DP-200 Azure Real-Time and Batch Analytics 1 — Questions and Answers
Question 1: Which Azure service is the managed platform for running Apache Spark and Apache Hadoop clusters for large-scale batch processing?
- Azure Databricks
- Azure HDInsight (Correct answer)
- Azure Synapse Spark Pool
- Azure Batch
Correct answer: Azure HDInsight
Azure HDInsight is Microsoft's fully managed cloud distribution of open-source frameworks including Hadoop, Spark, Kafka, and HBase.
Question 2: What Azure service provides a fully managed, serverless Apache Spark environment integrated with Azure Synapse Analytics?
- Azure HDInsight
- Azure Synapse Spark pool (Correct answer)
- Azure Databricks
- Azure Machine Learning Compute
Correct answer: Azure Synapse Spark pool
Azure Synapse Spark pools provide on-demand, auto-scaling Apache Spark clusters within the Synapse workspace, billed per second of use.
Question 3: In Azure Event Hubs, what is a consumer group?
- A group of Event Hub namespaces sharing a single connection string
- A logical view of an Event Hub that enables multiple consumers to read the stream independently at their own pace (Correct answer)
- A batch of events grouped for delivery
- A security group controlling access to Event Hub topics
Correct answer: A logical view of an Event Hub that enables multiple consumers to read the stream independently at their own pace
Consumer groups allow multiple downstream consumers (e.g., Stream Analytics, Databricks, a custom app) to each read the full event stream independently without interfering.
Question 4: Which Azure service is best suited for orchestrating complex data workflows that include both batch and real-time components with dependencies between steps?
- Azure Logic Apps
- Azure Data Factory (Correct answer)
- Azure Functions
- Azure Scheduler
Correct answer: Azure Data Factory
Azure Data Factory is a cloud-scale data integration service that orchestrates both batch ETL and hybrid data pipelines with rich dependency and scheduling capabilities.
Question 5: In a lambda architecture built on Azure, what is the role of the batch layer?
- To process streaming data in milliseconds
- To reprocess all historical data periodically to produce accurate, comprehensive batch views (Correct answer)
- To cache query results for the serving layer
- To route events to multiple downstream consumers
Correct answer: To reprocess all historical data periodically to produce accurate, comprehensive batch views
The batch layer processes the complete historical dataset to produce accurate batch views, compensating for any errors in the speed layer.
Question 6: What is the primary purpose of Azure Event Hubs Capture?
- To replay events back to producers
- To automatically archive streaming events to Azure Blob Storage or ADLS Gen2 for batch analysis (Correct answer)
- To encrypt event payloads before storage
- To filter events based on content
Correct answer: To automatically archive streaming events to Azure Blob Storage or ADLS Gen2 for batch analysis
Event Hubs Capture automatically stores the full stream of events to Azure Blob Storage or ADLS Gen2 in Avro format for downstream batch processing.
DP-200 Azure Real-Time and Batch Analytics 1
Which Azure service is the managed platform for running Apache Spark and Apache Hadoop clusters for large-scale batch processing?