April 2017
Intermediate to advanced
532 pages
12h 39m
English
book
Machine Learning with Spark - Second Edition
by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
Content preview from Machine Learning with Spark - Second Edition
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SparkSession
SparkSession allows programming with the DataFrame and Dataset APIs. It is a single point of entry for these APIs.
First, we need to create an instance of the SparkConf class and use it to create the SparkSession instance. Consider the following example:
val spConfig = (new SparkConf).setMaster("local").setAppName("SparkApp") val spark = SparkSession .builder() .appName("SparkUserData").config(spConfig) .getOrCreate()
Next we can use spark object to create a DataFrame:
val user_df = spark.read.format("com.databricks.spark.csv") .option("delimiter", "|").schema(customSchema) .load("/home/ubuntu/work/ml-resources/spark-ml/data/ml-100k/u.user")val first = user_df.first()
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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.