The standard way that we indicate that there are more results than can
be returned is by paginating. So even though we don’t intend to paginate
the search results in the admin app, it can still use the presence or
absence of a ‘next’ link to determine whether or not to show a message
about only showing the first 50 results.
We were doing this temporarily while the `normalised_to` field was not
populated for letters. Once we have a week of data in the
`normalised_to` field we can stop looking in the `to` field. This should
improve performance because:
- it’s one `WHERE` clause not two
- we had to do `ilike` on the `to` field, because we don’t lowercase its
contents – even if the two where clauses are somehow paralleized it’s
is slower than a `like` comparison, which is case-sensitive
Depends on:
- [ ] Tuesday 5 May (7 full days after deploying https://github.com/alphagov/notifications-api/pull/2814)
Like we have search by email address or phone number, finding an
individual letter is a common task. At the moment users are having to
click through pages and pages of letters to find the one they’re looking
for.
We have to search in the `to` and `normalised_to` fields for now because
we’re not populating the `normalised_to` column for letters at the
moment.
It is possible a service has data rention that is smaller than the time it takes to get a delivery receipt.
This PR refactors process_ses_receipt to update NotificationHistory if the Notifcation has already been purged.
- fix test name
- make query filter consistent with each other
- add comment for clarity
- add inner loop to continue to insert and delete notifications while the delete count is greater than 0
The insert_notification_history_delete_notifications function uses a temp table to store the data to insert and delete. This will save extra queries while performing the insert and delete operations.
The function is written in such a way that if the task is stop while processing when it's started up again it will just pick up where it left off.
I've made a decision to delete all test data in one query, I don't anticipate a problem with that.
The performance of this might also be better than last nights test because we are inserting everything we need for the NotificationHistory insert, so we don't need the join to Notifications to perform the insert.
Need to test the performance of this function, then we can call it from the task.
- Create a temporary table to insert ids of the desired rows, limit by 10K (might be too low).
- Insert into NotifcationHistory select from notification where id in temp table
- Delete from Notifications where id in temp table
- drop temp table
We should be able to iterate of this. The query stats for the query to create the temp table are very good, 17ms.
The date in the notifications table should always be the most recent date for the template.
Removed the template_type param for the query as well.
Simplified the tests.
The existing endpoint returned a whole notification for the last time the template was used. But this only takes into account data in the last week. This new methods allows us to be specific about when the template was last used if ever but looking into the ft_notification_status table as well.
Before the search term was either:
- an email address (or partial email address)
- a phone number (or partial phone number)
Now it can also be:
- a reference (or partial reference)
We can take a pretty good guess, by looking at the search term, whether
the thing the user is searching by email address or phone number. This
helps us:
- only show relevant notifications
- normalise the search term to give the best chance of matching what we
store in the `normalised_to` field
However we can’t look at a search term and guess whether it’s a
reference, because a reference could take any format. Therefore if the
user hasn’t told us what kind of thing their search term is, we should
stop trying to guess.
We have a team who want to find emails that might have been sent to an
incorrect address. Therefore they can’t search by the correct address,
because it won’t match.
What they do have is the reference number of the user’s application,
which is also stored in the `client_reference` field on the
notification.
So when a user is searching we should also look at the client reference,
as well as the recipient, allowing the user to enter either in the
search box.
The nightly job to delete email notifications was failing because it was
timing out (`psycopg2.errors.QueryCanceled: canceling statement due to statement timeout`).
This adds a query limit to the query which inserts or updates
notification history so that it only updates a maximum of 10000 rows at
a time.
All our endpoint should perform a check that the params are valid - this is an easy whay to check that and is standard for our endpoints.
I reverted the query to just filter by job id.
Now we consistently use the created_at date, so we can always get the right file location and name.
The previous updates to this code were trying to solve the problem if a pdf being created at 17:29, but not ready to upload until 17:31 after the antivirus and validation check.
But in those cases we would have trouble finding the file.
When we cancel a job, we need to check if all notifications are
already in the database. So far, we were querying for all
notification objects in the database and counting them in
admin app, which runs into pagination problems for large jobs,
and could time out for very large jobs.
* remove unnecessary parametrisation where we're not testing
type-specific things
* remove some unused fixtures
* replace len(x.all()) with x.count()
* don't deleted notificationhistory now that we know it's not written
* remove some pre-test function asserts
re-order notification dao delete notifications test to move "fixtures"
to the top of the file
changed create_service_data_retention to take an ORM object, not an id.
brings it in line with other db.py test functions
Update subquery to run again but for test keys. Test data is never inserted in Notifications so they need to be deleted separately now given the join to NotificationHistory.
This PR adds a function to upsert (insert or update if exists) NotificationHistory all the rows from Notification that we are about to delete in the nightly task. This will happen just before the delete function. Since it is a upsert query the function can be called more than once.
This should allow us remove all the insert/updates to NotificationHistory.
However, there is a consern that this will double the length of time the tasks take. So do we do these upserts in a separate task or in the same one?
Currently we switch if:
* status = delivered and updated_at - sent_at > threshold
* status = sending and now - sent_at > threshold
firetext can leave notifications in the pending state, which is
equivalent to sending in terms of how we should handle it, so this
commit changes the second case to allow pending as well as sending.
Flask-SQLAlchemy paginate function issues a separate query to get
the total count of rows for a given filter. This query (with
filters used by the API integration Message log page) is slow for
services with large number of notifications.
Since Message log page doesn't actually allow users to paginate
through the response (it only shows the last 50 messages) we can
use limit instead of paginate, which requires passing in another
flag from admin to the dao method.
`count` flag has been added to `paginate` in March 2018, however
there was no release of flask-sqlalchemy since then, so we need
to pull the dev version of the package from Github.
