Trigger batches are a critical component when working with data in Microsoft Azure, particularly when preparing for the DP-203 Data Engineering exam. Trigger batches provide a mechanism for launching actions based on certain conditions or events, allowing for automation and streamlined processes.
In the context of Azure, triggers are used in Azure Data Factory to create data-driven workflows. These workflows are orchestrated and executed in a streamlined manner. The execution of these workflows can be planned according to event-based programming or timer-based scheduling.
Event-based Trigger Batches
Event-based triggers are created when you need an event to trigger the batch job. Examples of these events include the arrival of new data in the data source or the modification of existing data. Event-based triggers are highly useful for real-time data applications where instantaneous processing is required.
Here’s an example of how an event trigger is set up in Azure:
from azure.mgmt.datafactory.models import EventTrigger, BlobEventsTrigger
blob_events_trigger = BlobEventsTrigger(events=['Microsoft.Storage.BlobCreated'])
event_trigger = EventTrigger(
name="EventTriggerName",
type_properties=blob_events_trigger,
pipeline='pipeline_name',
blob_path_begins_with="container_name/",
scope="",
)
client.triggers.create_or_update("my_resource_group", "data_factory_name", "trigger_name", event_trigger)
In the code snippet above, an Event Trigger is created for a blob storage event where a new blob is created. When the stated event occurs, it triggers the defined data pipeline.
Schedule-based Trigger Batches
Unlike event-based triggers, schedule-based triggers initiate an action at a specific time or interval. This type of trigger is ideal for operations that need to be performed regularly, such as daily data ingestion or weekly reports.
The following snippet illustrates how a schedule-based trigger might look:
from azure.mgmt.datafactory.models import ScheduleTrigger, ScheduleTriggerRecurrence
recurrence = ScheduleTriggerRecurrence(frequency='Minute', interval=15)
schedule_trigger = ScheduleTrigger(recurrence=recurrence)
client.triggers.create_or_update("my_resource_group", "data_factory_name", "trigger_name", schedule_trigger)
In this code example, a schedule trigger executes every fifteen minutes, instigating whatever workload is attached to it regularly.
Comparison of Event-based and Schedule-based Triggers
| Event-based Triggers | Schedule-based Triggers | |
|---|---|---|
| Triggering Condition | Event occurs (e.g Data arrives or changes) | Specific time or regular interval |
| Applications | Real-time data applications, alert systems | Regular data ingestion, periodic reporting |
| Example Use case | A retail company wants to update their inventory as soon as a purchase is made | A company wants to run weekly reports for their monthly meetings |
Understanding trigger batches is essential when working with Azure data factories. Practicing creating and manipulating event and schedule-based triggers will strengthen your skills for the DP-203 Data Engineering exam and provide robust solutions in your real-world data scenarios.
Practice Test
True or False: Trigger batches in Azure Data Factory enables data transfer from one place to another.
- True
- False
Answer: True
Explanation: Trigger batches are a part of Azure Data Factory which helps in orchestrating and automating the data movement and transformation.
A batched trigger in Azure Data Factory will not be operational until it has a published pipeline with a new trigger. Is this correct?
- True
- False
Answer: True
Explanation: A batch trigger in Azure Data Factory comes into operation only once its associated pipeline has been published successfully.
Can a trigger batch have more than one pipeline?
- True
- False
Answer: True
Explanation: Azure allows us to attach one or more pipelines to a trigger. This allows running multiple pipelines every time the trigger is fired.
Which type of trigger in Azure Data Factory can be used to process files in a batch whenever new files arrive at the source location?
- a) Schedule trigger
- b) Tumbling window trigger
- c) Batch trigger
- d) Event-based trigger
Answer: d) Event-based trigger
Explanation: Event-based triggers in Azure Data Factory can be used to initiate data processing when new data arrives.
True or False: It is possible to manually run the trigger batches in Azure.
- True
- False
Answer: True
Explanation: We can manually invoke the trigger batches in Azure. It ensures the flexibility of running the batch operations as and when required.
Can a trigger batch in Azure be paused and resumed?
- True
- False
Answer: True
Explanation: Azure gives the provision to pause and resume the trigger batches as per the need.
True or False: Triggers in Azure can only be event-based.
- True
- False
Answer: False
Explanation: Azure Data Factory provides various kinds of triggers including event-based, schedule, and tumbling window triggers.
What are the steps to create a trigger batch in Azure data factory?
- a) Creating a pipeline, creating a trigger, linking the pipeline and the trigger
- b) Creating a dataflow, creating a trigger
- c) Creating a pipeline, creating a trigger
- d) Creating a trigger, linking the pipeline and the trigger
Answer: a) Creating a pipeline, creating a trigger, linking the pipeline and the trigger
Explanation: The complete process involves making a pipeline, creating a trigger, and then linking them.
Which of these is not a type of trigger in Azure Data Factory?
- a) Batch trigger
- b) Continuous trigger
- c) Tumbling window trigger
- d) Schedule trigger
Answer: b) Continuous trigger
Explanation: There is no continuous trigger type in Azure Data Factory. The available types are batch, event, schedule, and tumbling window trigger.
Trigger batches in Azure are a part of which service?
- a) Azure Data Lake
- b) Azure Databricks
- c) Azure Data Factory
- d) Azure Storage Account
Answer: c) Azure Data Factory
Explanation: Trigger batches are a part of Azure Data Factory’s offering, it’s not specifically related to Azure Data Lake, Databricks, or Storage Account.
Interview Questions
What is the primary aim of trigger batches in Azure Data Factory?
The primary aim of trigger batches in Azure Data Factory is to specify multiple pipelines to activate them together at a particular schedule.
Which automation task can be performed using trigger batches in Azure?
Trigger batches in Azure allows for combined scheduling and centralized management of multiple pipelines running at the same time.
What is the maximum number of pipelines you can include in a single batch?
You can include up to 100 pipelines in a single batch.
How can a batch of pipelines be activated?
A batch of pipelines can be activated by trigger run through a REST API, PowerShell or Azure portal.
How do trigger batches help in managing data in Azure?
Trigger batches in Azure can be utilized to schedule and manage execution of multiple pipelines at the same time, making data management more efficient and reliable.
What are the ways of managing trigger batches?
Trigger batches can be managed using the Azure portal, PowerShell, Python, REST API or .NET.
Can we implement trigger batches in a pipeline?
Yes, you can implement trigger batches in a pipeline using the Trigger Now option in the Azure portal.
What command is used to create a trigger in Azure?
The command ‘New-AzDataFactoryV2Trigger’ is used to create a trigger in Azure.
Can trigger batches be paused in Azure Data Factory?
Yes, trigger batches can be paused and resumed later in Azure Data Factory.
What is the common use case of trigger batches in Azure Data Factory?
The common use case of trigger batches is to simultaneously start and manage multiple data pipelines which share a common schedule.
How can we configure trigger batches in ADF?
Trigger batches in ADF can be configured by creating a tumbling window trigger and attaching it to the pipeline.
How can triggers be removed from a pipeline?
Triggers can be removed from a pipeline using the ‘Remove-AzDataFactoryV2Trigger’ command.
How is the order of pipeline execution defined in a trigger batch?
The order of pipeline execution in a trigger batch is not guaranteed. However, the sequence can be controlled programmatically if necessary.
Can event-based triggers be created in Azure?
Yes, event-based triggers can be created in Azure to respond to blob events such as creation or deletion of a blob.
How is a trigger linked to a pipeline?
A trigger is linked to a pipeline by defining the pipeline name and parameters within the trigger definition.
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