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Contents
Title and Copyright Information
Preface
Audience
Documentation Accessibility
Related Documents
Oracle R Enterprise Online Resources
Conventions
Changes in This Release for Oracle R Enterprise
Changes in Oracle R Enterprise 1.5.1
New Features for Oracle Database Release 12.1.0.2 and Earlier
New Features for Oracle Database Release 12.2.0.1
OAAgraph Package
New Features of the OREdm Package
Changes in Oracle R Enterprise 1.5
New Features in Oracle R Enterprise 1.5
R for Datastore and Script Repository Management
PL/SQL and Data Dictionary Views for Datastore and Script Repository Management
ore.groupApply Function Changes
ore.randomForest Modeling Function
ore.summary Function Changes
Statistical Function Method Changes
Support for BLOB and CLOB Data Types
Changes in Oracle R Enterprise 1.4.1
New Features in Oracle R Enterprise 1.4.1
Other Changes in Oracle R Enterprise 1.4.1
Changes in Oracle R Enterprise 1.4
New Features in Oracle R Enterprise 1.4
Changes in Oracle R Enterprise 1.3
New Features in Oracle R Enterprise 1.3
Other Changes in Oracle R Enterprise 1.3
Changes in Oracle R Enterprise 1.1
1
Introducing Oracle R Enterprise
1.1
About Oracle R Enterprise
1.2
Advantages of Oracle R Enterprise
1.3
Get Online Help for Oracle R Enterprise Classes, Functions, and Methods
1.4
About Transparently Using R on Oracle Database Data
1.4.1
About the Transparency Layer
1.4.2
Transparency Layer Support for R Data Types and Classes
1.4.2.1
About Oracle R Enterprise Data Types and Classes
1.4.2.2
About the ore.frame Class
1.4.2.3
Support for R Naming Conventions
1.4.2.4
About Coercing R and Oracle R Enterprise Class Types
1.5
Typical Operations in Using Oracle R Enterprise
1.6
Oracle R Enterprise Global Options
1.7
Oracle R Enterprise Examples
1.7.1
Listing the Oracle R Enterprise Examples
1.7.2
Running an Oracle R Enterprise Example Script
2
Getting Started with Oracle R Enterprise
2.1
Connecting to an Oracle Database Instance
2.1.1
About Connecting to the Database
2.1.1.1
About Using the ore.connect Function
2.1.1.2
About Using the ore.disconnect Function
2.1.2
Using the ore.connect and ore.disconnect Functions
2.2
Creating and Managing R Objects in Oracle Database
2.2.1
Creating R Objects for In-Database Data
2.2.1.1
About Creating R Objects for Database Objects
2.2.1.2
Using the ore.sync Function
2.2.1.3
Using the ore.get Function
2.2.1.4
Using the ore.attach Function
2.2.2
Creating Ordered and Unordered ore.frame Objects
2.2.2.1
About Ordering in ore.frame Objects
2.2.2.2
Global Options Related to Ordering
2.2.2.3
Ordering Using Keys
2.2.2.4
Ordering Using Row Names
2.2.2.5
Using Ordered Frames
2.2.3
Moving Data to and from the Database
2.2.4
Creating and Deleting Database Tables
2.2.5
Saving and Managing R Objects in the Database
2.2.5.1
About Persisting Oracle R Enterprise Objects
2.2.5.2
About Oracle R Enterprise Datastores
2.2.5.3
Saving Objects to a Datastore
2.2.5.4
Control Access to Datastores
2.2.5.5
Getting Information about Datastore Contents
2.2.5.6
Restoring Objects from a Datastore
2.2.5.7
Deleting a Datastore
2.2.5.8
About Using a datastore in Embedded R Execution
3
Preparing and Exploring Data in the Database
3.1
Preparing Data in the Database Using Oracle R Enterprise
3.1.1
About Preparing Data in the Database
3.1.2
Selecting Data
3.1.2.1
Selecting Data by Column
3.1.2.2
Selecting Data by Row
3.1.2.3
Selecting Data by Value
3.1.3
Indexing Data
3.1.4
Combining Data
3.1.5
Summarizing Data
3.1.6
Transforming Data
3.1.7
Sampling Data
3.1.8
Partitioning Data
3.1.9
Preparing Time Series Data
3.2
Exploring Data
3.2.1
About the Exploratory Data Analysis Functions
3.2.2
About the NARROW Data Set for Examples
3.2.3
Correlating Data
3.2.4
Cross-Tabulating Data
3.2.5
Analyzing the Frequency of Cross-Tabulations
3.2.6
Building Exponential Smoothing Models on Time Series Data
3.2.7
Ranking Data
3.2.8
Sorting Data
3.2.9
Summarizing Data with ore.summary
3.2.10
