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
- Import the statistics and related classes:
scala> import org.apache.spark.ml.linalg.Vectorsscala> import org.apache.spark.ml.regression.LinearRegression
- Create a DataFrame with the house price as the label:
scala> val points = spark.createDataFrame(Seq( (1620000,Vectors.dense(2100)), (1690000,Vectors.dense(2300)), (1400000,Vectors.dense(2046)), (2000000,Vectors.dense(4314)), (1060000,Vectors.dense(1244)), (3830000,Vectors.dense(4608)), (1230000,Vectors.dense(2173)), (2400000,Vectors.dense(2750)), (3380000,Vectors.dense(4010)), (1480000,Vectors.dense(1959)) )).toDF("label","features")
- Initialize linear regression:
scala> val lr = new LinearRegression()
- Train a model using ...
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