Azure Data Factory is a hybrid data integration service that allows you to create, schedule and manage data pipelines.
To schedule a pipeline in Azure Data Factory, follow the below steps:
- Browse to the Azure Data Factory interface and go to Author & Monitor.
- In the Author menu, under Factory Resources, select Pipelines, and then pick the pipeline you want to schedule.
- In the pipeline details, go to the Trigger option and click New/Edit.
- In the New Trigger panel, specify the trigger name, start time, end time, timezone, and frequency of the pipeline.
- Click Next and review the settings before finally clicking the Finish button.
Here is an example to set a trigger for your pipeline:
{
“name”: “Trigger1”,
“properties”: {
“runtimeState”: “Started”,
“pipelines”: [
{
“pipelineReference”: {
“referenceName”: “Pipeline1”,
“type”: “PipelineReference”
}
}
],
“type”: “ScheduleTrigger”,
“typeProperties”: {
“recurrence”: {
“frequency”: “Minute”,
“interval”: 15
}
}
}
}
In this example, a trigger named ‘Trigger1’ is created which will start a pipeline named ‘Pipeline1’ every 15 minutes.
II. Azure Synapse Pipelines:
Azure Synapse Analytics is an analytics service that brings together big data and data warehousing into a unified, integrated service that offers limitless analytics. It uses pipelines for data orchestration.
Scheduling a pipeline in Azure Synapse Analytics involves similar steps to Azure Data Factory
- Browse to the Synapse Studio and under the Develop menu, select Pipelines.
- Click on the specific pipeline which you want to schedule.
- Go to the Add Trigger option and choose New.
- Specify the trigger name, start and end time, timezone, and intervals of the pipeline under trigging conditions.
- Click on Next, review your settings, and then finally click Apply.
Here’s an example to set a trigger for your pipeline in Azure Synapse Analytics:
{
“name”: “Trigger1”,
“properties”: {
“type”: “ScheduleTrigger”,
“typeProperties”: {
“recurrence”: {
“frequency”: “Hour”,
“interval”: 2
}
},
“pipelines”: [
{
“parameters”: {},
“pipelineReference”: {
“type”: “PipelineReference”,
“referenceName”: “Pipeline1”
}
}
]
}
}
In this example, ‘Trigger1’ triggers ‘Pipeline1’ every 2 hours.
To sum up, both Azure Data Factory and Azure Synapse Pipelines provide seamless options to schedule your data pipelines. The choice between the two depends heavily on your specific use cases and requirements. Exam DP-203 Data Engineering on Microsoft Azure tests these concepts extensively, and a proper understanding of scheduling data pipelines is essential for it.
Remember, practice is key to mastering these skills and concepts. Make sure to spend a fair amount of time understanding how to create, schedule, and manage data pipelines on Azure Data Factory and Azure Synapse Pipelines. Good luck with your exam preparation!
Practice Test
True or False: Azure Data Factory is a cloud-based data integration service that allows you to create, schedule, and manage data pipelines.
Answer: True
Explanation: Azure Data Factory is a Microsoft cloud service that allows you to create data-driven workflows for orchestrating and automating data movement and data transformation.
Can you trigger the execution of an Azure Data Factory pipeline manually?
Answer: Yes
Explanation: Apart from scheduling, pipelines can also be manually executed through the ‘Trigger Now’ functionality in Azure Data Factory.
Which service is used to schedule data pipelines in Microsoft Azure?
- a) Azure Data Lake
- b) Azure Data Factory
- c) Azure SQL Data Warehouse
- d) Azure Data Box
Answer: b) Azure Data Factory
Explanation: Azure Data Factory is a cloud-based data integration service that orchestrates and automates the movement and transformation of data, making it the correct service for scheduling data pipelines.
True or False: Azure Synapse Pipelines is a separate service from Azure Synapse Analytics.
Answer: False
Explanation: Azure Synapse Pipelines is a part of Azure Synapse Analytics, it’s not a separate service. It allows you to create, schedule and manage data integration workflows in your Azure Synapse Analytics workspace.
Multiple selection: Which trigger types can be used in Azure Data Factory and Azure Synapse Pipelines?
