EdgeQL — A primer

EdgeQL: a primer
Victor Petrovykh
February 10, 2022

Let’s model the schema for something familiar, like a Netflix clone.
Specifically, we concentrate on the part of the schema that represents the
movie library. We ignore all the complexities of accounts handling for this
primer.
2
Let’s Build a Schema

At the bare minimum we need movies with a title and maybe their release
year.
3
type Movie {
required property title -> str;
property release_year -> int32;
}
Start Simple

Movies should have a director.
4
type Movie {
}
type Movie {
}
Add Relationships
type Person {
property name -> str;
}
type Movie {
link director -> Person;
}

Movies should also have some actors listed.
5
More Relationships
type Person {
}
type Movie {
}
type Person {
}
type Movie {
multi link actors -> Person;
}

type Person {
}
type Movie {
multi link actors -> Person;
}
type Person {
}
type Movie {
multi link actors -> Person {
property character_name -> str;
}
}
It may be useful to add the names of the characters the actors played.
6
Enrich Relationships

In addition to the movies we also have shows with multiple episodes.
type Person {
}
type Movie {
}
}
type Show {
property num_episodes -> int32;
}
}
type Person {
}
type Movie {
}
}
More Type Variants
7

To keep duplication minimal we can refactor our Movie and Series.
Refactor
8
type Show {
}
}
type Person {
}
type Movie {
}
}
type Movie extending Content {
}
type Show extending Content {
}
type Person {
}
abstract type Content {
}
}

Let’s add some constraints to nip unreasonable values in the bud.
}
}
type Person {
}
}
}
Add Constraints
9
property release_year -> int32 {
constraint min_value(1900);
}
}
property num_episodes -> int32 {
}
}
type Person {
}
}
}

Querying Nested Data
We can start with a query that gets us all the movie information: title,
release year, director and actors.
select Movie; [
{"id": "a8e8f31a-8a06-11ec-99a1-f7de41ca9560"},
{"id": "a8e5ff2a-8a06-11ec-99a1-8b718b72ffc4"},
{"id": "a8cdecfa-8a06-11ec-99a1-d3ed2d4fe65d"},
{"id": "a8651108-8a06-11ec-99a1-db7a7e621bfc"},
{"id": "a868f052-8a06-11ec-99a1-0779a9198d5d"},
...
10
select Movie {
id,
title,
release_year
};
[
{
"id": "a8e8f31a-8a06-11ec-99a1-f7de41ca9560",
"release_year": 2021,
"title": "Black Widow"
},
{
"id": "a8e5ff2a-8a06-11ec-99a1-8b718b72ffc4",
"title": "Spider-Man: Far From Home"
},
...
select Movie {
id,
title,
release_year,
director: {
name
},
actors: {
name
}
};
[
{
"title": "Black Widow",
"director": {"name": "Cate Shortland"},
"actors": [
{"name": "Scarlett Johansson"},
{"name": "Florence Pugh"},
{"name": "Ray Winstone"},
{"name": "Olga Kurylenko"}
]
},
...
select Movie {
id,
title,
release_year,
director: {
name
},
actors: {
@character_name,
name
}
} filter Movie.title = 'Black Widow';
[
{
"actors": [
{
"@character_name": "Black Widow",
"name": "Scarlett Johansson"
},
{
"@character_name": "Yelena Belova",
"name": "Florence Pugh"
},
...
select Movie {
id,
title,
release_year,
director: {
name
},
actors: {
@character_name,
name
}
} filter .title = 'Black Widow';
[
{
"actors": [
{
"@character_name": "Black Widow",
},
{
"@character_name": "Yelena Belova",
"name": "Florence Pugh"
},
...

Polymorphic Queries
Let’s tweak our query to provide us the kinds of results we may want to
see in suggestions.
11
select Movie {
id,
title,
release_year,
director: { name }
}
filter .actors.name =
'Scarlett Johansson';
[
{
"director": {"name": "Cate Shortland"}
},
{
"id": "a8921e64-8a06-11ec-99a1-d3e990178505",
"title": "Captain America: Civil War",
...
select Movie {
id,
title,
release_year,
director: { name }
}
'Scarlett Johansson'
order by .release_year desc
limit 5;
[
{
"director": {"name": "Cate Shortland"}
},
{
"id": "a8cdecfa-8a06-11ec-99a1-d3ed2d4fe65d",
"title": "Avengers: Endgame",
...
select Content {
id,
title,
[is Show].num_episodes,
[is Movie].release_year,
[is Movie].director: { name }
}
'Scarlett Johansson'
limit 5;
[
{
"num_seasons": null,
},
{
"id": "a8cdecfa-8a06-11ec-99a1-d3ed2d4fe65d",
"num_seasons": null,
"title": "Avengers: Endgame"
...

Querying Custom Data
We probably want to be able to display some information about the actors,
too. But don’t they only have one property?
12
select Person {
id,
name,
name_parts :=
str_split(.name, ' ')
}
filter .name = 'Scarlett Johansson';
[
{
"id": "a8328530-8a06-11ec-99a1-6b35f115a4eb",
"name": "Scarlett Johansson",
"name_parts": ["Scarlett", "Johansson"]
}
]
select Person {
id,
name,
name_parts :=
str_split(.name, ' '),
movies_count := count(
(select Movie
filter .actors = Person)
)
}
[
{
"id": "a8328530-8a06-11ec-99a1-6b35f115a4eb",
"name_parts": ["Scarlett", "Johansson"],
“movies_count”: 8
}
]
select Person {
id,
name,
name_parts :=
str_split(.name, ' '),
movies_count :=
count(.<actors[is Movie])
}
[
{
"id": "a8328530-8a06-11ec-99a1-6b35f115a4eb",
"name_parts": ["Scarlett", "Johansson"],
“movies_count”: 8
}
]

That backlink seems useful, so let’s just add it to the schema.
}
}
}
}
type Person {
}
}
}
Add Computed Link
13
}
}
}
}
type Person {
link in_movies :=
.<actors[is Movie];
}
}
}

Fine-Tuned Queries
Let’s add the latest 3 movies the actor appeared in to the data we fetch.
14
select Person {
id,
name,
movies_count := count(.in_movies)
}
[
{
"id": "a8328530-8a06-11ec-99a1-6b35f115a4eb",
"movies_count": 8,
}
]
select Person {
id,
name,
movies_count := count(.in_movies),
in_movies: {
title,
release_year
}
limit 3
}
[
{
"in_movies": [
{
},
{
"title": "Avengers: Endgame"
},
{
"title": "Avengers: Infinity War"
}
],
"id": "a8328530-8a06-11ec-99a1-6b35f115a4eb",
"movies_count": 8,
}
]

Insert Data
Of course you can also insert, update and delete data.
So let’s look at a nice simple nested insert here.
15
insert Movie {
title := 'Dune',
release_year := 2021,
director := (
insert Person {
name := 'Denis Villeneuve'
}
)
};
[{"id": "4bfef230-8a56-11ec-a746-e310c2aa2b6e"}]

Many More Features
16
this primer
scalar constraints
alias
function
index
annotation
EdgeQL

EdgeQL — A primer

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