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.classification. {BinaryLogisticRegressionSummary, LogisticRegression} scala> import org.apache.spark.ml.linalg.{Vector, Vectors}
- Create a dataset with either the presence or absence of spiders as the label:
scala> val trainingDataSet = spark.createDataFrame(Seq( (0.0,Vectors.dense(0.245)), (0.0,Vectors.dense(0.247)), (1.0,Vectors.dense(0.285)), (1.0,Vectors.dense(0.299)), (1.0,Vectors.dense(0.327)), (1.0,Vectors.dense(0.347)), (0.0,Vectors.dense(0.356)), (1.0,Vectors.dense(0.36)), (0.0,Vectors.dense(0.363)), (1.0,Vectors.dense(0.364)), (0.0,Vectors.dense(0.398)), (1.0,Vectors.dense(0.4)), (0.0,Vectors.dense(0.409)), ...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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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.