Spark Connector R Guide
For the source code that contains the examples below, see introduction.R.
Prerequisites
- Basic working knowledge of MongoDB and Apache Spark. Refer to the MongoDB documentation and Spark documentation for more details.
- Running MongoDB instance (version 2.6 or later).
- Spark 2.4.x.
- Scala 2.12.x
Getting Started
sparkR Shell
This tutorial uses the sparkR shell, but the code examples work
just as well with self-contained R applications.
When starting the sparkR shell, you can specify:
the
--packagesoption to download the MongoDB Spark Connector package. The following package is available:mongo-spark-connector_2.12for use with Scala 2.12.x
the
--confoption to configure the MongoDB Spark Connnector. These settings configure theSparkConfobject.NoteWhen specifying the Connector configuration via
SparkConf, you must prefix the settings appropriately. For details and other available MongoDB Spark Connector options, see the Configuration Options.
For example,
./bin/sparkR --conf "spark.mongodb.input.uri=mongodb://127.0.0.1/test.myCollection?readPreference=primaryPreferred" \ --conf "spark.mongodb.output.uri=mongodb://127.0.0.1/test.myCollection" \ --packages org.mongodb.spark:mongo-spark-connector_2.12:3.0.1
- The spark.mongodb.input.uri specifies the
MongoDB server address (
127.0.0.1), the database to connect (test), and the collection (myCollection) from which to read data, and the read preference. - The spark.mongodb.output.uri specifies the
MongoDB server address (
127.0.0.1), the database to connect (test), and the collection (myCollection) to which to write data. Connects to port27017by default. - The
packagesoption specifies the Spark Connector's Maven coordinates, in the formatgroupId:artifactId:version.
Create a SparkSession Object
When you start sparkR you get a SparkSession object called
spark by default. In a standalone R application, you need
to create your SparkSession object explicitly, as show below.
If you specified the spark.mongodb.input.uri
and spark.mongodb.output.uri configuration options when you
started sparkR, the default SparkSession object uses them.
If you'd rather create your own SparkSession object from within
sparkR, you can use sparkr.session() and specify different
configuration options.
my_spark <- sparkR.session( master="local[*]", sparkConfig=list(), appName="my_app" )
You can use a SparkSession object to write data to MongoDB, read
data from MongoDB, create DataFrames, and perform SQL operations.