Section 6 -- Execution.md

Execution

GraphQL generates a response from a request via execution.

A request for execution consists of a few pieces of information:

• The schema to use, typically solely provided by the GraphQL service.
• A {Document} which must contain GraphQL {OperationDefinition} and may contain {FragmentDefinition}.
• Optionally: The name of the Operation in the Document to execute.
• Optionally: Values for any Variables defined by the Operation.
• An initial value corresponding to the root type being executed. Conceptually, an initial value represents the "universe" of data available via a GraphQL Service. It is common for a GraphQL Service to always use the same initial value for every request.

Given this information, the result of {ExecuteRequest()} produces the response, to be formatted according to the Response section below.

Executing Requests

To execute a request, the executor must have a parsed {Document} and a selected operation name to run if the document defines multiple operations, otherwise the document is expected to only contain a single operation. The result of the request is determined by the result of executing this operation according to the "Executing Operations” section below.

ExecuteRequest(schema, document, operationName, variableValues, initialValue):

• Let {operation} be the result of {GetOperation(document, operationName)}.
• Let {coercedVariableValues} be the result of {CoerceVariableValues(schema, operation, variableValues)}.
• If {operation} is a query operation:
  • Return {ExecuteQuery(operation, schema, coercedVariableValues, initialValue)}.
• Otherwise if {operation} is a mutation operation:
  • Return {ExecuteMutation(operation, schema, coercedVariableValues, initialValue)}.
• Otherwise if {operation} is a subscription operation:
  • Return {Subscribe(operation, schema, coercedVariableValues, initialValue)}.

GetOperation(document, operationName):

• If {operationName} is {null}:
  • If {document} contains exactly one operation.
    • Return the Operation contained in the {document}.
  • Otherwise raise a request error requiring {operationName}.
• Otherwise:
  • Let {operation} be the Operation named {operationName} in {document}.
  • If {operation} was not found, raise a request error.
  • Return {operation}.

Validating Requests

As explained in the Validation section, only requests which pass all validation rules should be executed. If validation errors are known, they should be reported in the list of "errors" in the response and the request must fail without execution.

Typically validation is performed in the context of a request immediately before execution, however a GraphQL service may execute a request without immediately validating it if that exact same request is known to have been validated before. A GraphQL service should only execute requests which at some point were known to be free of any validation errors, and have since not changed.

For example: the request may be validated during development, provided it does not later change, or a service may validate a request once and memoize the result to avoid validating the same request again in the future.

Coercing Variable Values

If the operation has defined any variables, then the values for those variables need to be coerced using the input coercion rules of variable's declared type. If a request error is encountered during input coercion of variable values, then the operation fails without execution.

CoerceVariableValues(schema, operation, variableValues):

• Let {coercedValues} be an empty unordered Map.
• Let {variableDefinitions} be the variables defined by {operation}.
• For each {variableDefinition} in {variableDefinitions}:
  • Let {variableName} be the name of {variableDefinition}.
  • Let {variableType} be the expected type of {variableDefinition}.
  • Assert: {IsInputType(variableType)} must be {true}.
  • Let {defaultValue} be the default value for {variableDefinition}.
  • Let {hasValue} be {true} if {variableValues} provides a value for the name {variableName}.
  • Let {value} be the value provided in {variableValues} for the name {variableName}.
  • If {hasValue} is not {true} and {defaultValue} exists (including {null}):
    • Add an entry to {coercedValues} named {variableName} with the value {defaultValue}.
  • Otherwise if {variableType} is a Non-Nullable type, and either {hasValue} is not {true} or {value} is {null}, raise a request error.
  • Otherwise if {hasValue} is true:
    • If {value} is {null}:
      • Add an entry to {coercedValues} named {variableName} with the value {null}.
    • Otherwise:
      • If {value} cannot be coerced according to the input coercion rules of {variableType}, raise a request error.
      • Let {coercedValue} be the result of coercing {value} according to the input coercion rules of {variableType}.
      • Add an entry to {coercedValues} named {variableName} with the value {coercedValue}.
• Return {coercedValues}.

