Performance optimisation with GraphQL

  • Published on
    06-Jan-2017

  • View
    1.718

  • Download
    0

Transcript

  • Optimising response times with GraphQL an experiment with MongoDB and ElasticSearch (These slides were adapted to be suitable offline)
  • Intuitions: GraphQL faster ⢠less requests ⢠smaller responses
  • Reality Eats Intuitions for Breakfast
  • Not obvious ⢠Client has to send more info ⢠query contains list of fields ⢠-> biggest requests payloads ⢠Server has more work to do ⢠query validation ⢠customise response
  • Do not guess it, test it
  • âA client âI want the id and the versions of all productsâ
  • 30000 50000 100000 MongoDB ES Perf of REST endpoints
  • query($offset: Int!, $limit: Int!) { products(offset: $offset, limit: $limit) { results { id version } } } In GraphiQL GaphQL query https://impex.sphere.io/graphiql?query=query(%24offset%3A%20Int!%2C%20%24limit%3A%20Int!)%20%7B%0A%20%20products(offset%3A%20%24offset%2C%20limit%3A%20%24limit)%20%7B%0A%20%20%20%20results%20%7B%0A%20%20%20%20%20%20id%0A%20%20%20%20%20%20version%0A%20%20%20%20%7D%0A%20%20%7D%0A%7D%0A&variables=%7B%0A%20%20%22offset%22%3A%200%2C%0A%20%20%22limit%22%3A%205%0A%7D
  • Client App Server Data storage Optimisation between client and application server
  • 30000 50000 100000 MongoDB ES MongoDB GraphQL ES GraphQL
  • ⢠smallest responses -> better performances ⢠difference not as important as expected
  • Client App Server Data storage Optimisation between application server and data storage
  • select * from products; select id, version from products; Optimise DB queries
  • http://sangria-graphql.org/learn/#projections http://sangria-graphql.org/learn/#projections
  • In Mongo db .getCollection('products') .find({}) db .getCollection('products') .find({}, {_id: 1, version: 1})
  • 30000 50000 100000 Mongo Mongo GraphQL Mongo GraphQL projections
  • In Elasticsearch { "_source": true, "query" : [â¦] } { "_source": [ "id", "version"], "query" : [â¦] }
  • 30000 50000 100000 ES ES GraphQL ES GraphQL projections
  • 30000 50000 100000 Mongo ES Mongo GraphQL projections ES GraphQL projections
  • ⢠Optimising database queries have an important impact on performances ⢠GraphQL allows to optimise from client to data storage
  • ⢠Tested use-case intentionally picked to be favorable to GraphQL (test assumption) ⢠Test yourself for your use-case ⢠Should not choose GraphQL primary for performances but for features
  • Further optimisations ⢠Pre-computed queries ⢠client sends only values of variables ⢠queries already validated ⢠Binary serialisation format