In our API, each SQL table is reflected as a set of GraphQL types. At a high level, tables become types and columns/foreign keys become fields on those types.
By default, PostgreSQL table and column names are not inflected when reflecting GraphQL names. For example, an account_holder table has GraphQL type name account_holder. In cases where SQL entities are named using snake_case, enable inflection to match GraphQL/Javascript conventions e.g. account_holder -> AccountHolder.
Individual table, column, and relationship names may also be manually overridden.
Every table must have a primary key for it to be exposed in the GraphQL schema. For example, the following Blog table will be available in the GraphQL schema as blogCollection since it has a primary key named id:
create table "Blog"(
id serial primary key,
name varchar(255) not null,
);But the following table will not be exposed because it doesn't have a primary key:
create table "Blog"(
id int,
name varchar(255) not null,
);The Query type is the entrypoint for all read access into the graph.
The node interface allows for retrieving records that are uniquely identifiable by a globally unique nodeId: ID! field. For more information about nodeId, see nodeId.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null,
description varchar(255),
"createdAt" timestamp not null,
"updatedAt" timestamp not null
);GraphQL Types === "QueryType"
```graphql
"""The root type for querying data"""
type Query {
"""Retrieve a record by its `ID`"""
node(nodeId: ID!): Node
}
```
To query the node interface effectively, use inline fragments to specify which fields to return for each type.
Example === "Query"
```graphql
{
node(
nodeId: "WyJwdWJsaWMiLCAiYmxvZyIsIDFd"
) {
nodeId
# Inline fragment for `Blog` type
... on Blog {
name
description
}
}
}
```
=== "Response"
```json
{
"data": {
"node": {
"name": "Some Blog",
"nodeId": "WyJwdWJsaWMiLCAiYmxvZyIsIDFd",
"description": "Description of Some Blog"
}
}
}
```
Each table has top level entry in the Query type for selecting records from that table. Collections return a connection type and can be paginated, filtered, and sorted using the available arguments.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null,
description varchar(255),
"createdAt" timestamp not null,
"updatedAt" timestamp not null
);GraphQL Types === "QueryType"
```graphql
"""The root type for querying data"""
type Query {
"""A pagable collection of type `Blog`"""
blogCollection(
"""Query the first `n` records in the collection"""
first: Int
"""Query the last `n` records in the collection"""
last: Int
"""Query values in the collection before the provided cursor"""
before: Cursor
"""Query values in the collection after the provided cursor"""
after: Cursor
"""
Skip n values from the after cursor. Alternative to cursor pagination. Backward pagination not supported.
"""
offset: Int
"""Filters to apply to the results set when querying from the collection"""
filter: BlogFilter
"""Sort order to apply to the collection"""
orderBy: [BlogOrderBy!]
): BlogConnection
}
```
Connection types are the primary interface to returning records from a collection.
Connections wrap a result set with some additional metadata.
=== "BlogConnection"
```graphql
type BlogConnection {
# Count of all records matching the *filter* criteria
totalCount: Int!
# Pagination metadata
pageInfo: PageInfo!
# Result set
edges: [BlogEdge!]!
}
```
=== "BlogEdge"
```graphql
type BlogEdge {
# Unique identifier of the record within the query
cursor: String!
# Contents of a record/row in the results set
node: Blog
}
```
=== "PageInfo"
```graphql
type PageInfo {
# unique identifier of the first record within the query
startCursor: String
# unique identifier of the last record within the query
endCursor: String
# is another page of content available
hasNextPage: Boolean!
# is another page of content available
hasPreviousPage: Boolean!
}
```
=== "Blog"
```graphql
# A record from the `blog` table
type Blog {
# globally unique identifier
nodeId: ID!
# Value from `id` column
id: Int!
# Value from `name` column
name: String!
# Value from `description` column
description: String
# Value from `createdAt` column
createdAt: Datetime!
# Value from `updatedAt` column
updatedAt: Datetime!
}
```
=== "BlogOrderBy"
```graphql
input BlogOrderBy {
id: OrderByDirection
name: OrderByDirection
description: OrderByDirection
createdAt: OrderByDirection
updatedAt: OrderByDirection
}
```
=== "BlogFilter"
```graphql
input BlogFilter {
nodeId: IDFilter
id: IntFilter
name: StringFilter
description: StringFilter
createdAt: DatetimeFilter
updatedAt: DatetimeFilter
and: [BlogFilter!]
or: [BlogFilter!]
not: BlogFilter
}
```
!!! note
The `totalCount` field is disabled by default because it can be expensive on large tables. To enable it use a [comment directive](configuration.md#totalcount)
Paginating forwards and backwards through collections is handled using the first, last, before, and after parameters, following the relay spec.