Note: This algorithm is very similar to {CoerceArgumentValues()}.

Executing Operations

The type system, as described in the "Type System" section of the spec, must provide a query root operation type. If mutations or subscriptions are supported, it must also provide a mutation or subscription root operation type, respectively.

Query

If the operation is a query, the result of the operation is the result of executing the operation’s top level selection set with the query root operation type.

An initial value may be provided when executing a query operation.

ExecuteQuery(query, schema, variableValues, initialValue):

• Let {queryType} be the root Query type in {schema}.
• Assert: {queryType} is an Object type.
• Let {selectionSet} be the top level Selection Set in {query}.
• Let {data} be the result of running {ExecuteSelectionSet(selectionSet, queryType, initialValue, variableValues)} normally (allowing parallelization).
• Let {errors} be any field errors produced while executing the selection set.
• Return an unordered map containing {data} and {errors}.

Mutation

If the operation is a mutation, the result of the operation is the result of executing the operation’s top level selection set on the mutation root object type. This selection set should be executed serially.

It is expected that the top level fields in a mutation operation perform side-effects on the underlying data system. Serial execution of the provided mutations ensures against race conditions during these side-effects.

ExecuteMutation(mutation, schema, variableValues, initialValue):

• Let {mutationType} be the root Mutation type in {schema}.
• Assert: {mutationType} is an Object type.
• Let {selectionSet} be the top level Selection Set in {mutation}.
• Let {data} be the result of running {ExecuteSelectionSet(selectionSet, mutationType, initialValue, variableValues)} serially.
• Let {errors} be any field errors produced while executing the selection set.
• Return an unordered map containing {data} and {errors}.

Subscription

If the operation is a subscription, the result is an event stream called the "Response Stream" where each event in the event stream is the result of executing the operation for each new event on an underlying "Source Stream".

Executing a subscription operation creates a persistent function on the service that maps an underlying Source Stream to a returned Response Stream.

Subscribe(subscription, schema, variableValues, initialValue):

• Let {sourceStream} be the result of running {CreateSourceEventStream(subscription, schema, variableValues, initialValue)}.
• Let {responseStream} be the result of running {MapSourceToResponseEvent(sourceStream, subscription, schema, variableValues)}
• Return {responseStream}.

Note: In large scale subscription systems, the {Subscribe()} and {ExecuteSubscriptionEvent()} algorithms may be run on separate services to maintain predictable scaling properties. See the section below on Supporting Subscriptions at Scale.

As an example, consider a chat application. To subscribe to new messages posted to the chat room, the client sends a request like so:

subscription NewMessages {
  newMessage(roomId: 123) {
    sender
    text
  }
}

While the client is subscribed, whenever new messages are posted to chat room with ID "123", the selection for "sender" and "text" will be evaluated and published to the client, for example:

{
  "data": {
    "newMessage": {
      "sender": "Hagrid",
      "text": "You're a wizard!"
    }
  }
}

The "new message posted to chat room" could use a "Pub-Sub" system where the chat room ID is the "topic" and each "publish" contains the sender and text.

Event Streams

An event stream represents a sequence of discrete events over time which can be observed. As an example, a "Pub-Sub" system may produce an event stream when "subscribing to a topic", with an event occurring on that event stream for each "publish" to that topic. Event streams may produce an infinite sequence of events or may complete at any point. Event streams may complete in response to an error or simply because no more events will occur. An observer may at any point decide to stop observing an event stream by cancelling it, after which it must receive no more events from that event stream.

Supporting Subscriptions at Scale

Supporting subscriptions is a significant change for any GraphQL service. Query and mutation operations are stateless, allowing scaling via cloning of GraphQL service instances. Subscriptions, by contrast, are stateful and require maintaining the GraphQL document, variables, and other context over the lifetime of the subscription.

Consider the behavior of your system when state is lost due to the failure of a single machine in a service. Durability and availability may be improved by having separate dedicated services for managing subscription state and client connectivity.

