lsandrade / basic-transformations Goto Github PK

Work through the katas in this codebase to learn basic transformations, transformations on a single dataframe/dataset, with Spark + Scala.

• count number of records
• remove duplicates
• calculate average price
• calculate min and max price
• filter flawless diamonds
• groupBy clarity and calculate average price
• Add column "grade" with computation based on cut and clarity
• drop a column

Dataset: src/main/resources/diamonds.csv

Metadata: (Ref: https://www.kaggle.com/shivam2503/diamonds)

Column   Description

1. index: counter
2. carat: Carat weight of the diamond
3. cut: Describe cut quality of the diamond. Quality in increasing order Fair, Good, Very Good, Premium, Ideal
4. color: Color of the diamond, with D being the best and J the worst
5. clarity: How obvious inclusions are within the diamond:(in order from best to worst, FL = flawless, I3= level 3 inclusions) FL,IF, VVS1, VVS2, VS1, VS2, SI1, SI2, I1, I2, I3
6. depth: depth % :The height of a diamond, measured from the culet to the table, divided by its average girdle diameter
7. table: table%: The width of the diamond's table expressed as a percentage of its average diameter
8. price: the price of the diamond
9. x: length mm
10. y: width mm
11. z: depth mm

• Set main class as org.apache.spark.deploy.SparkSubmit
• Set program arguments as --master local --class<main_class> target/scala-2.12/<jar_name>