Scalar types in Amazon AppSync - Amazon AppSync
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Scalar types in Amazon AppSync

A GraphQL object type has a name and fields, and those fields can have sub-fields. Ultimately, an object type's fields must resolve to scalar types, which represent the leaves of the query. For more information about object types and scalars, see Schemas and types on the GraphQL website.

In addition to the default set of GraphQL scalars, Amazon AppSync also lets you use the service-defined scalars that start with the Amazon prefix. Amazon AppSync doesn't support the creation of user-defined (custom) scalars. You must use either the default or Amazon scalars.

You cannot use Amazon as a prefix for custom object types.

The following section is a reference for schema typing.

Default scalars

GraphQL defines the following default scalars:

ID

A unique identifier for an object. This scalar is serialized like a String but isn't meant to be human-readable.

String

A UTF-8 character sequence.

Int

An integer value between -(231) and 231-1.

Float

An IEEE 754 floating point value.

Boolean

A Boolean value, either true or false.

Amazon AppSync scalars

Amazon AppSync defines the following scalars:

AWSDate

An extended ISO 8601 date string in the format YYYY-MM-DD.

AWSTime

An extended ISO 8601 time string in the format hh:mm:ss.sss.

AWSDateTime

An extended ISO 8601 date and time string in the format YYYY-MM-DDThh:mm:ss.sssZ.

Note

The AWSDate, AWSTime, and AWSDateTime scalars can optionally include a time zone offset. For example, the values 1970-01-01Z, 1970-01-01-07:00, and 1970-01-01+05:30 are all valid for AWSDate. The time zone offset must be either Z (UTC) or an offset in hours and minutes (and, optionally, seconds). For example, ±hh:mm:ss. The seconds field in the time zone offset is considered valid even though it's not part of the ISO 8601 standard.

AWSTimestamp

An integer value representing the number of seconds before or after 1970-01-01-T00:00Z.

AWSEmail

An email address in the format local-part@domain-part as defined by RFC 822.

AWSJSON

A JSON string. Any valid JSON construct is automatically parsed and loaded in the resolver code as maps, lists, or scalar values rather than as the literal input strings. Unquoted strings or otherwise invalid JSON result in a GraphQL validation error.

AWSPhone

A phone number. This value is stored as a string. Phone numbers can contain either spaces or hyphens to separate digit groups. Phone numbers without a country code are assumed to be US/North American numbers adhering to the North American Numbering Plan (NANP).

AWSURL

A URL as defined by RFC 1738. For example, https://www.amazon.com/dp/B000NZW3KC/ or mailto:example@example.com. URLs must contain a schema (http, mailto) and can't contain two forward slashes (//) in the path part.

AWSIPAddress

A valid IPv4 or IPv6 address. IPv4 addresses are expected in quad-dotted notation (123.12.34.56). IPv6 addresses are expected in non-bracketed, colon-separated format (1a2b:3c4b::1234:4567). You can include an optional CIDR suffix (123.45.67.89/16) to indicate subnet mask.

Schema usage example

The following example GraphQL schema uses all of the custom scalars as an "object" and shows the resolver request and response templates for basic put, get, and list operations. Finally, the example shows how you can use this when running queries and mutations.

type Mutation { putObject( email: AWSEmail, json: AWSJSON, date: AWSDate, time: AWSTime, datetime: AWSDateTime, timestamp: AWSTimestamp, url: AWSURL, phoneno: AWSPhone, ip: AWSIPAddress ): Object } type Object { id: ID! email: AWSEmail json: AWSJSON date: AWSDate time: AWSTime datetime: AWSDateTime timestamp: AWSTimestamp url: AWSURL phoneno: AWSPhone ip: AWSIPAddress } type Query { getObject(id: ID!): Object listObjects: [Object] } schema { query: Query mutation: Mutation }

Here's what a request template for putObject might look like. A putObject uses a PutItem operation to create or update an item in your Amazon DynamoDB table. Note that this code snippet doesn't have a configured Amazon DynamoDB table as a data source. This is being used as an example only:

{ "version" : "2017-02-28", "operation" : "PutItem", "key" : { "id": $util.dynamodb.toDynamoDBJson($util.autoId()), }, "attributeValues" : $util.dynamodb.toMapValuesJson($ctx.args) }

The response template for putObject returns the results:

$util.toJson($ctx.result)

Here's what a request template for getObject might look like. A getObject uses a GetItem operation to return a set of attributes for the item given the primary key. Note that this code snippet doesn't have a configured Amazon DynamoDB table as a data source. This is being used as an example only:

{ "version": "2017-02-28", "operation": "GetItem", "key": { "id": $util.dynamodb.toDynamoDBJson($ctx.args.id), } }

The response template for getObject returns the results:

$util.toJson($ctx.result)

Here's what a request template for listObjects might look like. A listObjects uses a Scan operation to return one or more items and attributes. Note that this code snippet doesn't have a configured Amazon DynamoDB table as a data source. This is being used as an example only:

{ "version" : "2017-02-28", "operation" : "Scan", }

The response template for listObjects returns the results:

$util.toJson($ctx.result.items)

The following are some examples of using this schema with GraphQL queries:

mutation CreateObject { putObject(email: "example@example.com" json: "{\"a\":1, \"b\":3, \"string\": 234}" date: "1970-01-01Z" time: "12:00:34." datetime: "1930-01-01T16:00:00-07:00" timestamp: -123123 url:"https://amazon.com" phoneno: "+1 555 764 4377" ip: "127.0.0.1/8" ) { id email json date time datetime url timestamp phoneno ip } } query getObject { getObject(id:"0d97daf0-48e6-4ffc-8d48-0537e8a843d2"){ email url timestamp phoneno ip } } query listObjects { listObjects { json date time datetime } }