Delivery Agnostic

GraphQL subscriptions do not require any specific serialization format or transport mechanism. Subscriptions specifies algorithms for the creation of a stream, the content of each payload on that stream, and the closing of that stream. There are intentionally no specifications for message acknowledgement, buffering, resend requests, or any other quality of service (QoS) details. Message serialization, transport mechanisms, and quality of service details should be chosen by the implementing service.

Source Stream

A Source Stream represents the sequence of events, each of which will trigger a GraphQL execution corresponding to that event. Like field value resolution, the logic to create a Source Stream is application-specific.

CreateSourceEventStream(subscription, schema, variableValues, initialValue):

• Let {subscriptionType} be the root Subscription type in {schema}.
• Assert: {subscriptionType} is an Object type.
• Let {selectionSet} be the top level Selection Set in {subscription}.
• Let {groupedFieldSet} be the result of {CollectFields(subscriptionType, selectionSet, variableValues)}.
• If {groupedFieldSet} does not have exactly one entry, raise a request error.
• Let {fields} be the value of the first entry in {groupedFieldSet}.
• Let {fieldName} be the name of the first entry in {fields}. Note: This value is unaffected if an alias is used.
• Let {field} be the first entry in {fields}.
• Let {argumentValues} be the result of {CoerceArgumentValues(subscriptionType, field, variableValues)}
• Let {fieldStream} be the result of running {ResolveFieldEventStream(subscriptionType, initialValue, fieldName, argumentValues)}.
• Return {fieldStream}.

ResolveFieldEventStream(subscriptionType, rootValue, fieldName, argumentValues):

• Let {resolver} be the internal function provided by {subscriptionType} for determining the resolved event stream of a subscription field named {fieldName}.
• Return the result of calling {resolver}, providing {rootValue} and {argumentValues}.

Note: This {ResolveFieldEventStream()} algorithm is intentionally similar to {ResolveFieldValue()} to enable consistency when defining resolvers on any operation type.

Response Stream

Each event in the underlying Source Stream triggers execution of the subscription selection set using that event as a root value.

MapSourceToResponseEvent(sourceStream, subscription, schema, variableValues):

• Return a new event stream {responseStream} which yields events as follows:
• For each {event} on {sourceStream}:
  • Let {response} be the result of running {ExecuteSubscriptionEvent(subscription, schema, variableValues, event)}.
  • Yield an event containing {response}.
• When {responseStream} completes: complete this event stream.

ExecuteSubscriptionEvent(subscription, schema, variableValues, initialValue):

• Let {subscriptionType} be the root Subscription type in {schema}.
• Assert: {subscriptionType} is an Object type.
• Let {selectionSet} be the top level Selection Set in {subscription}.
• Let {data} be the result of running {ExecuteSelectionSet(selectionSet, subscriptionType, initialValue, variableValues)} normally (allowing parallelization).
• Let {errors} be any field errors produced while executing the selection set.
• Return an unordered map containing {data} and {errors}.

Note: The {ExecuteSubscriptionEvent()} algorithm is intentionally similar to {ExecuteQuery()} since this is how each event result is produced.

Unsubscribe

Unsubscribe cancels the Response Stream when a client no longer wishes to receive payloads for a subscription. This may in turn also cancel the Source Stream. This is also a good opportunity to clean up any other resources used by the subscription.

Unsubscribe(responseStream):

• Cancel {responseStream}

Executing Selection Sets

To execute a selection set, the object value being evaluated and the object type need to be known, as well as whether it must be executed serially, or may be executed in parallel.

First, the selection set is turned into a grouped field set; then, each represented field in the grouped field set produces an entry into a response map.

