- (Exam Topic 3)
You are building an Azure Analytics query that will receive input data from Azure IoT Hub and write the results to Azure Blob storage.
You need to calculate the difference in readings per sensor per hour.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Solution:
Box 1: LAG
The LAG analytic operator allows one to look up a “previous” event in an event stream, within certain constraints. It is very useful for computing the rate of growth of a variable, detecting when a variable crosses a threshold, or when a condition starts or stops being true.
Box 2: LIMIT DURATION
Example: Compute the rate of growth, per sensor: SELECT sensorId,
growth = reading
LAG(reading) OVER (PARTITION BY sensorId LIMIT DURATION(hour, 1)) FROM input
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/lag-azure-stream-analytics
Does this meet the goal?
Correct Answer:
A
- (Exam Topic 3)
You have an Azure Synapse Analytics dedicated SQL pool named Pool1 and an Azure Data Lake Storage Gen2 account named Account1.
You plan to access the files in Account1 by using an external table.
You need to create a data source in Pool1 that you can reference when you create the external table. How should you complete the Transact-SQL statement? To answer, select the appropriate options in the
answer area.
NOTE: Each correct selection is worth one point.
Solution:
Graphical user interface, diagram Description automatically generated
Box 1: blob
The following example creates an external data source for Azure Data Lake Gen2 CREATE EXTERNAL DATA SOURCE YellowTaxi
WITH ( LOCATION = 'https://azureopendatastorage.blob.core.windows.net/nyctlc/yellow/', TYPE = HADOOP)
Box 2: HADOOP
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-external-tables
Does this meet the goal?
Correct Answer:
A
- (Exam Topic 3)
You are planning a solution to aggregate streaming data that originates in Apache Kafka and is output to Azure Data Lake Storage Gen2. The developers who will implement the stream processing solution use Java,
Which service should you recommend using to process the streaming data?
Correct Answer:
C
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/stream-processing
- (Exam Topic 3)
You have an Azure subscription that contains an Azure Blob Storage account named storage1 and an Azure Synapse Analytics dedicated SQL pool named Pool1.
You need to store data in storage1. The data will be read by Pool1. The solution must meet the following requirements:
Enable Pool1 to skip columns and rows that are unnecessary in a query. Automatically create column statistics. Minimize the size of files.
Which type of file should you use?
Correct Answer:
B
Automatic creation of statistics is turned on for Parquet files. For CSV files, you need to create statistics manually until automatic creation of CSV files statistics is supported.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/develop-tables-statistics
- (Exam Topic 3)
You have an Azure Data Factory that contains 10 pipelines.
You need to label each pipeline with its main purpose of either ingest, transform, or load. The labels must be available for grouping and filtering when using the monitoring experience in Data Factory.
What should you add to each pipeline?
Correct Answer:
D
Annotations are additional, informative tags that you can add to specific factory resources: pipelines, datasets, linked services, and triggers. By adding annotations, you can easily filter and search for specific factory resources.
Reference:
https://www.cathrinewilhelmsen.net/annotations-user-properties-azure-data-factory/