I have a very big object in javascript (about 10MB).
And when I stringify it, it takes a long time, so I send it to backend and parse it to an object( actually nested objects with arrays), and that takes long time too but it's not our problem in this question.
The problem:
How can I make JSON.stringify
faster, any ideas or alternatives, I need a javaScript solution, libraries I can use or ideas here.
What I've tried
I googled a lot and looks there is no better performance than JSON.stringify
or my googling skills got rusty!
Result
I accept any suggestion that may solve me the long saving (sending to backend) in the request (I know its big request).
Code Sample of problem (details about problem)
Request URL:http://localhost:8081/systemName/controllerA/update.html;jsessionid=FB3848B6C0F4AD9873EA12DBE61E6008
Request Method:POST
Status Code:200 OK
Am sending a POST to backend and then in JAVA
request.getParameter("BigPostParameter")
and I read it to convert to object using
public boolean fromJSON(String string) {
if (string != null && !string.isEmpty()) {
ObjectMapper json = new ObjectMapper();
DateFormat dateFormat = new SimpleDateFormat(YYYY_MM_DD_T_HH_MM_SS_SSS_Z);
dateFormat.setTimeZone(TimeZone.getDefault());
json.setDateFormat(dateFormat);
json.configure(DeserializationFeature.ACCEPT_SINGLE_VALUE_AS_ARRAY, true);
WebObject object;
// Logger.getLogger("JSON Tracker").log(Level.SEVERE, "Start");
try {
object = json.readValue(string, this.getClass());
} catch (IOException ex) {
Logger.getLogger(JSON_ERROR).log(Level.SEVERE, "JSON Error: {0}", ex.getMessage());
return false;
}
// Logger.getLogger("JSON Tracker").log(Level.SEVERE, "END");
return this.setThis(object);
}
return false;
}
Like This
BigObject someObj = new BigObject();
someObj.fromJSON(request.getParameter("BigPostParameter"))
P.S : FYI this line object = json.readValue(string, this.getClass());
is also very very very slow.
Again to summarize
Problem in posting time (stringify) JavaScript bottle nick.
Another problem parsing that stringified into an object (using jackson), and mainly I have svg tags content in that stringified object as a style column, and other columns are strings, int mainly
I have a very big object in javascript (about 10MB).
And when I stringify it, it takes a long time, so I send it to backend and parse it to an object( actually nested objects with arrays), and that takes long time too but it's not our problem in this question.
The problem:
How can I make JSON.stringify
faster, any ideas or alternatives, I need a javaScript solution, libraries I can use or ideas here.
What I've tried
I googled a lot and looks there is no better performance than JSON.stringify
or my googling skills got rusty!
Result
I accept any suggestion that may solve me the long saving (sending to backend) in the request (I know its big request).
Code Sample of problem (details about problem)
Request URL:http://localhost:8081/systemName/controllerA/update.html;jsessionid=FB3848B6C0F4AD9873EA12DBE61E6008
Request Method:POST
Status Code:200 OK
Am sending a POST to backend and then in JAVA
request.getParameter("BigPostParameter")
and I read it to convert to object using
public boolean fromJSON(String string) {
if (string != null && !string.isEmpty()) {
ObjectMapper json = new ObjectMapper();
DateFormat dateFormat = new SimpleDateFormat(YYYY_MM_DD_T_HH_MM_SS_SSS_Z);
dateFormat.setTimeZone(TimeZone.getDefault());
json.setDateFormat(dateFormat);
json.configure(DeserializationFeature.ACCEPT_SINGLE_VALUE_AS_ARRAY, true);
WebObject object;
// Logger.getLogger("JSON Tracker").log(Level.SEVERE, "Start");
try {
object = json.readValue(string, this.getClass());
} catch (IOException ex) {
Logger.getLogger(JSON_ERROR).log(Level.SEVERE, "JSON Error: {0}", ex.getMessage());
return false;
}
// Logger.getLogger("JSON Tracker").log(Level.SEVERE, "END");
return this.setThis(object);
}
return false;
}
Like This
BigObject someObj = new BigObject();
someObj.fromJSON(request.getParameter("BigPostParameter"))
P.S : FYI this line object = json.readValue(string, this.getClass());
is also very very very slow.
Again to summarize
Problem in posting time (stringify) JavaScript bottle nick.
Another problem parsing that stringified into an object (using jackson), and mainly I have svg tags content in that stringified object as a style column, and other columns are strings, int mainly
- 2 How do you send it to a backend without converting it to JSON? – csander Commented Aug 4, 2017 at 19:03
- 1 A 10 MB object will take a considerable time to be processed, there is no way around that directly. Posing a question looking for a workaround would be akin to asking how to make a big file download faster: sure you can cut some time here and there, but there is still an enormous amount of data to be processed, and that will take time. You'll need to design your UX around this. – John Weisz Commented Aug 4, 2017 at 19:13
- 1 Is this a perceptual (UI hangs/blocked interactions, etc.) or performance issue (you actually need the data to be serialized faster)? If the issue is perceptual, you may want to look into handling the operation using the Service Worker APIs – Rob M. Commented Aug 4, 2017 at 19:13
- 3 I'm inclined to say this is too broad, because the solution is to cache and/or break up the object, or both. There are no faster serializers: see github.com/kawanet/msgpack-lite – Meirion Hughes Commented Aug 4, 2017 at 19:43
- 3 Have you considered using protobuf to communicate ? It is not much faster, but still faster auth0.com/blog/beating-json-performance-with-protobuf Maybe in your scenario the gains can be larger than on this sample, it may be worth giving it a try – Jonathan Muller Commented Nov 24, 2018 at 6:39
4 Answers
Reset to default 2As commenters said - there is no way to make parsing faster.
