YouTube video analysis based on datasets on Kaggle
spark-shell -i file.scala
:load file.scala
- setup.scala - initial setup. Read from csv and clean date
- saveToParquet.scala - save RDD to Parquet. Assume Parquet is created with Hive.
CREATE EXTERNAL TABLE videos(video_id STRING, trending_date STRING, title STRING, channel_title STRING, category_id STRING, publish_time STRING, tags STRING, views INT, likes INT, dislikes INT, comment_count INT, thumbnail_link STRING, comments_disabled BOOLEAN, ratings_disabled BOOLEAN, video_error_removed BOOLEAN, description STRING) STORED AS PARQUET LOCATION '/user/cloudera/labs';
- readFromParquet.scala - read from Parquet after saved
- trending.scala - Video Trending analysis