When we explore precomputed aggregate data storage, let's focus on the first question posed above: how many total views did status updates receive on each day of September?

More generally, we want to store the daily overall view counts in a structure that allows us to easily retrieve the counts for a given range of time. We don't need to store discrete information about every view event that happened; simply knowing how many views occurred per day is sufficient.

Let's create a new daily_status_update_views table that aggregates our analytics observations at just the right granularity:

CREATE TABLE "daily_status_update_views" (
  "year" int,
  "date" timestamp,
  "total_views" counter,
  "web_views" counter,
  "mobile_views" counter,
  "api_views" counter,
  PRIMARY KEY (("year"), "date")
);

Of course, the most striking thing about this table definition is the introduction of the counter column type; we'll dive into this a little later in this chapter...