Understanding Spark MLlib ALS.trainImplicit input format
<p>I`m trying to make a recommender system based on purchase history using trainImplicit. My input is in domain [1, +inf) (the sum of views and purchases). </p>

<p>So the element of my input RDD looks like this: <code>[(user_id,item_id),rating] --&gt; [(123,5564),6]</code> - the user(id = 123) interacted with the item(id=5564) 6 times.</p>

<p>Should I add to my RDD elements such as <code>[(user_id,item_id),rating] --&gt; [(123,2222),0]</code>, meaning that given user has never interacted with given item or the ALS.implicitTrain does this implicitly?</p>