previously we checked notifications table, and if the results were
zero, checked the notification history table to see if there's data
in there. When we know that data isn't in notifications, we're still
checking. These queries take half a second per service, and we're
doing at least ten for each of the five thousand services we have in
notify. Most of these services have no data in either table for any
given day, and we can reduce the amount of queries we do by only
checking one table.
Check the data retention for a service, and then if the date is older
than the retention, get from history table.
NOTE: This requires that the delete tasks haven't run yet for the day!
If your retention is three days, this will look in the Notification
table for data from three days ago - expecting that shortly after the
task finishes, we'll delete that data.
The group by for the query was wrong which would result in 2 rows with different totals but the same unique key, so the second row would update the first row. Meaning we had incorrect numbers for the billing data.
Because some of the data had null for the sent_by column, the select would turn the Null --> dvla, but that same function was not used in the group by. So any time we had missing sent_by data we would end up with 2 rows where one would overwrite the other.
bst_date is a date field. Comparing dates with datetimes in postgres
gets confusing and dangerous. See this example, where a date evaluates
as older than midnight that same day.
```
notification_api=# select '2019-04-01' >= '2019-04-01 00:00';
?column?
----------
f
(1 row)
```
By only using dates everywhere, we reduce the chance of these bugs
happening
from service, join organisation, the free_allowance_remainder subquery
and the ft_billing table. Being explicit reduces confusion about what
tables we're joining and how we're constraining those joins
also remove references to AnnualBilling since we've already got the
free sms allowance from the free_allowance_remainder subquery
if there are no rows for a service in ft_billing, we should still
return their allowance (with 0 fragments used).
To do this, we need to build the query starting from AnnualBilling and
joining onto FactBilling, rather than the other way round. Also, we
need to account for the possibility of the sums being null by
coalescing them to 0
This PR updates those queries to look in either Notification or NotificationHistory. Since the data does not exist in both tables at the same time we can do with and not worry about the data retention.
The query will iterate over each service, then each notification type and query the data if no results then try the history table.
the create_nightly_notification_status task runs at 00:30am UK time,
however this means that in summer datetime.today() will return the
wrong date as the server (which runs on UTC) will run the task at
23:30 (populating the wrong row in the table).
fix this to use nice tz aware functions
Bumped notifications-utils to 3.7.0. Version 3.7.0 includes the
`convert_utc_to_bst` and `convert_bst_to_utc` functions and the
`LETTER_PROCESSING_DEADLINE` constant, so these have been removed from
this repo and anywhere using these has now been updated to get these
from `notifications-utils`.
Also bumped pytest by a patch version to bring in a bug fix.
We were already returning the month, notification_type, billing_units
and rate from the /monthly-usage billing endpoint. This adds in the
postage too so that we can display postage details on the usage page of
admin.
* Changed update_fact_billing DAO function to update the table with the
real data for postage instead of hard-coding in 'second'.
* Added a test for the create nightly billing task to test that rows
with different postage are being inserted correctly.
* Updated the 'fetch_billing_data_for_day' DAO function to take postage into
account
* Updated the 'update_fact_billing' DAO function to insert postage for
new rows. When updating rows which are identical apart from the postage, the
original row will be kept. (This behaviour will change once postage is
added to the primary key - at this point, upserting will add a new row.)
* Also changed some fixtures / test set up functions to take postage
into account
if the billing data was incorrect and needs to be rebuilt, we should
remove old rows. Previously we were only upserting new rows, but old
no-longer-relevant rows were staying in the database. This commit
makes the flask command remove *all* rows for that service and day,
before inserting the rows from the original notification data after.
This commit doesn't change the existing nightly task, nor does it
change the upsert that happens upon viewing the usage page. In normal
usage, there should never be a case where the number of billable units
for a rate decreases. It should only ever increase, thus, never need to
be deleted
`created_at` was added previously and made nullable temporarily. This
commit now populates the column, ensures that it will always have a
value, and makes `created_at` non-nullable.
Update test_provider_statistics dao - this is really irrelevant since the endpoint using the query is not being used. We have a PR coming to delete the unused code.
Update rate_multiplier to always be an integer
- Change the usage queries to a union so that billing_units is correct for all notification types. Removing the business logic from the schema.
- Added tests for different fragment counts, rates and sheet counts.
This was because the rate_multiplier was being added as 1 and 1.0 which was not resolving to the same.
This updates the table to use Integrer.
Also changed the logging for the task.
