Performance issues related to complete_value on large datasets #189

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1. JCatrielLopez

   changed the title [-]Performance issues with complete_value on large datasets[/-] [+]Performance issues related to complete_value on large datasets[/+] on Jan 11, 2023
2. JCatrielLopez commented on Jan 11, 2023

   

   JCatrielLopez

   on Jan 11, 2023

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   Possibly related to this graphql-js issue
3. Cito commented on Jan 11, 2023

   

   Cito

   on Jan 11, 2023

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   Thanks for reporting. Will look into this when I have more time, probably only after releasing 3.3. It would be helpful if you could post example code with dummy data to reproduce this.
4. JCatrielLopez commented on Jan 12, 2023

   

   JCatrielLopez

   on Jan 12, 2023

   Last edited by JCatrielLopez

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   schema.graphql:

   type Query {
       persons: [Person]
   }
   
   type Person {
       id: String!
       name: String
       ssn: String
       alive: Boolean
       has_job: Boolean
       job: JobDetails
       address: Address
       pets: Address
       house: House
       partner: Person
   }
   
   type JobDetails {
       id: String
       name: String
   }
   
   type Address {
       id: String
       name: String
   }
   
   type Pets {
       id: String
       name: String
       race: String
       color: String
   }
   
   type House {
       color: String
       floors: Int
       is_duplex: Boolean
       is_apt: Boolean
   }
   

   server.py:

   import random
   import string
   import sys
   
   import yappi
   
   from graphql import graphql_sync, build_ast_schema
   from graphql.language.parser import parse
   
   yappi.set_clock_type("wall")
   
   with open("./schema.graphql", "r") as f:
       schema = build_ast_schema(parse(f.read()))
   
   
   class Query:
       """The root resolvers"""
   
       def persons(self, info):
           output = []
           for _ in range(5_000):
               output.append(
                   dict(
                       id="".join(random.choices(string.ascii_lowercase + string.digits, k=9)),
                       name=f"John Doe",
                       ssn="00000000000000000",
                       alive=True,
                       has_job=False,
                       job=dict(id="xxx", name="test"),
                       address=dict(id="yyy", name="Fake Street"),
                       pets=dict(id="zzz", name="test"),
                       house=dict(
                           color="RED",
                           floors=2,
                           is_duplex=False
                       ),
                       partner=dict(id="".join(random.choices(string.ascii_lowercase + string.digits, k=9)), name="test"),
                   )
               )
           return output
   
   
   def main():
       query = """{ 
           persons{ 
               id 
               name 
               alive 
               has_job 
               job{id name}
               partner{id name}
               address{id name}
               pets{id name}
               house{color floors is_duplex}
           } 
       }"""
   
       yappi.start()
       result = graphql_sync(schema, query, Query())
       yappi.stop()
   
       if result.errors:
           print(result)
           sys.exit(1)
   
       yappi.get_func_stats().save("profile", type="pstat")
   
   
   # To visualize profile:
   # python -m snakeviz profile --server
   
   if __name__ == '__main__':
       main()