1)Storm and kafka 2)Spark streaming and structured streaming 3)Spark rdd dataframe and dataset 4)Partitioning and bucketing scenarios 5)Sql functions practice 6)Test cases 7)Spark hive context and sql context and spark session difference 8)Data modeling for bigdata 9)Dimension table and fact tables 10)Data crunching 11)Webservices and microservices applications 12)1000 files with particular set of id store id columns and final outcome should be like 13)count of stores for repeating id 14)So id and stores are repeating g 15)How to deal with 1000 files 16)How sql query steps works 17)Algorithm with spark program 18)How will it check job dependency first completes then only completes second one 19)Oozie scheduler 20)Lookinto titan glm code and spark functions
