更新时间：2021-06-24 19:04:10
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Introduction to R and SQL Server
Using R prior to SQL Server 2016
Microsoft's commitment to the open source R language
Boosting analytics with SQL Server R integration
Summary
Overview of Microsoft Machine Learning Server and SQL Server
Analytical barriers
The Microsoft Machine learning R Server platform
Microsoft R Open (MRO)
Microsoft Machine Learning R Server
Microsoft SQL Server Machine Learning R Services
R Tools for Visual Studio (RTVS)
The Microsoft Machine Learning R Services architecture
R Limitations
Performance issues
Memory limitations
Security aspects
Language syntax
Managing Machine Learning Services for SQL Server 2017 and R
Minimum requirements
Choosing the edition
Configuring the database
Configuring the environment and installing R Tools for Visual Studio (RTVS)
Security
Resource Governor
Installing new R packages
Package information
Using R Tools for Visual Studio (RTVS) 2015 or higher
Using R.exe in CMD
Using XP_CMDSHELL
Copying files
Using the rxInstallPackages function
Managing SQL Server R Services with PowerShell
Getting to know the sp_execute_external_script external procedure
Arguments
Data Exploration and Data Visualization
Understanding SQL and R data types
Data frames in R
Data exploration and data munging
Importing SQL Server data into R
Exploring data in R
Data munging in R
Adding/removing rows/columns in data frames
More data munging with dplyr
Finding missing values
Transpose data
Pivot / Unpivot data
Example - data exploration and munging using R in T-SQL
Data visualization in R
Plot
Histogram
Boxplot
Scatter plot
Tree diagram
Example – R data visualization in T-SQL
Integrating R code in reports and visualizations
Integrating R in SSRS reports
Integrating R in Power BI
RevoScaleR Package
Overcomming R language limitations
Scalable and distributive computational environments
Functions for data preparation
Data import from SAS SPSS and ODBC
Importing SAS data
Importing SPSS data
Importing data using ODBC
Variable creation and data transformation
Variable creation and recoding
Dataset subsetting
Dataset merging
Functions for descriptive statistics
Functions for statistical tests and sampling
Predictive Modeling
Data modeling
Advanced predictive algorithms and analytics
Deploying and using predictive solutions
Performing predictions with R Services in the SQL Server database
