Get up to speed with Presto, the open-source SQL query engine developed by Facebook. Learn the key concepts of Presto and how to use them to take full advantage of your modern big data system.
- [Ben] Working with data in Hadoop has been a challenge since the beginning. In 2008, Facebook gave us Hive, which allowed our analysts and our data scientists to use a language they're familiar with, SQL. But it had its own challenges in that it was still dependent upon MapReduce. In 2013, Facebook gave us another big step forward in working with data in Hadoop in Presto. Now this platform, in my opinion, is the evolution of SQL on Hadoop and is likely going to change how you're going to look at your analysis workflow.
Hi, I'm Ben Sullins, and in this course, we're going to take a look at how to use Presto for data science. I'll start by showing you how all the pieces fit together, and then we'll use the different interfaces with Presto, such as R and Tableau. We'll finish by digging into the expressive SQL language that Presto offers us for our analysis. We'll be covering all of these topics to get you up to speed with Presto and delivering high quality data to your users. Let's dive in.
Data science expert Ben Sullins helps you get up to speed with Presto, and leverage it to accomplish a wide-range of data science and analytics tasks. He uses different interfaces with Presto—such as R and Tableau—and digs into the expressive SQL language that Presto offers for your analysis. At the end of this course, you'll know the key concepts of Presto and how to use them to take full advantage of your modern big data system.
- What does Presto do?
- Running Presto
- Connecting from Tableau and R
- Connecting to Hive, MySQL, and the local system
- Retrieving data
- Combining data sources
- Basic SQL functions
- Advanced SQL functions
- Migrating from Hive