Association for Computing Machinery (ACM)

Introduction to Spark 2.0 for Database Researchers

Michael Armbrust ¹

Doug Bateman ²

Reynold Xin ¹

Matei Zaharia ³

Hide authors affiliations Show authors affiliations: 3 affiliations

Databricks, San Francisco, CA, USA |

Databricks, doug.bateman@databricks.com, CA, USA |

Databricks & Massachusetts Institute of Technology, San Francisco, CA, USA |

Publication type: Proceedings Article

Publication date: 2016-06-26

Association for Computing Machinery (ACM)

DOI: 10.1145/2882903.2912565

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Abstract

Originally started as an academic research project at UC Berkeley, Apache Spark is one of the most popular open source projects for big data analytics. Over 1000 volunteers have contributed code to the project; it is supported by virtually every commercial vendor; many universities are now offering courses on Spark. Spark has evolved significantly since the 2010 research paper: its foundational APIs are becoming more relational and structural with the introduction of the Catalyst relational optimizer, and its execution engine is developing quickly to adopt the latest research advances in database systems such as whole-stage code generation.

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Association for Computing Machinery (ACM)