Spark Fundamentals Week

match_details
- a row for every players performance in a match
matches
- a row for every match
medals_matches_players
- a row for every medal type a player gets in a match
medals
- a row for every medal type

Your goal is to make the following things happen:

Build a Spark job that
- Disabled automatic broadcast join with spark.conf.set("spark.sql.autoBroadcastJoinThreshold", "-1")
- Explicitly broadcast JOINs medals and maps
- Bucket join match_details, matches, and medal_matches_players on match_id with 16 buckets
- Aggregate the joined data frame to figure out questions like:
  - Which player averages the most kills per game?
  - Which playlist gets played the most?
  - Which map gets played the most?
  - Which map do players get the most Killing Spree medals on?
- With the aggregated data set
  - Try different .sortWithinPartitions to see which has the smallest data size (hint: playlists and maps are both very low cardinality)

Save these as .py files and submit them this way!