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Operational Analytics with Microsoft Azure Synapse Analytics Week 3 | Test prep Quiz Answers

Test prep Quiz Answers

Question 1)
Synapse Apache Spark allows you to ingest data into an Azure Cosmos DB. Data is always ingested into Azure Cosmos DB containers through which of the following:

• The Transactional store
• The Relational store
• The Analytical store

Question 2)
The following snippet of code has been added to the first cell of a notebook.

dfCustomer = spark.read\
.format(“cosmos.olap”)\
.option(“spark.synapse.linkedService”, “AdventureWorksSQL”)\
.option(“spark.cosmos.container”, “Customer”)\
.load()

Assuming all the requirements to run this code are already in place, what is the purpose of the code on line 4?
.option(“spark.cosmos.container”, “Customer”)\

• Creates a new container
• Specifies the destination to load data into after a query has run against the source data
• Specifies the name of the container that we wish to read

Question 3)
Assuming all prerequisites have been met to run the following snippet of code in an Azure Synapse Analytics notebook what will this piece of code output?
display(dfCustomer.groupBy(“address.country”,”address.city”).count().orderBy(“count”, ascending=False).limit(10))

• The result will display the top 10 country, city combinations having the most customers, At the bottom of the list will be customers who have no country or city information within the customer profile
• The result will display the top 10 country, city combinations having the most customers, At the top of the list will be customers who have no country or city information within the customer profile
• The result will only display the top 10 countries having the most customers, At the top of the list will be customers who have no country or city information within the customer profile
• The result will only display the top 10 countries having the most customers, At the bottom of the list will be customers who have no country or city information within the customer profile

Question 4)
Which of the following SparkSQL methods creates a connection to allow reading data from an analytical store?

• cosmos.db
• cosmos.olap
• cosmos.oltp

Question 5)
Azure Cosmos Core API account for MongoDB, uses full fidelity schema representation by default. This means that all top-level properties of a document are represented as columns with the associated property values as the value of the column.
Azure Cosmos DB automatically has system properties such as _ts, _self, _attachments, _rid, and _etag associated with every document. These system document properties are seldom useful for analytical store query purposes and can be removed using which of the following PySpark code snippet examples?

• customer_columns = list(set(dfCustomer.columns) = system_document_properties)
  system_document_properties = {‘_attachments’,’_etag’,’_rid’,’_self’,’_ts’}
• system_document_properties – {‘_attachments’,’_etag’,’_rid’,’_self’,’_ts’}
  customer_columns = list(set(dfCustomer.columns) = system_document_properties)
• system_document_properties = {‘_attachments’,’_etag’,’_rid’,’_self’,’_ts’}
  customer_columns = list(set(dfCustomer.columns) – system_document_properties)

Question 6)
By default, the OPENJSON table-valued function returns three columns. As an alternative, you can explicitly specify the schema of the result set that OPENJSON returns by providing which of the following clauses?

• Include
• Explicit
• With
• Insert

Question 7)
Once Azure Synapse Link is configured on Cosmos DB, what is the first step to perform to use Azure Synapse Analytics serverless SQL pools to query the Azure Cosmos DB data?

• Use the OPENROWSET function
• Use a SELECT clause
• Create a database

Question 8)
What function provides a rowset view over a JSON document?

• WITH
• OPENROWSET
• OPENJSON