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Replay Archived Stream Data related to Exam: Data Engineering on Microsoft Azure

Replaying archived stream data is a crucial aspect of data engineering on Microsoft Azure. It allows data engineers to analyze and process historical data that has been captured and stored in Azure services. This article will provide an overview of how to replay archived stream data using Azure services.

Prerequisites

Before you begin replaying archived stream data, ensure you have the following prerequisites:

  • An Azure account
  • Data engineering expertise

1. Store Stream Data in Azure Storage

The first step is to store the stream data in Azure Storage. Azure Blob storage is commonly used for this purpose. You can use Azure Event Hubs as an ingestion service to capture the stream data and then store it in Azure Blob storage.

python
# Python code to store stream data in Azure Blob Storage
from azure.eventhub import EventHubClient, EventData
from azure.storage.blob import BlobServiceClient, BlobClient, ContainerClient
import json

# Replace , with your own values
blob_connection_string = “
blob_container_name = “

# Replace and with your own values
event_hub_connection_string = “
event_hub_name = “

blob_service_client = BlobServiceClient.from_connection_string(blob_connection_string)
container_client = blob_service_client.get_container_client(blob_container_name)

event_hub_client = EventHubClient.from_connection_string(event_hub_connection_string, event_hub_name)

consumer_group = “$Default”

# Receive events from the Event Hub and store them in Azure Blob Storage
receiver = event_hub_client.create_consumer(consumer_group, partition_id=”@latest”, starting_position=”-1″)
with receiver:
for event_data in receiver.receive():
blob_name = f”stream_data_{event_data.sequence_number}.json”
blob_client = container_client.get_blob_client(blob_name)

json_data = json.loads(event_data.body_as_str())
blob_client.upload_blob(json.dumps(json_data))

The above Python code demonstrates storing stream data in Azure Blob Storage by capturing it using Azure Event Hubs and then uploading it to Azure Blob storage for archiving. Make sure to replace the placeholders with your own values for connection strings, container name, and event hub details.

2. Configure Stream Analytics Job

To replay archived stream data, you need to configure a Stream Analytics job in Azure. Stream Analytics allows you to perform real-time analytics on the archived data.

json
{
“properties”: {
“name”: ““,
“eventsOutOfOrderPolicy”: “adjust”,
“outputErrorPolicy”: “stop”,
“inputs”: [
{
“name”: ““,
“type”: “stream”,
“datasource”: {
“type”: “Microsoft.Storage/Blob”,
“properties”: {
“container”: ““,
“pathPattern”: “stream_data*.json”,
“dateFormat”: “yyyy/MM/dd”,
“timeFormat”: “HH:mm:ss”
}
}
}
],
“outputs”: [
{
“name”: ““,
“type”: “blob”,
“datasink”: {
“type”: “Microsoft.Storage/Blob”,
“properties”: {
“container”: “
}
}
}
],
“transformation”: {
“query”: “SELECT * INTO FROM
},
“identity”: {
“type”: “SystemAssigned”
},
“sku”: {
“name”: “standard”
},
“eventsLateArrivalMaxDelayInSeconds”: 3600
},
“location”: ““,
“tags”: {},
“tags”: {},
“type”: “Microsoft.StreamAnalytics/StreamAnalytics”,
“apiVersion”: “2019-06-01”
}

The above JSON code represents the configuration of a Stream Analytics job. Make sure to replace the placeholders with your own values for job name, input alias, blob container name, output alias, output blob container name, region name, and other necessary details.

3. Start the Stream Analytics Job

After configuring the Stream Analytics job, you can start the job to replay the archived stream data.

powershell
# PowerShell command to start the Stream Analytics job
Start-AzStreamAnalyticsJob -ResourceGroupName “” -Name “

Replace the placeholders with your own values for resource group name and job name in the PowerShell command.

4. Monitor the Job and Analyze Data

You can monitor the Stream Analytics job to check its progress and ensure that the archived stream data is being replayed successfully.

powershell
# PowerShell command to monitor the Stream Analytics job
Get-AzStreamAnalyticsJob -ResourceGroupName “” -Name “

Replace the placeholders with your own values for resource group name and job name in the PowerShell command.

Once the job is running, you can analyze the replayed data using various Azure services, such as Azure Databricks or Azure Synapse Analytics, to gain insights and perform further data engineering tasks.

Conclusion

Replaying archived stream data is a valuable capability in data engineering on Microsoft Azure. By following the steps outlined in this article, you can store and replay stream data, configure a Stream Analytics job, and analyze the replayed data using Azure services. This empowers you to derive meaningful insights and drive data-driven decision-making processes.

Answer the Questions in Comment Section

When replaying archived stream data in Azure Data Explorer, the data can only be replayed as is, without any modifications.

  • True

Which component in Azure Stream Analytics provides the capability to replay archived stream data?

  • Blob storage

When replaying archived stream data in Azure Event Hubs, the order in which the events were originally received is preserved.

  • True

Can archived stream data be replayed to Event Hubs in real time?

  • No, archived stream data can only be replayed to Event Hubs as historical data.

Which service in Azure allows you to schedule the replay of archived stream data?

  • Azure Data Factory

Can you specify a specific time range for replaying archived stream data in Azure Stream Analytics?

  • Yes, you can specify the start and end time for replaying archived stream data.

In Azure Stream Analytics, which function is used to read events from an Azure Blob storage account?

  • OPENROWSET

Can you replay archived stream data from multiple partitions at the same time in Azure Event Hubs?

  • Yes, you can replay archived data from multiple partitions simultaneously.

Which Azure service provides a distributed, scalable, and reliable platform for replaying archived stream data?

  • Azure Stream Analytics

Can you replay archived stream data to multiple destinations simultaneously in Azure Stream Analytics?

  • Yes, you can replay data to multiple outputs at the same time.
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slugabed TTN
8 months ago

I believe the questions below are one and the same “Which service in Azure allows you to schedule the replay of archived stream data?

Which Azure service provides a distributed, scalable, and reliable platform for replaying archived stream data?”

Therefore the answer should be Azure stream analytics.

Daniel Monroy
11 months ago

Great insights on replaying archived stream data for DP-203 exam preparation!

Teodomiro Farias
9 months ago

I found this very helpful. Thanks for sharing!

Sophia Edwards
1 year ago

Can anyone explain how archiving works in Azure Stream Analytics?

Miloslava Franchuk
9 months ago

Is there any impact on performance when archiving stream data?

Caleb Ramirez
1 year ago

Thanks for the detailed post!

Romã Carvalho
1 year ago

Can archived data be replayed into another stream for transformation?

Liam Grewal
1 year ago

I honestly think more practical examples would help.

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