I have a large data set with millions of records which is something like Movie Likes Comments Shares Views A 100 10 20 30 A 102 11 22 35 A 104 12 25 45 A *103* 13 *24* 50 B 200 10 20 30 B 205 *9* 21 35 B *203* 12 29 42 B 210 13 *23* *39*
Likes, comments etc are rolling totals and they are suppose to increase. If there is drop in any of this for a movie then its a bad data needs to be identified. I have initial thoughts about groupby movie and then sort within the group. I am using dataframes in spark 1.6 for processing and it does not seem to be achievable as there is no sorting within the grouped data in dataframe. Buidling something for outlier detection can be another approach but because of time constraint I have not explored it yet. Is there anyway I can achieve this ? Thanks !!
