Once the Data Sources API has been released, we’ve wanted to take advantage of these new features and, for this reason, we have developed a Spark-MongoDB library. With this new connector we help the growing MongoDB community to simplify the interaction with this datasource via Spark.
This library provides the mechanism for accessing MongoDB collections in a structured way from SparkSQL, accesible from Python and Scala API’s. Since MongoDB is an open-source document database leader among NoSQL databases and is highly used in several projects [http://www.mongodb.com/leading-nosql-database] we find this connection with all the operations permitted by SparkSQL not only useful but necessary.
Our library uses the 2.13.0 MongoDB Java Driver (that supports the newest MongoDB versions). We use the Casbah toolkit in order to better integrate our Scala implementation with MongoDB. Thus, the project becomes cleaner and less verbose while allowing for a simpler and more intuitive way of developing.
SparkSQL is being rapidly developed, giving support for reading data from other formats (Apache Hive, Parquet, …) and the chance of performing many operations with this data. With our library we extend these possibilities by adding other datasource with which the user could combine existing data in other formats.
We are looking forward for the new Spark 1.3 to keep updating and evolving our library.
Loreto Fernández Costas is a developer at Stratio Big Data. She graduated from Universidad Politécnica de Madrid in Computer Engineering. Her background started with Robotics and now she is discovering the Big Data world amazed with the possibilities that these technologies are capable of.