Significant performance hit when using async resolvers #190
Description
During development (Starlette + Ariadne) of our product I noticed significant performance degradation when GraphQL responses got significant long (1000+ entities in a list). I started profiling and drilling into the issue and I pinpointed it to async resolvers. Whenever a resolver is async and it is called a lot (100.000) you can see significant slowdowns 4x-7x, even if there is nothing async to it.
The question that I ended up with, is this a limitation of Python asyncio or how the results are gathered for async fields in graphql execute?
Any insight/help is greatly appreciated as we really need more performance and changing to sync is not really an option (nor is rewriting it to another language) 😭
import asyncio from dataclasses import dataclass from graphql import ( GraphQLField, GraphQLList, GraphQLObjectType, GraphQLSchema, GraphQLString, graphql, ) # On a MacBook Pro M1 Max this takes around 44 seconds in "async" case # and "only" 7 seconds when async field is removed from the query TOTAL_PEOPLE = 1000000 @dataclass class Person: firstName: str lastName: str def resolve_people(*_): return [Person(f"Jane{i}", "Do") for i in range(0, TOTAL_PEOPLE)] def resolve_fullname(person: Person, *_): return f"{person.firstName} {person.lastName}" async def async_resolve_fullname(person: Person, *_): return f"{person.firstName} {person.lastName}" PersonType = GraphQLObjectType( "Person", { "firstName": GraphQLField(GraphQLString), "lastName": GraphQLField(GraphQLString), "fullName": GraphQLField(GraphQLString, resolve=resolve_fullname), "asyncFullName": GraphQLField(GraphQLString, resolve=async_resolve_fullname), }, ) schema = GraphQLSchema( query=GraphQLObjectType( name="RootQueryType", fields={ "people": GraphQLField(GraphQLList(PersonType), resolve=resolve_people) }, ) ) async def main(): result = await graphql( schema, """#graphql query { people { firstName lastName fullName asyncFullName # THIS IS THE SLOW PART } } """, ) assert len(result.data["people"]) == TOTAL_PEOPLE def run(callable, is_profile: bool = False): if not is_profile: return asyncio.run(callable()) import yappi yappi.set_clock_type("WALL") with yappi.run(): asyncio.run(callable()) func_stats = yappi.get_func_stats() func_stats.save("callgrind.func_stats", "callgrind") with open("func_stats.txt", "w") as file: func_stats.print_all( file, { # We increase the column widths significantly 0: ("name", 120), 1: ("ncall", 10), 2: ("tsub", 12), 3: ("ttot", 12), 4: ("tavg", 12), }, ) if __name__ == "__main__": run(main, is_profile=False)
Versions:
- macOS: 13.2
- python 3.11
- graphql-core 3.2.3
- yappi 1.4.0