Designing Smart Notification of Stock Price Changes

5330 2019-08-13 12:21

Requirements

  • 3 million users
  • 5000 stocks + 250 global stocks
  • a user gets notified about the price change when
    1. subscribing the stock
    2. the stock has 5% or 10% changes
    3. since a) the last week or b) the last day
  • extensibility. may support other kinds of notifications like breaking news, earnings call, etc.

Sketching out the Architecture

Contexts:

  • What is clearing? Clearing is the procedure by which financial trades settle – that is, the correct and timely transfer of funds to the seller and securities to the buyer. Often with clearing, a specialized organization acts as an intermediary known as a clearinghouse.
  • What is a stock exchange? A facility where stock brokers and traders can buy and sell securities.

Apple Push Notification service
(APNs)
Apple Push Notification service<br>(APNs)
Google Firebase Cloud Messaging
(FCM)
Google Firebase Cloud Messaging<br>(FCM)
Email Services
AWS SES /sendgrid/etc
Email Services<br>AWS SES /sendgrid/etc
notifier
notifier
External Vendors

Market Prices
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Robinhood App
Robinhood App
API Gateway
API Gateway
Reverse Proxy
Reverse Proxy
batch write
batch write
price
ticker
[Not supported by viewer]
Time-series DB
influx or prometheus
Time-series DB<br>influx or prometheus
Tick every 5 mins
[Not supported by viewer]
periorical read
periorical read
price
watcher
price<br>watcher
User Settings
User Settings
Notification Queue
Notification Queue
throttler cache
throttler cache
cronjob
cronjob

What are those components and how do they interact with each other?

  • Price ticker
    • data fetching policies
      • option 1 preliminary: fetches data every 5 mins and flush into the time-series database in batches.
      • option 2 advanced: nowadays external systems usually push data directly so that we do not have to pull all the time.
    • ~6000 points per request or per price change.
    • data retention of 1 week, because this is just the speeding layer of the lambda architecture.
  • Price watcher
    • read the data ranging from last week or last 24 hours for each stock.
    • calculate if the fluctuation exceeds 5% or 10% in those two time spans. we get tuples like (stock, up 5%, 1 week).
      • corner case: should we normalize the price data? for example, some abnormal price like someone sold UBER mistakenly for $1 USD.
    • ratelimit (because 5% or 10% delta may occur many times within one day), and then emit an event PRICE_CHANGE(STOCK_CODE, timeSpan, percentage) to the notification queue.
  • Periodical triggers are cron jobs, e.g. Airflow, Cadence.
  • notification queue
    • may not necessarily be introduced in the first place when users and stocks are small.
    • may accept generic messaging event, like PRICE_CHANGE, EARNINGS_CALL, BREAKING_NEWS, etc.
  • Notifier
    • subscribe the notification queue to get the event
    • and then fetch who to notify from the user settings service
    • finally based on user settings, send out messages through APNs, FCM or AWS SES.

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