New R Driver Option in MongoDB 3.6

#mongodb #rlanguage #36

In a previous post, I discussed some options for using MongoDB with the R Language. While the information in that post is still accurate, MongoDB 3.6 introduces a new R driver option. Unlike the drivers previously discussed, this new R driver is under active development.

New R Driver

The new R driver, mongolite, can be found on GitHub and is easily installed from the Comprehensive R Archive Network (CRAN) using the install.packages("mongolite") command on Windows or OS-X. The driver, or client, is authored by Jeroen Ooms who also has provided some nice documentation in PDF format. Let’s head into RStudio and take a look at using the new R driver.

Accessing MongoDB

Let’s use the same dataset as in the previous post and, with mongoimport, get the data into a MongoDB collection. The database again will be called kenblog and the collection is scores. Here again is a sample document in the collection:

{
   "_id" : ObjectId("5627207b33ff2cf40effc25e"),
   "student" : 2,
   "type" : "quiz",
   "score" : 74
}

After using the install.packages("mongolite") command, we can put the power of R to work. We establish a connection to our database:

> require("mongolite")
Loading required package: mongolite
> connection <- mongo(collection = "scores", db = "kenblog", url = "mongodb://localhost")

The mongo connection method accepts the following arguments:

collection
db
url
verbose
options

The collection and db arguments allow for the specification of the names of the respective database information. url is the mongo connection string in URI format. If you need additional output from the connection one can set the verbose boolean value to TRUE. Additional connection options, such as SSL information, can also be passed in.

With a connection established, let’s query our scores collection for exam data.

examQuery <- connection$find('{"type": "exam"}')

This brings in our 585 exam documents. We can then create a vector of the exam scores and have a look at their summary.

> exam_scores <- examQuery[c('score')] 
> summary(exam_scores)
     score       
 Min. : 60.00  
 1st Qu.: 72.00  
 Median : 79.00  
 Mean : 79.45  
 3rd Qu.: 86.00  
 Max. :100.00

Personally, I’m already liking the syntax of this new R driver for doing queries and working with MongoDB in R.

Other methods that will be familiar to MongoDB users are drop() to drop a collection, aggregate for aggregation pipeline operations, and insert for creating information in the database. There are many additional methods that can be used that allow for map-reduce operations and importing or exporting JSON or BSON data, and many more.

Further, with support for features such as indexing, encryption, and authentication, this new R driver is much more robust than previous options.

Wrap Up

Connecting to MongoDB from R is pretty straightforward and simple using the new R driver. It is the new “official” and supported method to leverage the power of R with the flexibility and power of MongoDB.

R is a great statistical language and can definitely be used to query and analyze MongoDB collections. If you are using R in your work today, this new way of connecting with MongoDB is definitely worth a look.

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There are a few MongoDB specific terms in this post. I created a MongoDB Dictionary skill for the Amazon Echo line of products. Check it out and you can say “Alexa, ask MongoDB for the definition of a document?” and get a helpful response.