May 2017
Intermediate to advanced
294 pages
7h 33m
English
Content preview from Apache Spark 2.x Cookbook
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How to do it...
- Start the Spark shell:
$ spark-shell
- Create a DataFrame of house price and size:
scala> val houses = spark.createDataFrame(Seq( (1620000d,2100), (1690000d,2300), (1400000d,2046), (2000000d,4314), (1060000d,1244), (3830000d,4608), (1230000d,2173), (2400000d,2750), (3380000d,4010), (1480000d,1959) )).toDF("price","size")
- Compute the correlation:
scala> houses.stat.corr("price","size") correlation: Double = 0.8577177736252574
Since we do not have a specific algorithm here, it is, by default, Pearson. The corr method is overloaded to take the algorithm name as the third parameter. 0.85 means a very strong positive correlation.
- Compute the correlation with Pearson passed explicitly as a parameter:
scala> houses.stat.corr("price","size","pearson") ...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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