Third Party Projects

This page tracks external software projects that supplement Apache Spark and add to its ecosystem.

spark-packages.org

spark-packages.org is an external, community-managed list of third-party libraries, add-ons, and applications that work with Apache Spark. You can add a package as long as you have a GitHub repository.

Infrastructure Projects

• Spark Job Server - REST interface for managing and submitting Spark jobs on the same cluster (see blog post for details)
• SparkR - R frontend for Spark
• MLbase - Machine Learning research project on top of Spark
• Apache Mesos - Cluster management system that supports running Spark
• Alluxio (née Tachyon) - Memory speed virtual distributed storage system that supports running Spark
• Spark Cassandra Connector - Easily load your Cassandra data into Spark and Spark SQL; from Datastax
• FiloDB - a Spark integrated analytical/columnar database, with in-memory option capable of sub-second concurrent queries
• ElasticSearch - Spark SQL Integration
• Spark-Scalding - Easily transition Cascading/Scalding code to Spark
• Zeppelin - an IPython-like notebook for Spark.  There is also ISpark, and the Spark Notebook.
• IBM Spectrum Conductor with Spark - cluster management software that integrates with Spark
• EclairJS -  enables Node.js developers to codeagainst Spark, and data scientists to use Javascript in Jupyter notebooks.
• SnappyData - an open source OLTP + OLAP database integrated with Spark on the same JVMs.
• GeoSpark - Geospatial RDDs and joins
  
• Spark Cluster Deploy Tools for OpenStack

Applications Using Spark

• Apache Mahout - Previously on Hadoop MapReduce, Mahout has switched to using Spark as the backend
• Apache MRQL - A query processing and optimization system for large-scale, distributed data analysis, built on top of Apache Hadoop, Hama, and Spark
• BlinkDB - a massively parallel, approximate query engine built on top of Shark and Spark
  
• Spindle - Spark/Parquet-based web analytics query engine
• Spark Spatial - Spatial joins and processing for Spark
• Thunderain - a framework for combining stream processing with historical data, think Lamba architecture
• DF from Ayasdi - a Pandas-like data frame implementation for Spark
• Oryx -  Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning
• ADAM - A framework and CLI for loading, transforming, and analyzing genomic data using Apache Spark