February 2018
Intermediate to advanced
606 pages
14h 54m
English
Content preview from Spark: The Definitive Guide
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Chapter 10. Spark SQL
Spark SQL is arguably one of the most important and powerful features in Spark. This chapter introduces the core concepts in Spark SQL that you need to understand. This chapter will not rewrite the ANSI-SQL specification or enumerate every single kind of SQL expression. If you read any other parts of this book, you will notice that we try to include SQL code wherever we include DataFrame code to make it easy to cross-reference with code samples. Other examples are available in the appendix and reference sections.
In a nutshell, with Spark SQL you can run SQL queries against views or tables organized into databases. You also can use system functions or define user functions and analyze query plans in order to optimize their workloads. This integrates directly into the DataFrame and Dataset API, and as we saw in previous chapters, you can choose to express some of your data manipulations in SQL and others in DataFrames and they will compile to the same underlying code.
What Is SQL?
SQL or Structured Query Language is a domain-specific language for expressing relational operations over data. It is used in all relational databases, and many “NoSQL” databases create their SQL dialect in order to make working with their databases easier. SQL is everywhere, and even though tech pundits prophesized its death, it is an extremely resilient data tool that many businesses depend on. Spark implements a subset of ANSI SQL:2003. This SQL standard is one that is available ...
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