ExecuteSelectionSet(selectionSet, objectType, objectValue, variableValues):

• Let {groupedFieldSet} be the result of {CollectFields(objectType, selectionSet, variableValues)}.
• Initialize {resultMap} to an empty ordered map.
• For each {groupedFieldSet} as {responseKey} and {fields}:
  • Let {fieldName} be the name of the first entry in {fields}. Note: This value is unaffected if an alias is used.
  • Let {fieldType} be the return type defined for the field {fieldName} of {objectType}.
  • If {fieldType} is defined:
    • Let {responseValue} be {ExecuteField(objectType, objectValue, fieldType, fields, variableValues)}.
    • Set {responseValue} as the value for {responseKey} in {resultMap}.
• Return {resultMap}.

Note: {resultMap} is ordered by which fields appear first in the operation. This is explained in greater detail in the Field Collection section below.

Errors and Non-Null Fields

If during {ExecuteSelectionSet()} a field with a non-null {fieldType} raises a field error then that error must propagate to this entire selection set, either resolving to {null} if allowed or further propagated to a parent field.

If this occurs, any sibling fields which have not yet executed or have not yet yielded a value may be cancelled to avoid unnecessary work.

Note: See Handling Field Errors for more about this behavior.

Normal and Serial Execution

Normally the executor can execute the entries in a grouped field set in whatever order it chooses (normally in parallel). Because the resolution of fields other than top-level mutation fields must always be side effect-free and idempotent, the execution order must not affect the result, and hence the service has the freedom to execute the field entries in whatever order it deems optimal.

For example, given the following grouped field set to be executed normally:

{
  birthday {
    month
  }
  address {
    street
  }
}

A valid GraphQL executor can resolve the four fields in whatever order it chose (however of course birthday must be resolved before month, and address before street).

When executing a mutation, the selections in the top most selection set will be executed in serial order, starting with the first appearing field textually.

When executing a grouped field set serially, the executor must consider each entry from the grouped field set in the order provided in the grouped field set. It must determine the corresponding entry in the result map for each item to completion before it continues on to the next item in the grouped field set:

For example, given the following selection set to be executed serially:

{
  changeBirthday(birthday: $newBirthday) {
    month
  }
  changeAddress(address: $newAddress) {
    street
  }
}

The executor must, in serial:

• Run {ExecuteField()} for changeBirthday, which during {CompleteValue()} will execute the { month } sub-selection set normally.
• Run {ExecuteField()} for changeAddress, which during {CompleteValue()} will execute the { street } sub-selection set normally.

As an illustrative example, let's assume we have a mutation field changeTheNumber that returns an object containing one field, theNumber. If we execute the following selection set serially:

{
  first: changeTheNumber(newNumber: 1) {
    theNumber
  }
  second: changeTheNumber(newNumber: 3) {
    theNumber
  }
  third: changeTheNumber(newNumber: 2) {
    theNumber
  }
}

The executor will execute the following serially:

• Resolve the changeTheNumber(newNumber: 1) field
• Execute the { theNumber } sub-selection set of first normally
• Resolve the changeTheNumber(newNumber: 3) field
• Execute the { theNumber } sub-selection set of second normally
• Resolve the changeTheNumber(newNumber: 2) field
• Execute the { theNumber } sub-selection set of third normally

A correct executor must generate the following result for that selection set:

{
  "first": {
    "theNumber": 1
  },
  "second": {
    "theNumber": 3
  },
  "third": {
    "theNumber": 2
  }
}

Field Collection

Before execution, the selection set is converted to a grouped field set by calling {CollectFields()}. Each entry in the grouped field set is a list of fields that share a response key (the alias if defined, otherwise the field name). This ensures all fields with the same response key (including those in referenced fragments) are executed at the same time.

As an example, collecting the fields of this selection set would collect two instances of the field a and one of field b:

{
  a {
    subfield1
  }
  ...ExampleFragment
}

fragment ExampleFragment on Query {
  a {
    subfield2
  }
  b
}

The depth-first-search order of the field groups produced by {CollectFields()} is maintained through execution, ensuring that fields appear in the executed response in a stable and predictable order.

When {CollectFields()} is used during validation (see for example the single root field subscription operation validation rule), the runtime value for {variableValues} will not be available - in this case we set {variableValues} to {null} and forbid the use of the @skip and @include directives. During execution, {variableValues} will always be non-null.