Analyzing Distribution of Numeric Variables
3.2.11
Principal Component Analysis
3.2.12
Singular Value Decomposition
3.3
Data Manipulation Using OREdplyr
3.3.1
Select and Order Data
3.3.1.1
Examples of Selecting Columns
3.3.1.2
Examples of Programming with select_
3.3.1.3
Examples of Selecting Distinct Columns
3.3.1.4
Examples of Selecting Rows by Position
3.3.1.5
Examples of Arranging Columns
3.3.1.6
Examples of Filtering Columns
3.3.1.7
Examples of Mutating Columns
3.3.2
Join Rows
3.3.3
Group Columns and Rows
3.3.4
Aggregate Columns and Rows
3.3.5
Sample Rows
3.3.6
Rank Rows
3.4
Graph Analysis Using OAAgraph
3.5
Using a Third-Party Package on the Client
4
Building Models in Oracle R Enterprise
4.1
Building Oracle R Enterprise Models
4.1.1
About OREmodels Functions
4.1.2
About the longley Data Set for Examples
4.1.3
Building Linear Regression Models
4.1.4
Building a Generalized Linear Model
4.1.5
Building a Neural Network Model
4.1.6
Building a Random Forest Model
4.2
Building Oracle Data Mining Models
4.2.1
About Building Oracle Data Mining Models using Oracle R Enterprise
4.2.1.1
Oracle Data Mining Models Supported by Oracle R Enterprise
4.2.1.2
About Oracle Data Mining Models Built by Oracle R Enterprise Functions
4.2.1.3
Partitioning and Text Mining
4.2.2
Building an Association Rules Model
4.2.3
Building an Attribute Importance Model
4.2.4
Building a Decision Tree Model
4.2.5
Building an Expectation Maximization Model
4.2.6
Building an Explicit Semantic Analysis Model
4.2.7
Building an Extensible R Algorithm Model
4.2.8
Building General Linearized Models
4.2.9
Building a k-Means Model
4.2.10
Building a Naive Bayes Model
4.2.11
Building a Non-Negative Matrix Factorization Model
4.2.12
Building an Orthogonal Partitioning Cluster Model
4.2.13
Building a Singular Value Decomposition Model
4.2.14
Building a Support Vector Machine Model
4.3
Cross-Validating Models
5
Predicting With R Models
5.1
About the ore.predict Function
5.2
Using the ore.predict Function
6
Using Oracle R Enterprise Embedded R Execution
6.1
About Oracle R Enterprise Embedded R Execution
6.1.1
Benefits of Embedded R Execution
6.1.2
APIs for Embedded R Execution
6.1.3
Security Considerations for Scripts
6.1.4
Support for Parallel Execution
6.1.5
Installing a Third-Party Package for Use in Embedded R Execution
6.2
R Interface for Embedded R Execution
6.2.1
Arguments for Functions that Run Scripts
6.2.1.1
Input Function to Execute
6.2.1.2
Optional and Control Arguments
6.2.1.3
Structure of Return Value
6.2.1.4
Input Data
6.2.1.5
Parallel Execution
6.2.1.6
Unique Arguments
6.2.2
Manage Scripts in R
6.2.3
Using the ore.doEval Function
6.2.4
Using the ore.tableApply Function
6.2.5
Using the ore.groupApply Function
6.2.5.1
Partitioning on a Single Column
6.2.5.2
Partitioning on Multiple Columns
6.2.6
Using the ore.rowApply Function
6.2.7
Using the ore.indexApply Function
6.2.7.1
Simple Example of Using the ore.indexApply Function
6.2.7.2
Column-Parallel Use Case
6.2.7.3
Simulations Use Case
6.3
SQL Interface for Embedded R Execution
6.3.1
About Oracle R Enterprise SQL Table Functions
6.3.1.1
Parameters of the SQL Table Functions
6.3.1.2
Return Value of SQL Table Functions
6.3.1.3
Connecting to Oracle R Enterprise in Embedded R Execution
6.3.2
Manage Scripts in SQL
6.3.2.1
Creating a Script with the SQL APIs
6.3.3
Manage Datastores in SQL
A
SQL APIs for Oracle R Enterprise
A.1
rqDropDataStore Procedure
A.2
rqEval Function
A.3
rqGrant Procedure
A.4
rqGroupEval Function
A.5
rqRevoke Procedure
A.6
rqRowEval Function
A.7
rqTableEval Function
A.8
sys.rqScriptCreate Procedure
A.9
sys.rqScriptDrop Procedure
B
Oracle Database Views for Oracle R Enterprise
B.1
ALL_RQ_DATASTORES
B.2
ALL_RQ_SCRIPTS
B.3
RQUSER_DATASTORECONTENTS
B.4
RQUSER_DATASTORELIST
B.5
USER_RQ_DATASTORE_PRIVS
B.6
USER_RQ_DATASTORES
B.7
USER_RQ_SCRIPT_PRIVS
B.8
USER_RQ_SCRIPTS
C
R Operators and Functions Supported by Oracle R Enterprise
Index
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