Graphene acts as Data Cache layer like open query engine.

Hi Team,

My name is Giang, I would like to propose a new feature for caching results on certain selected nodes with class Meta: cache = True.
I would to do data analytics on big data lake s3 using pyspark mapping spark (or other libraries) schema to graphene schema and I would like to utilize server side graphql as **cache layer** . In other words, I would like to treat graphql as a next custom ORM for pyspark or other dataframe libraries.

When query data, I would like to get custom field results on that node and cache it for 30 minutes **(Where big data speed of access to data lake s3 does not matter, but rather than the aggregations of results)**

@jkimbo cc
Cached data will need to be run when there is no cached data when query and updating when using mutation on the Node

And we also have a scheme for updating from childs to parents

```
import graphene
Import os
os.env[“GRAPHENE_CACHE_TIME”] = 1800

class Company(graphene.ObjectType):
class Meta:
interfaces = (relay.Node,)
cache = True
name = graphene.String()
revenue = graphene.Float()
datetime = graphene.DateTime()
if there are nested child (update all parent nodes cache)

@classmethod // cache this result on query
get_all_companies(cls, info):
return [cls(**data) for data in database.values()]
@classmethod // cache this result by different pairs of inputs on query
get_company_report_by_period(cls, info, name, period):
selected_data = [data for data in database.values() if name == data[“name”] and period in data[“datetime”]]
return {
“name”: name,
“revenue”: sum(data[“revenue”] for data in selected_data),
“datetime”: period
}

class Query(graphene.ObjectType):
get_report = graphene.List(Company)
get_company_report_period = graphene.Field(Company)

def resolve_get_report(_, info):
return Company.get_all_companies()
def resolve_get_company_report_period(_, info, name, period):
return Company.get_company_report_by_period(name, period)

database = {
“0”: {
“name”: “amazon”,
“revenue”: 1000,
“datetime”: “2021-04-01”
},
“1”: {
“name”: “amazon”,
“revenue”: 1000,
“datetime”: “2021-05-01”
},
“2”: {
“name”: “google”,
“revenue”: 1000,
“datetime”: “2021-06-01”
}
}
```
Kind regards
Giang