- a) Tumbling window trigger
- b) Waterfall trigger
- c) Event-based trigger
- d) Scheduled trigger
Answer: a) Tumbling window trigger, c) Event-based trigger, d) Scheduled trigger
Explanation: Tumbling window triggers, event-based triggers, and scheduled triggers are supported in both Azure Data Factory and Azure Synapse Pipelines. Waterfall trigger isn’t a valid trigger type.
True or False: Data pipelines in Azure Data Factory can be set to execute at regular intervals.
Answer: True
Explanation: Azure Data Factory provides a scheduling system to run data pipelines at regular intervals, such as hourly, daily, or weekly.
In Azure Data Factory, is it possible to have a pipeline be triggered by an event in Blob Storage?
Answer: Yes
Explanation: An event-based trigger in Azure Data Factory will run a pipeline in response to an event such as the creation or deletion of a blob in Azure Blob Storage.
What does the scheduling of data pipelines in Azure Data Factory help with?
- a) Automation of data flow
- b) Security of data
- c) Visualizing data
- d) Data backup
Answer: a) Automation of data flow
Explanation: Scheduling data pipelines in Azure Data Factory helps in automating the flow of data between different services.
True or False: Azure Synapse Pipelines does not support executing stored procedures in Azure SQL Database or Azure Synapse Analytics.
Answer: False
Explanation: Azure Synapse Pipelines supports executing stored procedures in Azure SQL Database or Azure Synapse Analytics as a part of its data flow processing capabilities.
In Azure Synapse Pipelines, what is the minimum frequency for scheduling a pipeline?
- a) Every minute
- b) Every hour
- c) Every day
- d) Every week
Answer: a) Every minute
Explanation: Azure Synapse Pipelines can schedule a pipeline to run as frequently as every minute.
Interview Questions
What is the main role of Azure Data Factory?
Azure Data Factory is a cloud-based data integration service that orchestrates and automates the movement and transformation of data from various sources.
How can you schedule data pipelines in Azure Data Factory?
Data pipelines in Azure Data Factory can be scheduled by creating a trigger. The trigger can be scheduled to run at a specific time, in response to an event, or even continuously.
What is Azure Synapse Pipelines?
Azure Synapse Pipelines is a cloud-based service that helps in the creation, scheduling, and management of data pipelines for ETL, ELT and data integration at scale.
What tools are provided by Azure Data Factory for visually managing data workflows?
Azure Data Factory provides tools like Copy Activity in ADF and Mapping Data Flow for visually building, debugging, and managing data transformation processes.
In Azure Synapse Pipelines, what is meant by pipeline orchestration?
Pipeline orchestration in Azure Synapse Pipelines refers to the process of coordinating the execution of multiple pipeline activities, including specifying dependencies and providing error handling capabilities.
Can Azure Data Factory transform data?
Yes, Azure Data Factory can perform light transformations using the Mapping Data Flow tool, and can also invoke compute services for heavier transformations.
What is the primary purpose of triggers in Data Factory or Azure Synapse Pipelines?
Triggers in Data Factory or Azure Synapse Pipelines are primarily used to control when a data pipeline execution should occur.
What are some types of data stores supported by Azure Data Factory?
Azure Data Factory supports a wide range of data stores such as Azure Blob storage, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL Database, and more.
How can you create a pipeline in Azure Data Factory?
A pipeline can be created in Azure Data Factory using the ADF user interface in the Azure portal, or by using the SDK for .Net, Python, etc.
What are the types of activities supported by Azure Data Factory?
Azure Data Factory supports a variety of activities, such as data movement activities, data transformation activities, and control activities.
Is it possible to monitor the activities in Azure Synapse Pipelines?
Yes, all the activities in Azure Synapse Pipelines can be monitored using the Monitoring and Management App.
What is the benefit of using Azure Data Factory for data integration?
Azure Data Factory simplifies the process of data integration, allowing users to create, schedule, and manage data pipelines without needing to write complex code.
How can we ensure pipeline execution in the case of errors in Azure Data Factory?
We can ensure pipeline execution even in the case of errors by configuring retry policies and using control activities for error-handling.
What transformation capabilities does Azure Synapse Pipelines offer?
Azure Synapse Pipelines offers a range of transformation capabilities, including data cleaning, aggregation, and joining of data from different sources.
How does Azure Data Factory support security and compliance?
Azure Data Factory supports security and compliance through built-in features like data encryption, firewall rules, virtual network service endpoints, authentication, and audit logging.
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