=== "QueryType"
```graphql
type Query {
blogCollection(
"""Query the first `n` records in the collection"""
first: Int
"""Query the last `n` records in the collection"""
last: Int
"""Query values in the collection before the provided cursor"""
before: Cursor
"""Query values in the collection after the provided cursor"""
after: Cursor
...truncated...
): BlogConnection
}
```
Metadata relating to the current page of a result set is available on the pageInfo field of the connection type returned from a collection.
=== "PageInfo" ```graphql type PageInfo {
# unique identifier of the first record within the query
startCursor: String
# unique identifier of the last record within the query
endCursor: String
# is another page of content available
hasNextPage: Boolean!
# is another page of content available
hasPreviousPage: Boolean!
}
```
=== "BlogConnection"
```graphql
type BlogConnection {
# Pagination metadata
pageInfo: PageInfo!
# Result set
edges: [BlogEdge!]!
}
```
To paginate forward in the collection, use the first and after arguments. To retrieve the first page, the after argument should be null or absent.
Example
=== "Query"
```graphql
{
blogCollection(
first: 2,
after: null
) {
pageInfo {
startCursor
endCursor
hasPreviousPage
hasNextPage
}
edges {
cursor
node {
id
}
}
}
}
```
=== "Page 1"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 1
},
"cursor": "WzFd"
},
{
"node": {
"id": 2
},
"cursor": "WzJd"
}
],
"pageInfo": {
"startCursor": "WzFd",
"endCursor": "WzJd",
"hasNextPage": true,
"hasPreviousPage": false
}
}
}
}
```
To retrieve the next page, provide the cursor value from data.blogCollection.pageInfo.endCursor to the after argument of another query.
=== "Query"
```graphql
{
blogCollection(
first: 2,
after: "WzJd"
) {
...truncated...
}
```
=== "Page 2"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 3
},
"cursor": "WzNd"
},
{
"node": {
"id": 4
},
"cursor": "WzRd"
}
],
"pageInfo": {
"startCursor": "WzNd",
"endCursor": "WzRd",
"hasNextPage": false,
"hasPreviousPage": true
}
}
}
}
```
once the collection has been fully enumerated, data.blogConnection.pageInfo.hasNextPage returns false.
To paginate backwards through a collection, repeat the process substituting first -> last, after -> before, hasNextPage -> hasPreviousPage
In addition to keyset pagination, collections may also be paged using first and offset, which operates like SQL's limit and offset to skip offset number of records in the results.
!!! note
`offset` based pagination becomes inefficient the `offset` value increases. For this reason, prefer cursor based pagination where possible.
=== "Query"
```graphql
{
blogCollection(
first: 2,
offset: 2
) {
...truncated...
}
```
=== "Page 2"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 3
},
"cursor": "WzNd"
},
{
"node": {
"id": 4
},
"cursor": "WzRd"
}
],
"pageInfo": {
"startCursor": "WzNd",
"endCursor": "WzRd",
"hasNextPage": false,
"hasPreviousPage": true
}
}
}
}
```
To filter the result set, use the filter argument.
=== "QueryType"
```graphql
type Query {
blogCollection(
"""Filters to apply to the results set when querying from the collection"""
filter: BlogFilter
...truncated...
): BlogConnection
}
```
Where the <Table>Filter type enumerates filterable fields and their associated <Type>Filter.
=== "BlogFilter"
```graphql
input BlogFilter {
nodeId: IDFilter
id: IntFilter
name: StringFilter
description: StringFilter
tags: StringListFilter
createdAt: DatetimeFilter
updatedAt: DatetimeFilter
and: [BlogFilter!]
or: [BlogFilter!]
not: BlogFilter
}
```
=== "IntFilter"
```graphql
"""
Boolean expression comparing fields on type "Int"
"""
input IntFilter {
eq: Int
gt: Int
gte: Int
in: [Int!]
lt: Int
lte: Int
neq: Int
is: FilterIs
}
```
=== "StringFilter"
```graphql
"""
Boolean expression comparing fields on type "String"
"""
input StringFilter {
eq: String
gt: String
gte: String
in: [String!]
