September 2016
Beginner to intermediate
326 pages
6h 47m
English
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Introducing SQL, Datasources, DataFrame, and Dataset APIs
Let's understand four components in Spark SQL—SQL, the Data Sources API, the DataFrame API, and the Dataset API.
Spark SQL can write and read data to and from Hive tables using the SQL language. SQL can be used within Java, Scala, Python, R languages, over JDBC/ODBC, or using the command-line option. When SQL is used in programming languages, the results will be converted as DataFrames.
Advantages of SQL are:
- Can work with Hive tables easily
- Can connect BI tools to a distributed SQL engine using Thrift Server and submit SQL or Hive QL queries using JDBC or ODBC interfaces
The Data Sources API provides a single interface for reading and writing data using Spark SQL. In addition to the in-built ...
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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.