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开源软件名称(OpenSource Name):banterfm/graphql-crunch开源软件地址(OpenSource Url):https://github.com/banterfm/graphql-crunch开源编程语言(OpenSource Language):TypeScript 99.8%开源软件介绍(OpenSource Introduction):graphql-crunchOptimizes JSON responses by minimizing duplication and improving compressibility. On Banter.fm, we see a 76% reduction in raw JSON size and a 30% reduction in gzip'd size. This leads to reduced transfer time and faster JSON parsing on mobile. Client support
InstallationThis library is distributed on $ npm install graphql-crunch --save or with Yarn: $ yarn add graphql-crunch How does it work?We flatten the object hierarchy into an array using a post-order traversal of the object graph. As we traverse we efficiently check if we've come across a value before, including arrays and objects, and replace it with a reference to it's earlier occurence if we've seen it. Values are only ever present in the array once. Note: Crunching and uncrunching is an entirely lossless process. The final payload exactly matches the original.MotivationLarge JSON blobs can be slow to parse on some mobile platforms, especially older Android phones, so we set out to improve that. At the same time we also wound up making the payloads more amenable to gzip compression too. GraphQL and REST-ful API responses tend to have a lot of duplication leading to huge payload sizes. ExampleIn these examples, we use the SWAPI GraphQL demo. Small ExampleUsing this query we'll fetch the first 2 people and their first 2 films and the first 2 characters in each of those films. We limit the connections to the first two items to keep the payload small: {
allPeople(first: 2) {
people {
name
gender
filmConnection(first: 2) {
films {
title
characterConnection(first: 2) {
characters {
name
gender
}
}
}
}
}
}
} We get this response: {
"data": {
"allPeople": {
"people": [
{
"name": "Luke Skywalker",
"gender": "male",
"filmConnection": {
"films": [
{
"title": "A New Hope",
"characterConnection": {
"characters": [
{
"name": "Luke Skywalker",
"gender": "male"
},
{
"name": "C-3PO",
"gender": "n/a"
}
]
}
},
{
"title": "The Empire Strikes Back",
"characterConnection": {
"characters": [
{
"name": "Luke Skywalker",
"gender": "male"
},
{
"name": "C-3PO",
"gender": "n/a"
}
]
}
}
]
}
},
{
"name": "C-3PO",
"gender": "n/a",
"filmConnection": {
"films": [
{
"title": "A New Hope",
"characterConnection": {
"characters": [
{
"name": "Luke Skywalker",
"gender": "male"
},
{
"name": "C-3PO",
"gender": "n/a"
}
]
}
},
{
"title": "The Empire Strikes Back",
"characterConnection": {
"characters": [
{
"name": "Luke Skywalker",
"gender": "male"
},
{
"name": "C-3PO",
"gender": "n/a"
}
]
}
}
]
}
}
]
}
}
} After we crunch it, we get: {
"data": [
"male",
"Luke Skywalker",
{ "gender": 0, "name": 1 },
"n/a",
"C-3PO",
{ "gender": 3, "name": 4 },
[2, 5],
{ "characters": 6 },
"A New Hope",
{ "characterConnection": 7, "title": 8 },
"The Empire Strikes Back",
{ "characterConnection": 7, "title": 10 },
[9, 11],
{ "films": 12 },
{ "filmConnection": 13, "gender": 0, "name": 1 },
{ "filmConnection": 13, "gender": 3, "name": 4 },
[14, 15],
{ "people": 16 },
{ "allPeople": 17 }
]
} The transformed payload is substantially smaller. After converting both payloads to JSON (with formatting removed), the transformed payload is 49% fewer bytes. When the client receives this, we simply uncrunch it and get back the exact original version for the client to handle. Large ExampleIn real-world scenarios, we'll have modularized our shcema with fragments and have
as well as connections that have more than two items in them. Here's a query
similar to the one above except we don't limit the size of the connections and
we request a standard set of selections on {
allPeople {
people {
...PersonFragment
filmConnection {
films {
...FilmFragment
}
}
}
}
}
fragment PersonFragment on Person {
name
birthYear
eyeColor
gender
hairColor
height
mass
skinColor
homeworld {
name
population
}
}
fragment FilmFragment on Film {
title
characterConnection {
characters {
...PersonFragment
}
}
} The resulting response from this query is roughly 1MB of JSON (989,946 bytes), but with tons of duplication. Here is how crunching impacts the payload size:
This is an admittedly extreme result, but highlights the potential for crunching payloads with large amounts of duplication. UsageServer-sideWith import { ApolloServer } from "apollo-server";
const server = new ApolloServer({
// schema, context, etc...
formatResponse: (response) => {
if (response.data) {
response.data = crunch(response.data);
}
return response;
},
});
server.listen({ port: 80 }); To maintain compatibility with clients that aren't expecting crunched payloads, we recommend conditioning the crunch on a query param, like so: import url from "url";
import querystring from "querystring";
import { ApolloServer } from "apollo-server";
const server = new ApolloServer({
// schema, context, etc...
formatResponse: (response, options) => {
const parsed = url.parse(options.context.request.url);
const query = querystring.parse(parsed.query);
if (query.crunch && response.data) {
const version = parseInt(query.crunch) || 1;
response.data = crunch(response.data, version);
}
return response;
},
});
server.listen({ port: 80 }); Now only clients that opt-in to crunched payloads via the Your client can specify the version of the crunch format to use in the query parameter. If the version isn't specified, or an unknown version is supplied, we default to v1.0. Client-sideOn the client, we uncrunch the server response before the GraphQL client processes it. With import { ApolloClient } from 'apollo-client';
import { ApolloLink, concat } from 'apollo-link';
import { HttpLink } from 'apollo-link-http';
import { uncrunch } from 'graphql-crunch';
const http = new HttpLink({
credentials: 'include',
uri: '/api'
});
const uncruncher = new ApolloLink((operation, forward) =>
forward(operation)
.map((response) => {
response.data = uncrunch(response.data);
return response;
});
);
const client = new ApolloClient({link: concat(uncruncher, http)}); |
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