lt: String
lte: String
neq: String
is: FilterIs
startsWith: String
like: String
ilike: String
regex: String
iregex: String
}
```
=== "StringListFilter"
```graphql
"""
Boolean expression comparing fields on type "StringList"
"""
input StringListFilter {
contains: [String!]
containedBy: [String!]
eq: [String!]
overlaps: [String!]
is: FilterIs
}
```
=== "FilterIs"
```graphql
enum FilterIs {
NULL
NOT_NULL
}
```
The following list shows the operators that may be available on <Type>Filter types.
| Operator | Description |
|---|---|
| eq | Equal To |
| neq | Not Equal To |
| gt | Greater Than |
| gte | Greater Than Or Equal To |
| in | Contained by Value List |
| lt | Less Than |
| lte | Less Than Or Equal To |
| is | Null or Not Null |
| startsWith | Starts with prefix |
| like | Pattern Match. '%' as wildcard |
| ilike | Pattern Match. '%' as wildcard. Case Insensitive |
| regex | POSIX Regular Expression Match |
| iregex | POSIX Regular Expression Match. Case Insensitive |
| contains | Contains. Applies to array columns only. |
| containedBy | Contained in. Applies to array columns only. |
| overlaps | Overlap (have points in common). Applies to array columns only. |
Not all operators are available on every <Type>Filter type. For example, UUIDFilter only supports eq and neq because UUIDs are not ordered.
Example: simple
=== "Query"
graphql { blogCollection( filter: {id: {lt: 3}}, ) { edges { cursor node { id } } } }
=== "Result"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 1
},
"cursor": "WzFd"
},
{
"node": {
"id": 2
},
"cursor": "WzJd"
}
]
}
}
}
```
Example: array column
The contains filter is used to return results where all the elements in the input array appear in the array column.
=== "contains Filter Query"
graphql { blogCollection( filter: {tags: {contains: ["tech", "innovation"]}}, ) { edges { cursor node { id name tags createdAt } } } }
=== "contains Filter Result"
json { "data": { "blogCollection": { "edges": [ { "node": { "id": 1, "name": "A: Blog 1", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["tech", "innovation"] }, "cursor": "WzFd" }, { "node": { "id": 2, "name": "A: Blog 2", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["tech", "innovation", "entrepreneurship"] }, "cursor": "WzJd" } ] } } }
The contains filter can also accept a single scalar.
=== "contains Filter with Scalar Query"
graphql { blogCollection( filter: {tags: {contains: "tech"}}, ) { edges { cursor node { id name tags createdAt } } } }
=== "contains Filter with Scalar Result"
json { "data": { "blogCollection": { "edges": [ { "node": { "id": 1, "name": "A: Blog 1", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["tech", "innovation"] }, "cursor": "WzFd" }, { "node": { "id": 2, "name": "A: Blog 2", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["tech", "innovation", "entrepreneurship"] }, "cursor": "WzJd" } ] } } }
The containedBy filter is used to return results where every element of the array column appears in the input array.
=== "containedBy Filter Query"
graphql { blogCollection( filter: {tags: {containedBy: ["entrepreneurship", "innovation", "tech"]}}, ) { edges { cursor node { id name tags createdAt } } } }
=== "containedBy Filter Result"
json { "data": { "blogCollection": { "edges": [ { "node": { "id": 1, "name": "A: Blog 1", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["tech", "innovation"] }, "cursor": "WzFd" }, { "node": { "id": 3, "name": "A: Blog 3", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["innovation", "entrepreneurship"] }, "cursor": "WzNd" } ] } } }
The containedBy filter can also accept a single scalar. In this case, only results where the only element in the array column is the input scalar are returned.
=== "containedBy Filter with Scalar Query"
graphql { blogCollection( filter: {tags: {containedBy: "travel"}}, ) { edges { cursor node { id name tags createdAt } } } }
=== "containedBy Filter with Scalar Result"
json { "data": { "blogCollection": { "edges": [ { "node": { "id": 4, "name": "A: Blog 4", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["travel"] }, "cursor": "WzPd" } ] } } }
The overlaps filter is used to return results where the array column and the input array have at least one element in common.
