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Analyze Amazon S3 Data in R

Use standard R functions and the development environment of your choice to analyze Amazon S3 data with the CData JDBC Driver for Amazon S3.

Access Amazon S3 data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for Amazon S3 and the RJDBC package to work with remote Amazon S3 data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to Amazon S3 and visualize Amazon S3 data by calling standard R functions.

Install R

You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:

library(RJDBC)

Connect to Amazon S3 as a JDBC Data Source

You will need the following information to connect to Amazon S3 as a JDBC data source:

  • Driver Class: Set this to cdata.jdbc.amazons3.AmazonS3Driver
  • Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for Amazon S3:

driver <- JDBC(driverClass = "cdata.jdbc.amazons3.AmazonS3Driver", classPath = "MyInstallationDir\lib\cdata.jdbc.amazons3.jar", identifier.quote = "'")

You can now use DBI functions to connect to Amazon S3 and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

To authorize Amazon S3 requests, provide the credentials for an administrator account or for an IAM user with custom permissions. Set AccessKey to the access key Id. Set SecretKey to the secret access key.

Note: You can connect as the AWS account administrator, but it is recommended to use IAM user credentials to access AWS services.

For information on obtaining the credentials and other authentication methods, refer to the Getting Started section of the Help documentation.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Amazon S3 JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.amazons3.jar

Fill in the connection properties and copy the connection string to the clipboard.

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:amazons3:AccessKey=a123;SecretKey=s123;")

Schema Discovery

The driver models Amazon S3 APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the Amazon S3 API:

objectsacl <- dbGetQuery(conn,"SELECT Name, OwnerId FROM ObjectsACL WHERE Name = 'TestBucket'")

You can view the results in a data viewer window with the following command:

View(objectsacl)

Plot Amazon S3 Data

You can now analyze Amazon S3 data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:

par(las=2,ps=10,mar=c(5,15,4,2)) barplot(objectsacl$OwnerId, main="Amazon S3 ObjectsACL", names.arg = objectsacl$Name, horiz=TRUE)