Spark Documentation

Setup instructions, programming guides, and other documentation are available for each version of Spark below:

• Spark 0.9.0 (latest release)
• Spark 0.8.1
• Spark 0.7.3
• Spark 0.6.2

Read these documents to get started with Spark, as well as with the built-in components (MLlib and Spark Streaming).

In addition, this page lists some external resources for learning Spark.

Video Tutorials

• Screencast 1: First Steps with Spark
• Screencast 2: Spark Documentation Overview
• Screencast 3: Transformations and Caching
• Screencast 4: A Spark Standalone Job in Scala

Hands-On Exercises

• Hands-on exercises are available online from Spark Summit 2013. These exercises let you launch a small EC2 cluster, load a dataset, and query it with Spark, Shark, Spark Streaming, and MLLib.

Training Materials

• Spark Summit 2013 contained a training session for which slides and videos are available for free online. The session also included exercises that you can run on Amazon EC2.
• The UC Berkeley AMPLab regularly hosts training camps on Spark and related projects. Slides and videos are available online:
  • AMP Camp Three (Berkeley, CA, August 2013)
  • AMP Camp Two (Strata Santa Clara, February 2013)
  • AMP Camp One (Berkeley, CA, August 2012)

External Tutorials, Blog Posts, and Talks

• Using Parquet and Scrooge with Spark — Scala-friendly Parquet and Avro usage tutorial from Ooyala's Evan Chan
• Using Spark with MongoDB — by Sampo Niskanen from Wellmo
• Spark Summit 2013 — contained 30 talks about Spark use cases, available as slides and videos
• Sampling Twitter Using Declarative Streams — Spark Streaming tutorial by Patrick Wendell
• A Powerful Big Data Trio: Spark, Parquet and Avro — Using Parquet in Spark by Matt Massie
• Real-time Analytics with Cassandra, Spark, and Shark — Presentation by Evan Chan from Ooyala at 2013 Cassandra Summit
• Getting Spark Setup in Eclipse — Developer blog post by James Percent
• Run Spark and Shark on Amazon Elastic MapReduce — Article by Amazon Elastic MapReduce team member Parviz Deyhim
• Unit testing with Spark — Quantifind tech blog post by Imran Rashid
• Configuring Spark logs — Quantifind tech blog by Imran Rashid
• Spark, an alternative for fast data analytics — IBM Developer Works article by M. Tim Jones

Books

• Fast Data Processing with Spark, by Holden Karau (Packt Publishing)

Examples

• The Spark examples page shows the basic API in Scala, Java and Python.

Wiki

• The Spark wiki contains information for developers, such as architecture documents and how to contribute to Spark.

Research Papers

Spark was initially developed as a UC Berkeley research project, and much of the design is documented in papers. The research page lists some of the original motivation and direction. The following papers have been published about Spark and related projects.

• Shark: SQL and Rich Analytics at Scale. Reynold Xin, Joshua Rosen, Matei Zaharia, Michael J. Franklin, Scott Shenker, Ion Stoica. Technical Report UCB/EECS-2012-214. November 2012.
• Discretized Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large Clusters. Matei Zaharia, Tathagata Das, Haoyuan Li, Scott Shenker, Ion Stoica. HotCloud 2012. June 2012.
• Shark: Fast Data Analysis Using Coarse-grained Distributed Memory (demo). Cliff Engle, Antonio Lupher, Reynold Xin, Matei Zaharia, Haoyuan Li, Scott Shenker, Ion Stoica. SIGMOD 2012. May 2012. Best Demo Award.
• Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica. NSDI 2012. April 2012. Best Paper Award and Honorable Mention for Community Award.
• Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica. Technical Report UCB/EECS-2011-82. July 2011.
• Spark: Cluster Computing with Working Sets. Matei Zaharia, Mosharaf Chowdhury, Michael J. Franklin, Scott Shenker, Ion Stoica. HotCloud 2010. June 2010.