=== "overlaps Filter Query"
graphql { blogCollection( filter: {tags: {overlaps: ["tech", "travel"]}}, ) { edges { cursor node { id name tags createdAt } } } }
=== "overlaps Filter Result"
json { "data": { "blogCollection": { "edges": [ { "node": { "id": 1, "name": "A: Blog 1", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["tech", "innovation"] }, "cursor": "WzFd" }, { "node": { "id": 2, "name": "A: Blog 2", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["tech", "innovation", "entrepreneurship"] }, "cursor": "WzJd" }, { "node": { "id": 4, "name": "A: Blog 4", "createdAt": "2023-07-24T04:01:09.882781", "tags": ["travel"] }, "cursor": "WzPd" } ] } } }
Example: and/or
Multiple filters can be combined with and, or and not operators. The and and or operators accept a list of <Type>Filter.
=== "and Filter Query"
graphql { blogCollection( filter: { and: [ {id: {eq: 1}} {name: {eq: "A: Blog 1"}} ] } ) { edges { cursor node { id name description createdAt } } } }
=== "and Filter Result"
json { "data": { "blogCollection": { "edges": [ { "node": { "id": 1, "name": "A: Blog 1", "createdAt": "2023-07-24T04:01:09.882781", "description": "a desc1" }, "cursor": "WzFd" } ] } } }
=== "or Filter Query"
graphql { blogCollection( filter: { or: [ {id: {eq: 1}} {name: {eq: "A: Blog 2"}} ] } ) { edges { cursor node { id name description createdAt } } } }
=== "or Filter Result"
json { "data": { "blogCollection": { "edges": [ { "node": { "id": 1, "name": "A: Blog 1", "createdAt": "2023-07-24T04:01:09.882781", "description": "a desc1" }, "cursor": "WzFd" }, { "node": { "id": 2, "name": "A: Blog 2", "createdAt": "2023-07-24T04:01:09.882781", "description": "a desc2" }, "cursor": "WzJd" } ] } } }
Example: not
not accepts a single <Type>Filter.
=== "not Filter Query"
graphql { blogCollection( filter: { not: {id: {eq: 1}} } ) { edges { cursor node { id name description createdAt } } } }
=== "not Filter Result"
json { "data": { "blogCollection": { "edges": [ { "node": { "id": 2, "name": "A: Blog 2", "createdAt": "2023-07-24T04:01:09.882781", "description": "a desc2" }, "cursor": "WzJd" }, { "node": { "id": 3, "name": "A: Blog 3", "createdAt": "2023-07-24T04:01:09.882781", "description": "a desc3" }, "cursor": "WzNd" }, { "node": { "id": 4, "name": "B: Blog 3", "createdAt": "2023-07-24T04:01:09.882781", "description": "b desc1" }, "cursor": "WzRd" } ] } } }
Example: nested composition
The and, or and not operators can be arbitrarily nested inside each other.
=== "Query"
graphql { blogCollection( filter: { or: [ { id: { eq: 1 } } { id: { eq: 2 } } { and: [{ id: { eq: 3 }, not: { name: { eq: "A: Blog 2" } } }] } ] } ) { edges { cursor node { id name description createdAt } } } }
=== "Result"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 1,
"name": "A: Blog 1",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc1"
},
"cursor": "WzFd"
},
{
"node": {
"id": 2,
"name": "A: Blog 2",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc2"
},
"cursor": "WzJd"
},
{
"node": {
"id": 3,
"name": "A: Blog 3",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc3"
},
"cursor": "WzNd"
}
]
}
}
}
```
Example: empty
Empty filters are ignored, i.e. they behave as if the operator was not specified at all.
=== "Query"
graphql { blogCollection( filter: { and: [], or: [], not: {} } ) { edges { cursor node { id name description createdAt } } } }
=== "Result"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 1,
"name": "A: Blog 1",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc1"
},
"cursor": "WzFd"
},
{
"node": {
"id": 2,
"name": "A: Blog 2",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc2"
},
"cursor": "WzJd"
},
{
"node": {
"id": 3,
"name": "A: Blog 3",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc3"
},
"cursor": "WzNd"
},
{
"node": {
"id": 4,
"name": "B: Blog 3",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "b desc1"
},
"cursor": "WzRd"
}
]
}
}
}
```
Example: implicit and
Multiple column filters at the same level will be implicitly combined with boolean and. In the following example the id: {eq: 1} and name: {eq: "A: Blog 1"} will be anded.
