March 2020
Beginner
380 pages
9h 44m
English
Content preview from Learning SQL, 3rd Edition
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Chapter 18. SQL and Big Data
While most of the content in this book covers the various features of the SQL language when using a relational database such as MySQL, the data landscape has changed quite a bit over the past decade, and SQL is changing to meet the needs of today’s rapidly evolving environments. Many organizations that had used relational databases exclusively just a few years ago are now also housing data in Hadoop clusters, data lakes, and NoSQL databases. At the same time, companies are struggling to find ways to gain insights from the ever-growing volumes of data, and the fact that this data is now spread across multiple data stores, perhaps both on-site and in the cloud, makes this a daunting task.
Because SQL is used by millions of people and has been integrated into thousands of applications, it makes sense to leverage SQL to harness this data and make it actionable. Over the past several years, a new breed of tools has emerged to enable SQL access to structured, semi-structured, and unstructured data: tools such as Presto, Apache Drill, and Toad Data Point. This chapter explores one of these tools, Apache Drill, to demonstrate how data in different formats and stored on different servers can be brought together for reporting and analysis.
Introduction to Apache Drill
There have been numerous tools and interfaces developed to allow SQL access to data stored in Hadoop, NoSQL, Spark, and cloud-based distributed filesystems. Examples include Hive, ...
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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.