November 2021
Intermediate to advanced
340 pages
10h 46m
Chinese
Content preview from Spark快速大数据分析（第2版）
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100
第 5 章
Spark SQL
与
DataFrame
：
读写外部数据源
第
4
章探索了
Spark
内建数据源的交互方式。我们还深入了解了
DataFrame API
及其与
Spark SQL
的互操作能力
。本章会关注
Spark SQL
如何与外部组件连接。具体地说，我们
将讨论
Spark SQL
如何实现下列功能。
•
使用
Hive
和
Spark
的用户自定义函数。
•
连接外部数据源，比如
JDBC
和
SQL
数据库
、
PostgreSQL
、
MySQL
、
Azure Cosmos
DB
，以及微软的
SQL
Server
等。
•
使用简单类型和复杂类型、高阶函数，以及常用的关系型算子。
我们还会讨论使用
Spark SQL
查
询
Spark
的各种方式，比如
Spark SQL shell
、
Beeline
和
T
ableau
。
5.1
Spark SQL
与
Apache Hive
Spark SQL
是
Spark
的基础组件，它将关系型处理与
Spark
的函数式编程
API
结合起来。
Spark SQL
起源于早前的
Shark
项
目。
Shark
依赖
Hive
的代码，在
Spark
1
之上实现，是
Hadoop
生态系统中最早的交互式
SQL
查询引擎之一
。
Shark
证明了鱼和熊掌是可以兼得
注
1
：
目前的
Spark SQL
引擎在实现中不再使用
Hive
代码。
Spark SQL ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.