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
- Do the required imports:
scala> import org.apache.spark.mllib.util.MLUtils scala> import org.apache.spark.mllib.classification.SVMWithSGD
- Load the data as an RDD:
scala> val data = MLUtils.loadLibSVMFile(sc,"s3a://sparkcookbook /medicaldata/diabetes.libsvm")
- Count the number of records:
scala> data.count
- Divide the dataset into equal halves of training data and testing data:
scala> val trainingAndTest = data.randomSplit(Array(0.5,0.5))
- Assign the training and test data:
scala> val trainingData = trainingAndTest(0)scala> val testData = trainingAndTest(1)
- Train the algorithm and build the model for 100 iterations (you can try different iterations, but at a certain ...
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