Scheduled, asynchronous JSON fetching for Node.js applications. Background;
npm install ft-poller
You can create an instance of Poller like so,
var Poller = require('ft-poller');
var p = new Poller(config);
Where config
is an object with the following properties
url
[required]: Url to fetch data fromdefaultData
[recommended]: Data to return if the poller is yet to make a successful request. Typically this will be an empty object of the same type/structure as a successful response e.g. if a successful response would give you an array of users then setdefaultData: []
options
[optional]: options object to pass to isomorphic-fetch. If options is not defined or doesn't contain atimeout
property, request timeout will be set to 4000ms by default. Ifretry
is specified then n-eager-fetch is used to send the request instead of fetchrefreshInterval
[default: 60000]: Number of milliseconds to wait between request for dataautostart
[default: false]: Whether to start the poller automatically when the instance is createdparseData
[optional]: function to post-process the data returned by the request. Should return the post-processed data e.g
parseData: function (data) {
return data.rows;
}
parseData
can be any function you like and there's nothing to stop you using it to mutate any other variables in scope.
-
start()
- Starts the poller. If passed an object{ initialRequest: true }
it will send its first request immediately, otherwise it will wait untilconfig.refreshInterval
milliseconds. Returns a promise for the result of the first request (ifinitialRequest
is true), or an empty resolved Promise otherwise -
stop()
- Stops polling -
getData()
- Returns the last set of data retrieved from the server (post-processed ifparseData
function exists). This will throw anHttpError
if the most recent fetch received an error.
error
- emits an error whenever a request returns with an errorok
- emits the response whenever a request returns successfully
The classic request cycle for a web application follows a call from a client to the server, which in turn makes one or more further requests to some underlying service(s).
+---> Web service 1 --> Data
|
Client ---> Presentation tier --|---> Web service 2 --> Data
|
+---> Web service 3 --> Data
Once the data has been retrieved the response makes its way back through the various layers to the client.
This causes two problems.
Firstly, your response is dependent on the slowest service to respond. If every request is hanging around waiting for 'the slow one' your performance is pegged to the worst performing part of your application.
Secondly, by far the slowest thing in this type of architecture is the round-trip between the presentation tier and the service(s). The more of these open connections you have hanging around, waiting to close, the greater the burden you place on your server.
Often though, and this is especially true of News sites, the data doesn't change radically from second to second so this round trip is wasted effort.
It's much more efficient for each presentation tier server to periodically fetch the data it needs (or listen for a message to signal when new content is available), stash it in memory, then use that to service any incoming requests.
This suits a microservice architecture, where many discrete modules, APIs etc. need to be assembled by a presentation tier before being rendered out to the client (as HTML, JSON etc.).
This pattern (of asynchronous fetching) allows the presentation tier to focus on building a response from existing data (in memory) and sending it back out the front door as quickly as possible.