December 2016
Beginner to intermediate
392 pages
8h 13m
English
Content preview from Apache Spark for Data Science CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Loading and saving data
This recipe shows how Spark supports a wide range of input and output sources. Spark makes it very simple to load and save data in a large number of file formats. Formats range from unstructured, such as text, to semi-structured, such as JSON, to structured, such as SequenceFiles.
Getting ready
To step through this recipe, you will need a running Spark cluster either in pseudo distributed mode or in one of the distributed modes, that is, standalone, YARN, or Mesos. Also, the reader is expected to have an understanding of text files, JSON, CSV, SequenceFiles, and object files.
How to do it…
- Load and save a text file as follows:
val input = sc.textFile("hdfs://namenodeHostName:8020/repos/spark/README.md") val wholeInput = sc.wholeTextFiles("file://home/padma/salesFiles") ...
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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.
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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.