Hi Gijs,
> I have been trying different approaches to achieve this by using a custom map
> and reduce function.
My rule of thumb is to avoid custom reduce functions at all cost.
Maybe it's a bit harsh but it saved me a lot of time and frustration.
>>> Now i want to do very mailchimp/campaignmonitor like summary per campaign
>>> (key[3}) that show nr of unique delivers, nr of unique opens, nr of unique
>>> clicks.
> SELECT count(*) FROM events WHERE type='click' GROUP BY contact_id;
> But i want the single view to output both the unique clicks, views and opens
First, you should emit the following keys (in this order, with no value):
[campaign, type, contact_id]
Then you can reduce those data (with any builtin reduce function, `_count` for
example) and `group=true` (which is shorter than
`reduce=true&group_level=exact`).
Then you'll need an other computation round to count unique contacts (per
campaign and type). While waiting for chained map-reduce (coming soon I hope),
you can cheat and do it with a list.
With a list, it is usually a good idea to send the results as soon as you know
them (i.e., in this case, when there is a new `type` in the current row or when
there are no rows anymore).
Regards,
Aurélien