=== "Query"
graphql { blogCollection( filter: { # Equivalent to not: { and: [{id: {eq: 1}}, {name: {eq: "A: Blog 1"}}]} not: { id: {eq: 1} name: {eq: "A: Blog 1"} } } ) { edges { cursor node { id name description createdAt } } } }
=== "Result"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 2,
"name": "A: Blog 2",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc2"
},
"cursor": "WzJd"
},
{
"node": {
"id": 3,
"name": "A: Blog 3",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc3"
},
"cursor": "WzNd"
},
{
"node": {
"id": 4,
"name": "B: Blog 3",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "b desc1"
},
"cursor": "WzRd"
}
]
}
}
}
```
This means that an and filter can be often be simplified. In the following example all queries are equivalent and produce the same result.
=== "Original and Query"
graphql { blogCollection( filter: { and: [ {id: {gt: 0}} {id: {lt: 2}} {name: {eq: "A: Blog 1"}} ] } ) { edges { cursor node { id name description createdAt } } } }
=== "Simplified and Query"
graphql { blogCollection( filter: { id: {gt: 0} id: {lt: 2} name: {eq: "A: Blog 1"} } ) { edges { cursor node { id name description createdAt } } } }
=== "Even More Simplified Query"
graphql { blogCollection( filter: { id: {gt: 0, lt: 2} name: {eq: "A: Blog 1"} } ) { edges { cursor node { id name description createdAt } } } }
=== "Result"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 2,
"name": "A: Blog 2",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc2"
},
"cursor": "WzJd"
},
{
"node": {
"id": 3,
"name": "A: Blog 3",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "a desc3"
},
"cursor": "WzNd"
},
{
"node": {
"id": 4,
"name": "B: Blog 3",
"createdAt": "2023-07-24T04:01:09.882781",
"description": "b desc1"
},
"cursor": "WzRd"
}
]
}
}
}
```
Be aware that the above simplification only works for the and operator. If you try it with an or operator it will behave like an and.
=== "Query"
graphql { blogCollection( filter: { # This is really an `and` in `or`'s clothing or: { id: {eq: 1} name: {eq: "A: Blog 2"} } } ) { edges { cursor node { id name description createdAt } } } }
=== "Result"
json { "data": { "blogCollection": { "edges": [] } } }
This is because according to the rules of GraphQL list input coercion, if a value passed to an input of list type is not a list, then it is coerced to a list of a single item. So in the above example or: {id: {eq: 1}, name: {eq: "A: Blog 2}} will be coerced into or: [{id: {eq: 1}, name: {eq: "A: Blog 2}}] which is equivalent to or: [and: [{id: {eq: 1}}, {name: {eq: "A: Blog 2}}}] due to implicit anding.
!!! note
Avoid naming your columns `and`, `or` or `not`. If you do, the corresponding filter operator will not be available for use.
The and, or and not operators also work with update and delete mutations.
The default order of results is defined by the underlying table's primary key column in ascending order. That default can be overridden by passing an array of <Table>OrderBy to the collection's orderBy argument.
=== "QueryType"
```graphql
type Query {
blogCollection(
"""Sort order to apply to the collection"""
orderBy: [BlogOrderBy!]
...truncated...
): BlogConnection
}
```
=== "BlogOrderBy"
```graphql
input BlogOrderBy {
id: OrderByDirection
name: OrderByDirection
description: OrderByDirection
createdAt: OrderByDirection
updatedAt: OrderByDirection
}
```
=== "OrderByDirection"
```graphql
"""Defines a per-field sorting order"""
enum OrderByDirection {
"""Ascending order, nulls first"""
AscNullsFirst
"""Ascending order, nulls last"""
AscNullsLast
"""Descending order, nulls first"""
DescNullsFirst
"""Descending order, nulls last"""
DescNullsLast
}
```
Example
=== "Query"
```graphql
{
blogCollection(
orderBy: [{id: DescNullsLast}]
) {
edges {
node {
id
}
}
}
}
```
=== "Result"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"id": 4
}
},
{
"node": {
"id": 3
}
},
{
"node": {
"id": 2
}
},
{
"node": {
"id": 1
}
}
]
}
}
}
```
Note, only one key value pair may be provided to each element of the input array. For example, [{name: AscNullsLast}, {id: AscNullFirst}] is valid. Passing multiple key value pairs in a single element of the input array e.g. [{name: AscNullsLast, id: AscNullFirst}], is invalid.
The Mutation type is the entrypoint for mutations/edits.
