How can I get Azure Synapse Pipeline run ID using python SDK in a synapse notebook? I have a ML pipeline that do a batch prediction everyday. What I want to do is get the pipeline run ID to save inside a DataFrame that is created in one of the notebook that I run in synapse.
I'm running my pipeline using the following major activities:
notebook: I'm using a synapse notebook to read some parquet files from a blob preprocess using pandas and save again in another blob.
I saw that you can put a system variable in the file name with the pipeline run id. But I want to now if there is a way to get the current pipeline run id and my notebook is being executed using the azure python sdk
You can do it using the Toggle parameter cell option in Synapse notebook cell.
Use Toggle parameter cell option in synapse notebook cell and give any parameter name and assign any value to it. (Here I have given empty string).
In Notebook activity of pipeline, use Base parameters and give same name and same data type for it. In dynamic content of the parameter give #pipeline().RunId like below.
Execute this activity and Go to Monitor-> Pipeline runs -> your pipeline-> Notebook activity snapshot and you can see the output of the Notebook.
You can use this parameter in the Notebook as per your requirement.
Related
I have a python script, which check whether APP_HOME directory is set as the environment variable or not and picks up few files in this directory to proceed with the further execution.
If it is running on windows, I am setting the environment variable pointing to APP_HOME directory. If the python script is created as a workflow in databricks, the workflow is giving me an option to set the environment variables while choosing the cluster for the task.
But, If the python script runs as a Databricks python activity from Azure Data factory, I have not found an option to set the environment variable for the databricks cluster that will be created by ADF. Is there a way to set up the environment variable APP_HOME in ADF for databricks cluster when Databricks python activity is used?
I have created data factory and created pipeline in data factory. I added data bricks as linked services linked service.
fill the required fields in additional settings of cluster will find environment variable field.
Reference image:
Can we automatically load new files added in adls gen2 into spark pool notebook? I am hard coding the parquet file name in my spark scala notebook for loading the file. I want all the new files which are added to be automatically loaded into my notebook.
You can achieve your requirement using storage event triggers and parameterized notebooks. Parameterized notebooks are only regular notebooks with parameters passed from the pipeline.
A storage event trigger is used to start the execution of pipeline if a file is uploaded, copied or deleted from a specific storage account. This type of trigger starts executing the pipeline for each of the uploaded file(s).
Implement the following steps to achieve this:
Create a notebook and create a filename parameter and toggle the cell to parameter cell as shown in the image (mssparkutils.notebook.exit({filename}) is just for my reference). Write the rest of your code using this filename parameter whose value will be in the format <filename>.<extension>.
Now create a pipeline, using synapse Notebook activity. Create a parameter for pipeline called triggeringFile. Go to notebook activity and specify your notebook to which you want to load the file.
Create a new parameter for notebook activity called filename with value as #pipeline().parameters.triggeringFile referring to the value of the pipeline parameter triggeringFile which we will pass to this notebook.
Now create a trigger for this pipeline by clicking Trigger -> New/Edit. Choose to create a new trigger and specify fields as specified below (The value of blob path begins with is just the path to your ADLS gen2 folder, you can leave it empty if the files are uploaded directly to container and blob path ends with is '.parquet' as you are working with parquet).
When you click continue, you can see trigger parameter values triggeringFile. Specify its value as #trigger().outputs.body.fileName Which gives the filename of the file that triggered the pipeline.
Publish the pipeline and trigger. When you upload any number of files to this ADLS gen2 storage, each of those files will trigger the pipeline. I have uploaded a file named sample.csv and you can see that the pipeline execution succeeds, and when you monitor the pipeline you can see that filename parameter is successfully passed to the notebook where it can be processed further.
I am implementing one testing solution as:
I have created an Azure databricks notebook in Python. This notebook is performing following tasks (for testing)-
Read blob file from Storage account in a Pyspark dataframe.
Doing some transformation and analysis on it.
Creating CSV with transformed data and storing in a different container.
Move original read CSV to different archive container (so that it should not be picked up in next execution).
*Above steps can be done in different Notebooks also.
Now, I need this Notebook to be triggered for each new Blob in a container.
I will implement following orchestration-
New blob in Container -> event to EventGrid topic-> trigger Datafactory pipeline -> execute Databricks Notebook.
We can pass filename as parameter from ADF pipeline to Databricks notebook.
Looking for some other ways to do the orchestration flow.
If above seems correct and more suitable, please mark as answered.
New blob in Container -> event to EventGrid topic-> trigger
Datafactory pipeline -> execute Databricks Notebook.
We can pass filename as parameter from ADF pipeline to Databricks
notebook.
Looking for some other ways to do the orchestration flow. If above
seems correct and more suitable, please mark as answered.
You can use this method. Of course, you can also follow this path:
New blob in Container -> Use built-in event trigger to trigger Datafactory pipeline -> execute Databricks Notebook.
I don't think you need to introduce the event grid, because Data Factory comes with triggers for creating events based on blobs.
I got 2 support comments for what I am following for orchestration.
//
New blob in Container -> event to EventGrid topic-> trigger Datafactory pipeline -> execute Databricks Notebook.
//
I have a Azure data factory pipeline that is calling a Databricks notebook.
I have parameterized the pipeline and via this pipeline I am passing the product name to the databricks notebook.
Based on the parameter the Databricks will push the processed data into the specific ADLS directory.
Now the problem is- How do I make my pipeline aware that which parameter need to pass to the Databricks.
Example: If I pass the Nike via the adf to the databricks then my data would get pushed into Nike directory or If I pass Adidas then data would get pushed into Adidas directory.
Please note that I am triggering the ADF from the automation account.
As I understood, you are using product_name = dbutils.widgets.get('product_name') statement in the databricks notebook to get the param and based on that param you process the data. The question is how to pass different params to the notebook? You create one adf pipeline and you can pass different params to the triggers that execute the adf pipeline.
Create ADF pipeline
Adf pipeline
create trigger that will pass params to the ADF pipeline
triggers
This way you will have 1 ADF pipeline with multiple instances of it with different params like Adidas, Nike etc.
I want to do some steps in my PowerShell based on a value from an Azure ADF(Azure Data Factory) pipeline. How can I pass a value from an ADF pipeline to the PowerShell, where I invoked this ADF Pipeline? So that, I can do the appropriate steps in the PowerShell based on a value I received from ADF pipeline.
NOTE: I am not looking for the run-status of the pipeline (success, failure etc), but I am looking for some variable-value that we get inside a pipeline - say, a flag-value we obtained from a table using a Lookup activity etc.
Any thoughts?
KPK, the requirements you're talking about definitely can be fulfilled though I do not know where does your Powershell scripts run.
You could write your Powershell scripts in HTTP Trigger Azure Function,please refer to this doc. Then you could get the output of the pipeline in Powershell:
https://learn.microsoft.com/en-us/powershell/module/azurerm.datafactoryv2/invoke-azurermdatafactoryv2pipeline?view=azurermps-4.4.1#outputs.
Then pass the value you want to HTTP Trigger Azure Function as parameters.