Encyclopedia of Big Data Technologies

2019 Edition
| Editors: Sherif Sakr, Albert Y. Zomaya

Spark SQL

  • Xiao Li
  • Cheng Lian
  • Shu MoEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-319-77525-8_251

Definitions

SQL is a highly scalable and efficient relational processing engine with ease-to-use APIs and mid-query fault tolerance. It is a core module of Apache Spark, which is a unified engine for distributed data processing (Zaharia et al. 2012). Spark SQL can process, integrate, and analyze the data from diverse data sources (e.g., Hive, Cassandra, Kafka, and Oracle) and file formats (e.g., Parquet, ORC, CSV, and JSON). The common use cases include ad hoc analysis, logical warehouse, query federation, and ETL processing. It also powers the other Spark libraries, including structured streaming for stream processing, MLlib for machine learning (Meng et al. 2016; Michael et al. 2018), GraphFrame for graph-parallel computation (Dave et al. 2016), and TensorFrames for TensorFlow binding. These libraries and Spark SQL can be seamlessly combined in the same application with holistic optimization by Spark SQL.

Overview

Spark is a general purpose big data processing system. It was...

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References

  1. Armbrust M, Xin RS, Lian C, Huai Y, Liu D, Bradley JK, Meng X, Kaftan T, Franklin MJ, Ghodsi A, Zaharia M (2015) Spark SQL: relational data processing in spark. In: Proceedings of the ACM SIGMOD international conference on management of data (SIGMOD’15)Google Scholar
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  6. Xin RS, Rosen J, Zaharia M, Franklin MJ, Shenker S, Stoica I (2013) Shark: SQL and rich analytics at scale. In: Proceedings of the ACM SIGMOD workshop on the web and databases (SIGMOD’13)Google Scholar
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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Databricks Inc.San FranciscoUSA