September 2018
Intermediate to advanced
398 pages
9h 43m
English
Content preview from Scala Programming Projects
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Dataframe
Spark SQL is composed of three main APIs:
- The SQL literal syntax
- The DataFrame API
- DataSet
DataFrame is conceptually the same as a table in the relational database. The data is distributed in the same way as in an RDD. DataFrame has a schema but is untyped. You can create DataFrame from an RDD or manually build it. Once created, DataFrame will contain a schema that maintains the name and type for each column (field).
If you then want to use DataFrame in an SQL query, all you need to do is create a named view (equivalent to the table name in the relational database) using the Dataframe.createTempView(viewName: String) method. In the SQL query, the fields that are available in the SELECT statement will come from the schema of
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.