March 2019
Beginner to intermediate
182 pages
4h 6m
English
Content preview from Hands-On Big Data Analytics with PySpark
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Using the Dataset API in an immutable way
In this section, we will use the Dataset API in an immutable way. We will cover the following topics:
- Dataset immutability
- Creating two leaves from the one root dataset
- Adding a new column by issuing transformation
The test case for the dataset is quite similar, but we need to do a toDS() for our data to be type safe. The type of dataset is userData, as shown in the following example:
import com.tomekl007.UserDataimport org.apache.spark.sql.SparkSessionimport org.scalatest.FunSuiteclass ImmutableDataSet extends FunSuite { val spark: SparkSession = SparkSession .builder().master("local[2]").getOrCreate()test("Should use immutable DF API") { import spark.sqlContext.implicits._ //given val userData ...Become 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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