled pipeline to perform a certain action if the pipeline fails for any reason? Actions could be to send me an email, try to run again in a few hours later or invoke a webhook. As it is now, I have to manually check the status of our production pipeline at regular intervals, and this is sub-optimal for obvious reasons. I could of course instruct every script in my pipeline to perform certain actions if they fail for whatever reason, but it would be cleaner and easier to specify it globally for the pipeline schedule (or the pipeline itself).
Possible sub-optimal solutions could be:
Setting up an Azure Logic App to invoke the pipeline
Setting a cron job or Azure Scheduler
Setting up a second Azure Machine Learning pipeline on a schedule that triggers the pipeline, monitors the output and performs relevant actions if errors are encountered
All the solutions above suffers from being convoluted and not very clean - surely there must exist a simple, clean solution for this problem?
This solution reads from the logs of your pipeline and let's you do something within a Logic App capability, I used it to email the team when a scheduled pipeline failed.
Steps:
Create Event Namespace and Event Hub
Create Service Bus Namespace and Service Bus Queue
Create a Stream Analytics Job using EventHub as Input and Service
Bus Queue as Output
Create Logic App with a trigger to any event coming into the Service
Bus Queue then, add an Outlook 360 send an email (v2) step
Create an Event Subscription inside ML Service that sends filtered
events to the Event Hub
Start Stream Analytics Job
Two fundamental steps while creating the Event subscription:
Subscribe to the 'Run Status Changed' event to get the log when a pipeline fails
Use the advanced filters section to specify which pipeline you want to monitor (change 'deal-UAT' to your specific ml experiment), like this:
It looks like a lot of setup but it's super easy and quick to do, it would look something like this in the end:
I am trying to use Azure Batch Job Schedule in my application with .Net core. I want to get some notification/event trigger once the recurrence job is completed/failed in the job schedule so that I can copy output files to storage and send email to the end-user.
Is it possible to get such notification from azure Batch job schedule or is there any solution to this?
I can't find any sample implementation of Azure Batch job scheduling.
I hope this blog will sove your problem: https://mindmajix.com/azure-batch
Step by step example with code has been provided
Batch Tutorial
Here we will use dot net batch library and visual studio to create a sample batch task.
Step 1. Create containers in Azure Blob Storage.
Step 2. Upload task application files and input files to containers.
Step 3. Create a Batch pool.
3a. The pool StartTask downloads the task binary files (TaskApplication) to nodes as they join the pool.
Step 4. Create a Batch job.
Step 5. Add tasks to the job.
5a. The tasks are scheduled to execute on nodes.
5b. Each task downloads its input data from Azure Storage, then begins execution.
Step 6. Monitor tasks.
6a. As tasks are completed, they upload their output data to Azure Storage.
Step 7. Download task output from Storage.
Using Azure Backup the scheduled daily job fails every once in a while and a notification is sent:
Backup failure alert has been activated
Severity : Critical
Alert : Backup failure
Description : The operation attempted cannot be performed at this time because a backup or restore operation is currently running.
Recommended action(s) : Wait until the operation finishes or cancel the currently running operation, and then try again.
It seems two jobs are started at the same time. Why?
Also, where can I see the scheduled jobs to confirm that only one daily job is scheduled? For some reason I can't seem to find this information either in the Azure Portal nor the Microsoft Azure Backup client. Am I missing something?