Each table has top level entry in the Mutation type for inserting insertInto<Table>Collection, updating update<Table>Collection and deleting deleteFrom<Table>Collection.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null,
description varchar(255),
"createdAt" timestamp not null default now(),
"updatedAt" timestamp
);=== "MutationType"
```graphql
"""The root type for creating and mutating data"""
type Mutation {
"""Adds one or more `BlogInsertResponse` records to the collection"""
insertIntoBlogCollection(
"""Records to add to the Blog collection"""
objects: [BlogInsertInput!]!
): BlogInsertResponse
"""Updates zero or more records in the collection"""
updateBlogCollection(
"""
Fields that are set will be updated for all records matching the `filter`
"""
set: BlogUpdateInput!
"""Restricts the mutation's impact to records matching the critera"""
filter: BlogFilter
"""
The maximum number of records in the collection permitted to be affected
"""
atMost: Int! = 1
): BlogUpdateResponse!
"""Deletes zero or more records from the collection"""
deleteFromBlogCollection(
"""Restricts the mutation's impact to records matching the critera"""
filter: BlogFilter
"""
The maximum number of records in the collection permitted to be affected
"""
atMost: Int! = 1
): BlogDeleteResponse!
}
```
To add records to a collection, use the insertInto<Table>Collection field on the Mutation type.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null,
description varchar(255),
"createdAt" timestamp not null default now(),
"updatedAt" timestamp
);GraphQL Types === "MutationType"
```graphql
"""The root type for creating and mutating data"""
type Mutation {
"""Adds one or more `BlogInsertResponse` records to the collection"""
insertIntoBlogCollection(
"""Records to add to the Blog collection"""
objects: [BlogInsertInput!]!
): BlogInsertResponse
}
```
=== "BlogInsertInput"
```graphql
input BlogInsertInput {
name: String
description: String
createdAt: Datetime
updatedAt: Datetime
}
```
=== "BlogInsertResponse"
```graphql
type BlogInsertResponse {
"""Count of the records impacted by the mutation"""
affectedCount: Int!
"""Array of records impacted by the mutation"""
records: [Blog!]!
}
```
Where elements in the objects array are inserted into the underlying table.
Example
=== "Query"
graphql mutation { insertIntoBlogCollection( objects: [ {name: "foo"}, {name: "bar"}, ] ) { affectedCount records { id name } } }
=== "Result"
```json
{
"data": {
"insertIntoBlogCollection": {
"records": [
{
"id": 1,
"name": "foo"
},
{
"id": 2,
"name": "bar"
}
],
"affectedCount": 2
}
}
}
```
To update records in a collection, use the update<Table>Collection field on the Mutation type.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null,
description varchar(255),
"createdAt" timestamp not null default now(),
"updatedAt" timestamp
);GraphQL Types === "MutationType"
```graphql
"""The root type for creating and mutating data"""
type Mutation {
"""Updates zero or more records in the collection"""
updateBlogCollection(
"""
Fields that are set will be updated for all records matching the `filter`
"""
set: BlogUpdateInput!
"""Restricts the mutation's impact to records matching the critera"""
filter: BlogFilter
"""
The maximum number of records in the collection permitted to be affected
"""
atMost: Int! = 1
): BlogUpdateResponse!
}
```
=== "BlogUpdateInput"
```graphql
input BlogUpdateInput {
name: String
description: String
createdAt: Datetime
updatedAt: Datetime
}
```
=== "BlogUpdateResponse"
```graphql
type BlogUpdateResponse {
"""Count of the records impacted by the mutation"""
affectedCount: Int!
"""Array of records impacted by the mutation"""
records: [Blog!]!
}
```
Where the set argument is a key value pair describing the values to update, filter controls which records should be updated, and atMost restricts the maximum number of records that may be impacted. If the number of records impacted by the mutation exceeds the atMost parameter the operation will return an error.
Example
=== "Query"
graphql mutation { updateBlogCollection( set: {name: "baz"} filter: {id: {eq: 1}} ) { affectedCount records { id name } } }
=== "Result"
```json
{
"data": {
"updateBlogCollection": {
"records": [
{
"id": 1,
"name": "baz"
}
],
"affectedCount": 1
}
}
}
```
To remove records from a collection, use the deleteFrom<Table>Collection field on the Mutation type.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null,
description varchar(255),
"createdAt" timestamp not null default now(),
"updatedAt" timestamp
);GraphQL Types === "MutationType"
```graphql
"""The root type for creating and mutating data"""
type Mutation {
"""Deletes zero or more records from the collection"""
deleteFromBlogCollection(
"""Restricts the mutation's impact to records matching the critera"""
filter: BlogFilter
"""
The maximum number of records in the collection permitted to be affected
"""
atMost: Int! = 1
): BlogDeleteResponse!
