Hi, I'm just a new one in the world big data and I'm trying understand the use cases of several projects. Of course one of them is Spark.
I wanna know that what is the proper way of examining my data that resides on my MySQL server? Think that I'm saving every page view of a user with the timestamp in a table called "views" (id, user_id, page, created_at). Let's assume there are millions of rows in this table. In the Spark examples, there are some text files which are analysed. So in the case of data that resides in MySQL, what should be my approach? By analysing the data, you can think of generating page recommendations for similar users. Thanks, -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Understanding-Spark-tp10373.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
