Univariate analysis
Once the data is available, we have to spend lot of time and effort in data exploration, cleaning and preparation because the quality of the high input data decides the quality of calculating the output. Hence, once we identify the business questions, the first step of data exploration/analysis is univariate analysis, which explores the variables one by one. The methods of univariate analysis depend on whether the variable type is categorical or continuous.
Getting ready
To step through this recipe, you will need a running Spark cluster in any one of the modes, that is, local, standalone, YARN, or Mesos. For installing Spark on a standalone cluster, please refer to http://spark.apache.org/docs/latest/spark-standalone.html. Also, include the Spark MLlib package in the build.sbt file so that it downloads the related libraries and the API can be used. Install Hadoop (optionally), Scala, and Java.
How to do it…
Let's take the example of
Titanicdataset. On April 15, 1912, the...