If the concern is that the app is blocked while it's stringifying/parsing then try to split data into separate objects, stringily them and assemble back into one object before saving on the server.
If loading time of the app is not a problem you could try to ad-hoc incremental change on top of the existing app.
- ... App loading
- Load map data
- Make full copy of the data
- ... End loading
- ... App working without changes
- ... When saving changes
- diff copy with changed data to get JSON diff
- send changes (much smaller then full data)
- ... On server
- apply JSON diff changes on the server to the full data stored on server
- save changed data
I used json-diff https://github.com/andreyvit/json-diff to calc changes, and there are few analogs.
Parsing is a slow process. If what you want is to POST a 10MB object, turn it into a file, a blob, or a buffer. Send that file/blob/buffer using formdata instead of application/json and application/x-www-form-urlencoded.
Reference
An example using express/multer
Solution
Well just as most big "repeatable" problems go, you could use async!
But wait, isn't JS still single-threaded even when it does async... yes... but you can use Service-Workers to get true async and serialize an object way faster by parallelizing the process.
General Approach
mainPage.js
//= Functions / Classes =============================================================|
// To tell JSON stringify that this is already processed, don't touch
class SerializedChunk {
constructor(data){this.data = data}
toJSON() {return this.data}
}
// Attach all events and props we need on workers to handle this use case
const mapCommonBindings = w => {
w.addEventListener('message', e => w._res(e.data), false)
w.addEventListener('error', e => w._rej(e.data), false)
w.solve = obj => {
w._state && await w._state.catch(_=>_) // Wait for any older tasks to complete if there is another queued
w._state = new Promise((_res, _rej) => {
// Give this object promise bindings that can be handled by the event bindings
// (just make sure not to fire 2 errors or 2 messages at the same time)
Object.assign(w, {_res, _rej})
})
w.postMessage(obj)
return await w._state // Return the final output, when we get the `message` event
}
}
//= Initialization ===================================================================|
// Let's make our 10 workers
const workers = Array(10).fill(0).map(_ => new Worker('worker.js'))
workers.forEach(mapCommonBindings)
// A helper function that schedules workers in a round-robin
workers.schedule = async task => {
workers._c = ((workers._c || -1) + 1) % workers.length
const worker = workers[workers._c]
return await worker.solve(task)
}
// A helper used below that takes an object key, value pair and uses a worker to solve it
const _asyncHandleValuePair = async ([key, value]) => [key, new SerializedChunk(
await workers.schedule(value)
)]
//= Final Function ===================================================================|
// The new function (You could improve the runtime by changing how this function schedules tasks)
// Note! This is async now, obviously
const jsonStringifyThreaded = async o => {
const f_pairs = await Promise.all(Object.entries(o).map(_asyncHandleValuePair))
// Take all final processed pairs, create a new object, JSON stringify top level
final = f_pairs.reduce((o, ([key, chunk]) => (
o[key] = chunk, // Add current key / chunk to object
o // Return the object to next reduce
), {}) // Seed empty object that will contain all the data
return JSON.stringify(final)
}
/* lot of other code, till the function that actually uses this code */
async function submitter() {
// other stuff
const payload = await jsonStringifyThreaded(input.value)
await server.send(payload)
console.log('Done!')
}
worker.js
self.addEventListener('message', function(e) {
const obj = e.data
self.postMessage(JSON.stringify(obj))
}, false)
Notes:
This works the following way:
- Creates a list of 10 workers, and adds a few methods and props to them
- We care about
async .solve(Object): String
which solves our tasks using promises while masking away callback hell
- We care about
- Use a new method:
async jsonStringifyThreaded(Object): String
which does theJSON.stringify
asynchronously- We break the object into entries and solve each one parallelly (this can be optimized to be recursive to a certain depth, use best judgement :))
- Processed chunks are cast into
SerializedChunk
which theJSON.stringify
will use as is, and not try to process (since it has.toJSON()
) - Internally if the number of keys exceeds the workers, we round-robin back to the first worker and overschedule them (remember, they can handle queued tasks)
Optimizations
You may want to consider a few more things to improve performance:
- Use of Transferable Objects which will decrease the overhead of passing objects to service workers significantly
- Redesign
jsonStringifyThreaded()
to schedule more objects at deeper levels.
You can explore libraries like fast-json-stringify which use a template schema and use it while converting the json object, to boost the performance. Check the below article.
https://developpaper.com/how-to-improve-the-performance-of-json-stringify/