A Julia interface to Apache Spark. Spark.jl provides an interface to Apache Spark™ platform, including SQL / DataFrame and Structured Streaming. It closely follows the PySpark API, making it easy to translate existing Python code to Julia. Spark.jl supports multiple cluster types (in client mode), and can be considered as an analog to PySpark or RSpark within the Julia ecosystem. It supports running within on-premise installations, as well as hosted instances such as Amazon EMR and Azure HDInsight.
Features
- Documentation available
- Spark.jl provides an interface to Apache Spark™ platform
- SQL / DataFrame and Structured Streaming
- It closely follows the PySpark API
- Easy to translate existing Python code to Julia
- Spark.jl supports multiple cluster types
Categories
Data VisualizationLicense
MIT LicenseFollow Spark.jl
Other Useful Business Software
Build Securely on Azure with Proven Frameworks
Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Spark.jl!