I'm am very interested by GraphQL for an analytic solution (think of an webapp displaying graphs). But I cannot find any examples of GraphQL using aggregate function. This is a main aspect of most of the queries done by my frontend.
For my solution, we have 3 typical backend calls.
Let say we have this type specified in GraphQL
type Person {
name: String
age: Int
create_time: Date
}
This seems to be well handled by GraphQL. No question here.
ex. Search age of Person named Bob { Person(name: "Bob") { age } }
This is the typical case where I want to display the info in a Pie Chart. So let say I want to count the number of person by age.
Here would be the PostgreSQL query:
SELECT age, count(*) from Ticket group by age;
What would be the equivalent in GraphQL?
ex. Let say I want to count the number of created user per hour.
Here would be the PostgreSQL query:
SELECT date_trunc('hour', create_time) as create_time_bin, count(*) from Person group by create_time_bin order by create_time_bin ASC;
What would be the GraphQL equivalent query?
Aggregate queries fetch aggregate data, including the following: Count queries that let you count fields satisfying certain criteria specified using a filter. Advanced aggregate queries that let you calculate the maximum, minimum, sum and average of specified fields.
GraphQL supports the following operations, which provide different ways to interact with a graph: queries: used to find a starting point and traverse a subgraph. mutations: used to change the graph and return a result. subscriptions: used to listen for changes in the graph.
GraphQL is often confused with being a database technology. This is a misconception, GraphQL is a query language for APIs - not databases. In that sense it's database agnostic and can be used with any kind of database or even no database at all.
Searching and filtering is a standard part of any GraphQL API.
@Damien, those problems are not GraphQL's problems.
Whenever you want do something in GraphQL you must define a Type of return data, Spec of function you implement, and sometimes a Type of input data to feed into your function. Finally you write code to do the job.
In fact, it looks like you (re)write your code in GraphQL language.
Take the example where you want to display the info in a Pie Chart:
SELECT age, count(*) from Ticket group by age;
Define your return data here is a list of age and count:
type TickGroupByAge {
age: Int
count: Int
}
Define your function or Query in GraphQL language:
getTicketGroupByAge : [TickGroupByAge]`
Finally write a function to implement above query:
async function(){
const res = await client.query("SELECT age, count(*) from Ticket group by age");
return res.rows;
}
@Ryan I totally agree with you that GraphQL forces you to write a lot of type definitions to resolve a simple task. For that reason, I ended up building my own NextQL - GraphQL-liked engine which is similar to GraphQL but simpler.
My project supports complex nested type definitions, which free you from define a lot of useless ones.
GraphQL, at the end of the day, responds with your defined types. You just need to put that data into a type. Whether this is a specific type for these different queries, or fields for that data on existing types, it's up to you but that's all it boils down to. GraphQL does require more effort up front in terms of defining your types and what all queries will return, which makes it more rigid, but the idea is that on other side of that lies some cool features, like introspection and type checking. If it doesn't seem to make logical sense to put that sort of "ad hoc" data structures into a GraphQL type, then it's not illegal to have non-GraphQL endpoints if you need other data sources.
Check out https://github.com/niclasko/Cypher.js (note: I'm the author)
With relevance to the question. It can be used to query and aggregate over data from JSON endpoints:
load json from "http://url/person" as l return l.age, count(1)
There’s even a bar chart function:
load json from "http://url/person" as l return barchart(toint(l.age)) as age_distribution
Here's an example of querying a complex JSON document and performing aggregate analysis on it:
Cypher.js JSON query example
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