}
```
=== "BlogFilter"
```graphql
input BlogFilter {
id: IntFilter
name: StringFilter
description: StringFilter
createdAt: DatetimeFilter
updatedAt: DatetimeFilter
and: [BlogFilter!]
or: [BlogFilter!]
not: BlogFilter
}
```
=== "BlogDeleteResponse"
```graphql
type BlogDeleteResponse {
"""Count of the records impacted by the mutation"""
affectedCount: Int!
"""Array of records impacted by the mutation"""
records: [Blog!]!
}
```
Where filter controls which records should be deleted and atMost restricts the maximum number of records that may be deleted. If the number of records impacted by the mutation exceeds the atMost parameter the operation will return an error.
Example === "Query"
```graphql
mutation {
deleteFromBlogCollection(
filter: {id: {eq: 1}}
) {
affectedCount
records {
id
name
}
}
}
```
=== "Result"
```json
{
"data": {
"deleteFromBlogCollection": {
"records": [
{
"id": 1,
"name": "baz"
}
],
"affectedCount": 1
}
}
}
```
The base GraphQL type for every table with a primary key is automatically assigned a nodeId: ID! field. That value, can be passed to the node entrypoint of the Query type to retrieve its other fields. nodeId may also be used as a caching key.
!!!note "relay support"
By default relay expects the ID field for types to have the name id. pg_graphql uses nodeId by default to avoid conflicting with user defined id columns. You can configure relay to work with pg_graphql's nodeId field with relay's nodeInterfaceIdField option. More info available here.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null
);GraphQL Types === "Blog"
```sql
type Blog {
nodeId: ID! # this field
id: Int!
name: String!
}
```
Relationships between collections in the Graph are derived from foreign keys.
A foreign key on table A referencing table B defines a one-to-many relationship from table A to table B.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null
);
create table "BlogPost"(
id serial primary key,
"blogId" integer not null references "Blog"(id),
title varchar(255) not null,
body varchar(10000)
);GraphQL Types === "Blog"
```sql
type Blog {
# globally unique identifier
nodeId: ID!
id: Int!
name: String!
description: String
blogPostCollection(
"""Query the first `n` records in the collection"""
first: Int
"""Query the last `n` records in the collection"""
last: Int
"""Query values in the collection before the provided cursor"""
before: Cursor
"""Query values in the collection after the provided cursor"""
after: Cursor
"""
Skip n values from the after cursor. Alternative to cursor pagination. Backward pagination not supported.
"""
offset: Int
"""Filters to apply to the results set when querying from the collection"""
filter: BlogPostFilter
"""Sort order to apply to the collection"""
orderBy: [BlogPostOrderBy!]
): BlogPostConnection
}
```
Where blogPostCollection exposes the full Query interface to BlogPosts.
Example === "Query"
```graphql
{
blogCollection {
edges {
node {
name
blogPostCollection {
edges {
node {
id
title
}
}
}
}
}
}
}
```
=== "Result"
```json
{
"data": {
"blogCollection": {
"edges": [
{
"node": {
"name": "pg_graphql blog",
"blogPostCollection": {
"edges": [
{
"node": {
"id": 2,
"title": "fIr3t p0sT"
}
},
{
"node": {
"id": 3,
"title": "graphql with postgres"
}
}
]
}
}
}
]
}
}
}
```
A foreign key on table A referencing table B defines a many-to-one relationship from table B to table A.
SQL Setup
create table "Blog"(
id serial primary key,
name varchar(255) not null
);
create table "BlogPost"(
id serial primary key,
"blogId" integer not null references "Blog"(id),
title varchar(255) not null,
body varchar(10000)
);GraphQL Types === "BlogPost"
```sql
type BlogPost {
nodeId: ID!
id: Int!
blogId: Int!
title: String!
body: String
blog: Blog
}
```
Where blog exposes the Blog record associated with the BlogPost.
=== "Query"
```graphql
{
blogPostCollection {
edges {
node {
title
blog {
name
}
}
}
}
}
```
=== "Result"
```json
{
"data": {
"blogPostCollection": {
"edges": [
{
"node": {
"blog": {
"name": "pg_graphql blog"
},
"title": "fIr3t p0sT"
}
},
{
"node": {
"blog": {
"name": "pg_graphql blog"
},
"title": "graphql with postgres"
}
}
]
}
}
}
```
A one-to-one relationship is defined by a foreign key on table A referencing table B where the columns making up the foreign key on table A are unique.
