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NEW QUESTION: 1



A. R1
B. ASW1
C. R4
D. DSW1
E. DSW2
F. R3
G. R2
H. ASW2
Answer: G

NEW QUESTION: 2
You have an Apache Storm cluster.
You need to ingest data from a Kafka queue.
Which component should you use to consume data emitted from Kaka?
A. Flume
B. a bolt
C. a Microsoft Azure Service Bus queue
D. a spout
Answer: D
Explanation:
Explanation
To perform real-time computation on Storm, we create "topologies." A topology is a graph of a computation, containing a network of nodes called "Spouts" and "Bolts." In a Storm topology, a Spout is the source of data streams and a Bolt holds the business logic for analyzing and processing those streams.
The org.apache.storm.kafka.KafkaSpout component reads data from Kafka.
Example:

References:
https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-apache-storm-with-kafka
https://hortonworks.com/blog/storm-kafka-together-real-time-data-refinery/

NEW QUESTION: 3
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure Data Lake Storage account that contains a staging zone.
You need to design a daily process to ingest incremental data from the staging zone, transform the data by executing an R script, and then insert the transformed data into a data warehouse in Azure Synapse Analytics.
Solution: You use an Azure Data Factory schedule trigger to execute a pipeline that copies the data to a staging table in the data warehouse, and then uses a stored procedure to execute the R script.
Does this meet the goal?
A. No
B. Yes
Answer: B
Explanation:
Explanation
If you need to transform data in a way that is not supported by Data Factory, you can create a custom activity with your own data processing logic and use the activity in the pipeline. You can create a custom activity to run R scripts on your HDInsight cluster with R installed.
Reference:
https://docs.microsoft.com/en-US/azure/data-factory/transform-data