By changing the created_at filter to use a specific date range I found a significant improvement to the queries performance. The unit test needed to change because now were are returning todays date as BST the local timezone. Query plan before Merge Left Join (cost=1226133.76..1226143.77 rows=1753 width=70) (actual time=5800.160..5801.657 rows=1849 loops=1) Merge Cond: (services.id = anon_1.service_id) -> Sort (cost=152.99..157.37 rows=1753 width=46) (actual time=2.205..2.631 rows=1762 loops=1) Sort Key: services.id Sort Method: quicksort Memory: 224kB -> Seq Scan on services (cost=0.00..58.54 rows=1753 width=46) (actual time=0.011..1.156 rows=1762 loops=1) Filter: active Rows Removed by Filter: 101 -> Sort (cost=1225980.77..1225980.99 rows=86 width=40) (actual time=5797.949..5797.984 rows=198 loops=1) Sort Key: anon_1.service_id Sort Method: quicksort Memory: 40kB -> Subquery Scan on anon_1 (cost=1225976.29..1225978.01 rows=86 width=40) (actual time=5797.682..5797.823 rows=198 loops=1) -> HashAggregate (cost=1225976.29..1225977.15 rows=86 width=48) (actual time=5797.681..5797.747 rows=198 loops=1) Group Key: notifications.notification_type, notifications.notification_status, notifications.service_id -> Seq Scan on notifications (cost=0.00..1220610.86 rows=536543 width=48) (actual time=0.064..5482.975 rows=643799 loops=1) Filter: (((key_type)::text <> 'TEST'::text) AND (date(created_at) = '2018-03-20'::date)) Rows Removed by Filter: 6804774 Planning time: 1.106 ms Execution time: 5802.130 ms Query plan after Merge Left Join (cost=953378.30..953388.30 rows=1753 width=70) (actual time=2380.144..2382.499 rows=1852 loops=1) Merge Cond: (services.id = anon_1.service_id) -> Sort (cost=152.99..157.37 rows=1753 width=46) (actual time=2.944..3.570 rows=1762 loops=1) Sort Key: services.id Sort Method: quicksort Memory: 224kB -> Seq Scan on services (cost=0.00..58.54 rows=1753 width=46) (actual time=0.006..1.294 rows=1762 loops=1) Filter: active Rows Removed by Filter: 101 -> Sort (cost=953225.31..953225.53 rows=86 width=40) (actual time=2377.194..2377.262 rows=201 loops=1) Sort Key: anon_1.service_id Sort Method: quicksort Memory: 40kB -> Subquery Scan on anon_1 (cost=953220.83..953222.55 rows=86 width=40) (actual time=2376.797..2377.034 rows=201 loops=1) -> HashAggregate (cost=953220.83..953221.69 rows=86 width=48) (actual time=2376.795..2376.905 rows=201 loops=1) Group Key: notifications.notification_type, notifications.notification_status, notifications.service_id -> Bitmap Heap Scan on notifications (cost=29883.14..947856.24 rows=536459 width=48) (actual time=270.061..1887.754 rows=644735 loops=1) Recheck Cond: ((created_at >= '2018-03-20 00:00:00'::timestamp without time zone) AND (created_at < '2018-03-21 00:00:00'::timestamp without time zone)) Rows Removed by Index Recheck: 947427 Filter: ((key_type)::text <> 'TEST'::text) Heap Blocks: exact=40882 lossy=186483 -> Bitmap Index Scan on ix_notifications_created_at (cost=0.00..29749.02 rows=536459 width=0) (actual time=258.631..258.631 rows=644849 loops=1) Index Cond: ((created_at >= '2018-03-20 00:00:00'::timestamp without time zone) AND (created_at < '2018-03-21 00:00:00'::timestamp without time zone)) Planning time: 0.548 ms Execution time: 2383.485 ms
notifications-api
Notifications api Application for the notification api.
Read and write notifications/status queue. Get and update notification status.
Setting Up
AWS credentials
To run the API you will need appropriate AWS credentials. You should receive these from whoever administrates your AWS account. Make sure you've got both an access key id and a secret access key.
Your aws credentials should be stored in a folder located at ~/.aws. Follow Amazon's instructions for storing them correctly.
### Virtualenv
mkvirtualenv -p /usr/local/bin/python3 notifications-api
### environment.sh
Creating the environment.sh file. Replace [unique-to-environment] with your something unique to the environment. Your AWS credentials should be set up for notify-tools (the development/CI AWS account).
Create a local environment.sh file containing the following:
echo "
export NOTIFY_ENVIRONMENT='development'
export MMG_API_KEY='MMG_API_KEY'
export LOADTESTING_API_KEY='FIRETEXT_SIMULATION_KEY'
export FIRETEXT_API_KEY='FIRETEXT_ACTUAL_KEY'
export NOTIFICATION_QUEUE_PREFIX='YOUR_OWN_PREFIX'
export FLASK_APP=application.py
export FLASK_DEBUG=1
export WERKZEUG_DEBUG_PIN=off
"> environment.sh
NOTES:
- Replace the placeholder key and prefix values as appropriate
- The SECRET_KEY and DANGEROUS_SALT should match those in the notifications-admin app.
- The unique prefix for the queue names prevents clashing with others' queues in shared amazon environment and enables filtering by queue name in the SQS interface.
Postgres
Install Postgres.app. You will need admin on your machine to do this.
Redis
To switch redis on you'll need to install it locally. On a OSX we've used brew for this. To use redis caching you need to switch it on by changing the config for development:
REDIS_ENABLED = True
To run the application
First, run scripts/bootstrap.sh to install dependencies and create the databases.
You need to run the api application and a local celery instance.
There are two run scripts for running all the necessary parts.
scripts/run_app.sh
scripts/run_celery.sh
Optionally you can also run this script to run the scheduled tasks:
scripts/run_celery_beat.sh
To test the application
First, ensure that scripts/bootstrap.sh has been run, as it creates the test database.
Then simply run
make test
That will run flake8 for code analysis and our unit test suite. If you wish to run our functional tests, instructions can be found in the notifications-functional-tests repository.
To run one off tasks
Tasks are run through the flask command - run flask --help for more information. There are two sections we need to
care about: flask db contains alembic migration commands, and flask command contains all of our custom commands. For
example, to purge all dynamically generated functional test data, do the following:
Locally
flask command purge_functional_test_data -u <functional tests user name prefix>
On the server
cf run-task notify-api "flask command purge_functional_test_data -u <functional tests user name prefix>"
All commands and command options have a --help command if you need more information.
To create a new worker app
You need to:
- Create a new entry for your app in manifest-delivery-base.yml (example)
- Update the jenkins deployment job in the notifications-aws repo (example)
- Add the new worker's log group to the list of logs groups we get alerts about and we ship them to kibana (example)
- Optionally add it to the autoscaler (example)
Important:
Before pushing the deployment change on jenkins, read below about the first time deployment.
First time deployment of your new worker
Our deployment flow requires that the app is present in order to proceed with the deployment.
This means that the first deployment of your app must happen manually.
To do this:
- Ensure your code is backwards compatible
- From the root of this repo run
CF_APP=<APP_NAME> make <cf-space> cf-push
Once this is done, you can push your deployment changes to jenkins to have your app deployed on every deployment.