SQL Setup
create table "EmailAddress"(
id serial primary key,
address text unique not null
);
create table "Employee"(
id serial primary key,
name text not null,
email_address_id int unique references "EmailAddress"(id)
);GraphQL Types === "Employee"
```sql
type Employee {
nodeId: ID!
id: Int!
name: String!
emailAddressId: Int
emailAddress: EmailAddress
}
```
=== "EmailAddress"
sql type EmailAddress { nodeId: ID! id: Int! address: String! employee: Employee }
Example === "Query"
```graphql
{
employeeCollection {
edges {
node {
name
emailAddress {
address
employee {
name
}
}
}
}
}
}
```
=== "Result"
```json
{
"data": {
"employeeCollection": {
"edges": [
{
"node": {
"name": "Foo Barington",
"emailAddress": {
"address": "[email protected]",
"employee": {
"name": "Foo Barington"
}
}
}
}
]
}
}
}
```
Due to differences among the types supported by PostgreSQL, JSON, and GraphQL, pg_graphql adds several new Scalar types to handle PostgreSQL builtins that require special handling.
pg_graphql serializes json and jsonb data types as String under the custom scalar name JSON.
scalar JSONExample
Given the setup
=== "SQL" ```sql create table "User"( id bigserial primary key, config jsonb );
insert into "User"(config)
values (jsonb_build_object('palette', 'dark-mode'));
```
=== "GraphQL"
sql type User { nodeId: ID! id: BigInt! config: JSON }
The query
{
userCollection {
edges {
node {
config
}
}
}
}The returns the following data. Note that config is serialized as a string
{
"data": {
"userCollection": {
"edges": [
{
"node": {
"config": "{\"palette\": \"dark-mode\"}"
}
}
]
}
}
}Use serialized JSON strings when updating or inserting JSON fields via the GraphQL API.
JSON does not currently support filtering.
PostgreSQL bigint and bigserial types are 64 bit integers. In contrast, JSON supports 32 bit integers.
Since PostgreSQL bigint values may be outside the min/max range allowed by JSON, they are represented in the GraphQL schema as BigInts and values are serialized as strings.
scalar BigInt
input BigIntFilter {
eq: BigInt
gt: BigInt
gte: BigInt
in: [BigInt!]
lt: BigInt
lte: BigInt
neq: BigInt
is: FilterIs
}Example
Given the setup
=== "SQL" ```sql create table "Person"( id bigserial primary key, name text );
insert into "Person"(name)
values ('J. Bazworth');
```
=== "GraphQL"
sql type Person { nodeId: ID! id: BigInt! name: String }
The query
{
personCollection {
edges {
node {
id
name
}
}
}
}The returns the following data. Note that id is serialized as a string
{
"data": {
"personCollection": {
"edges": [
{
"node": {
"id": "1",
"name": "Foo Barington",
}
}
]
}
}
}PostgreSQL's numeric type supports arbitrary precision floating point values. JSON's float is limited to 64-bit precision.
Since a PostgreSQL numeric may require more precision than can be handled by JSON, numeric types are represented in the GraphQL schema as BigFloat and values are serialized as strings.
scalar BigFloat
input BigFloatFilter {
eq: BigFloat
gt: BigFloat
gte: BigFloat
in: [BigFloat!]
lt: BigFloat
lte: BigFloat
neq: BigFloat
is: FilterIs
}Example
Given the SQL setup
create table "GeneralLedger"(
id serial primary key,
amount numeric(10,2)
);
insert into "GeneralLedger"(amount)
values (22.15);The query
{
generalLedgerCollection {
edges {
node {
id
amount
}
}
}
}The returns the following data. Note that amount is serialized as a string
{
"data": {
"generalLedgerCollection": {
"edges": [
{
"node": {
"id": 1,
"amount": "22.15",
}
}
]
}
}
}PostgreSQL's type system is extensible and not all types handle all operations e.g. filtering with like. To account for these, pg_graphql introduces a scalar Opaque type. The Opaque type uses PostgreSQL's to_json method to serialize values. That allows complex or unknown types to be included in the schema by delegating handling to the client.
scalar Opaque
input OpaqueFilter {
eq: Opaque
is: FilterIs
}