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NEW QUESTION: 1
There are two single-select attributes in an array set. The first single-select attribute shows a list of countries and the second attribute shows a list of states.
Which is the most efficient way to show relevant states based on chosen country?
A. Load all country and state combinations in a data table and write a Constraint rule to lookup the data table.
B. Use the Hiding rule, which is the only possible option, because arrays do not do not support Constraint rules.
C. Create Hiding rules for each country with Simple Conditions, and then select valid states for the Action attribute. In this case, the number of Hiding rules will be equal to the number of countries.
D. Create a Constraint rule for each country in the drop-down list by using Simple Conditions and select valid states for the Action attribute of the rule. In this case, number of rules will be equal to the number of countries in the list.
Answer: C

NEW QUESTION: 2
You plan to analyze data on a local computer. To improve performance, you plan to alternate the operation between a Microsoft SQL Server and the local computer.
You need to run complex code on the SQL Server, and then revert to the local compute context.
Which R code segment should you use?
A. sqlCompute <- RxInSqlServer(connectionstring = sqlConnString, shareDir = sqlShareDir,wait = sqlWait, consoleOutput = sqlConsoleOutput)rxSetComputeContext("sqlCompute")x <- 1:10rxExec(print, x, elemType
= "cores", timesToRun = 10)rxSetComputeContext("local")
B. sqlCompute <- RxInSqlServer(connectionstring = sqlConnString, shareDir = sqlShareDir,wait = sqlWait, consoleOutput = sqlConsoleOutput)rxSetComputeContext("local")x <- 1:10rxExec(print, x, elemType =
"cores", timesToRun = 10)rxSetComputeContext("sqlCompute")
C. sqlCompute <- RxInSqlServer(connectionString = "Driver=SQL Server;Server = myServer; Database = TestDB; Uid = myID; Pwd = myPwd;")sqlPackagePaths <- RxFindPackage(package = "RevoScaleR", computeContext = sqlServerCompute)
D. sqlCompute <- RxInSqlServer(connectionstring = sqlConnString, shareDir = sqlShareDir,wait = sqlWait, consoleOutput = sqlConsoleOutput)rxSetComputeContext("local")x <- 1:10rxExec(print, x, elemType =
"cores", timesToRun = 10)rxSetComputeContext("RxLocalParallel")
Answer: B
Explanation:
References: https://docs.microsoft.com/en-us/sql/advanced-analytics/tutorials/deepdive-define-and-use-compute-contexts

NEW QUESTION: 3
You define a datastore named ml-data for an Azure Storage blob container. In the container, you have a folder named train that contains a file named data.csv. You plan to use the file to train a model by using the Azure Machine Learning SDK.
You plan to train the model by using the Azure Machine Learning SDK to run an experiment on local compute.
You define a DataReference object by running the following code:

You need to load the training data.
Which code segment should you use?


A. Option A
B. Option B
C. Option D
D. Option C
E. Option E
Answer: E
Explanation:
Example:
data_folder = args.data_folder
# Load Train and Test data
train_data = pd.read_csv(os.path.join(data_folder, 'data.csv'))
Reference:
https://www.element61.be/en/resource/azure-machine-learning-services-complete-toolbox-ai

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