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Which statement should you use for each environment?

DRAG DROP
You need to set the compute context for three different target environments.
Which statement should you use for each environment? To answer, drag the appropriate statements to the
correct execution contexts. Each statement may be used once, more than once, or not at all. You may need to
drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:

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Answer:

Explanation:
https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-r-server-compute-contexts

2 Comments on “Which statement should you use for each environment?

  1. Levo says:

    QUESTION 1
    You perform an analysis that produces the decision tree shown in the exhibit. (Click the Exhibit button.)

    How many leaf nodes are there on the tree?

    A. 2
    B. 3
    C. 5
    D. 7

    Answer: C

    QUESTION 2
    You plan to read data from an Oracle database table and to store the data in the file system for later processing by dplyrXdf. The size of the data is larger than the memory on the server to be used for modelling.
    You need to ensure that the data can be processed by dplyrXdf in the least amount of time possible.
    How should you transfer the data from the Oracle database?

    A. Define a data source to the Oracle database server by using RxOdbcData. Use rxImport to save the data to a comma-separated values (CSV) file.
    B. Use the RODBC library, connect to the Oracle database server by using odbcConnect, and then use rxDataStep to export the data to a comma-separated values (CSV) file.
    C. Define a data source to the Oracle database server by using RxOdbcData, and then use rxImport to save the data to an XDF file.
    D. Use the RODBC library, connect to the Oracle database server by using odbcConnect, and then use rxSplit to save the data to multiple comma-separated values (CSV) file.

    Answer: C

    QUESTION 3
    Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
    You need to estimate a model where the outcome variable is continuous, is in the range of [0, inf], and has a substantial mass at an exact value of 0.
    Which function should you use?

    A. rxPredict
    B. rxLogit
    C. summary
    D. rxLinMod
    E. rxTweedie
    F. stepAic
    G. rxTransform
    H. rxDataStep

    Answer: F

    QUESTION 4
    Drag and Drop Question
    You are using rxPredict for a logistic regression model.
    You need to obtain prediction standard errors and confidence intervals. Which R code segment should you use? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
    NOTE: Each correct selection is worth one point.

    Answer:

    QUESTION 5
    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 = "Driver=SQL Server;Server = myServer; Database = TestDB; Uid = myID; Pwd = myPwd;")sqlPackagePaths <- RxFindPackage(package = "RevoScaleR", computeContext = sqlServerCompute)
    B. sqlCompute <- RxInSqlServer(connectionstring = sqlConnString, shareDir = sqlShareDir,wait = sqlWait, consoleOutput =
    sqlConsoleOutput)rxSetComputeContext("local")x <- 1:10rxExec(print, x, elemType = "cores", timesToRun = 10)rxSetComputeContext("RxLocalParallel")
    C. sqlCompute <- RxInSqlServer(connectionstring = sqlConnString, shareDir = sqlShareDir,wait = sqlWait, consoleOutput =
    sqlConsoleOutput)rxSetComputeContext("sqlCompute")x <- 1:10rxExec(print, x, elemType = "cores", timesToRun = 10)rxSetComputeContext("local")




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