CollectFields(objectType, selectionSet, variableValues, visitedFragments):

• If {visitedFragments} is not provided, initialize it to the empty set.
• Initialize {groupedFields} to an empty ordered map of lists.
• For each {selection} in {selectionSet}:
  • If {variableValues} is {null}:
    • {selection} must not provide the @skip directive.
    • {selection} must not provide the @include directive.
  • Otherwise:
    • If {selection} provides the directive @skip, let {skipDirective} be that directive.
      • If {skipDirective}'s {if} argument is {true} or is a variable in {variableValues} with the value {true}, continue with the next {selection} in {selectionSet}.
    • If {selection} provides the directive @include, let {includeDirective} be that directive.
      • If {includeDirective}'s {if} argument is not {true} and is not a variable in {variableValues} with the value {true}, continue with the next {selection} in {selectionSet}.
  • If {selection} is a {Field}:
    • Let {responseKey} be the response key of {selection} (the alias if defined, otherwise the field name).
    • Let {groupForResponseKey} be the list in {groupedFields} for {responseKey}; if no such list exists, create it as an empty list.
    • Append {selection} to the {groupForResponseKey}.
  • If {selection} is a {FragmentSpread}:
    • Let {fragmentSpreadName} be the name of {selection}.
    • If {fragmentSpreadName} is in {visitedFragments}, continue with the next {selection} in {selectionSet}.
    • Add {fragmentSpreadName} to {visitedFragments}.
    • Let {fragment} be the Fragment in the current Document whose name is {fragmentSpreadName}.
    • If no such {fragment} exists, continue with the next {selection} in {selectionSet}.
    • Let {fragmentType} be the type condition on {fragment}.
    • If {DoesFragmentTypeApply(objectType, fragmentType)} is false, continue with the next {selection} in {selectionSet}.
    • Let {fragmentSelectionSet} be the top-level selection set of {fragment}.
    • Let {fragmentGroupedFieldSet} be the result of calling {CollectFields(objectType, fragmentSelectionSet, variableValues, visitedFragments)}.
    • For each {fragmentGroup} in {fragmentGroupedFieldSet}:
      • Let {responseKey} be the response key shared by all fields in {fragmentGroup}.
      • Let {groupForResponseKey} be the list in {groupedFields} for {responseKey}; if no such list exists, create it as an empty list.
      • Append all items in {fragmentGroup} to {groupForResponseKey}.
  • If {selection} is an {InlineFragment}:
    • Let {fragmentType} be the type condition on {selection}.
    • If {fragmentType} is not {null} and {DoesFragmentTypeApply(objectType, fragmentType)} is false, continue with the next {selection} in {selectionSet}.
    • Let {fragmentSelectionSet} be the top-level selection set of {selection}.
    • Let {fragmentGroupedFieldSet} be the result of calling {CollectFields(objectType, fragmentSelectionSet, variableValues, visitedFragments)}.
    • For each {fragmentGroup} in {fragmentGroupedFieldSet}:
      • Let {responseKey} be the response key shared by all fields in {fragmentGroup}.
      • Let {groupForResponseKey} be the list in {groupedFields} for {responseKey}; if no such list exists, create it as an empty list.
      • Append all items in {fragmentGroup} to {groupForResponseKey}.
• Return {groupedFields}.

DoesFragmentTypeApply(objectType, fragmentType):

• If {fragmentType} is an Object Type:
  • if {objectType} and {fragmentType} are the same type, return {true}, otherwise return {false}.
• If {fragmentType} is an Interface Type:
  • if {objectType} is an implementation of {fragmentType}, return {true} otherwise return {false}.
• If {fragmentType} is a Union:
  • if {objectType} is a possible type of {fragmentType}, return {true} otherwise return {false}.

Note: The steps in {CollectFields()} evaluating the @skip and @include directives may be applied in either order since they apply commutatively.

Executing Fields

Each field requested in the grouped field set that is defined on the selected objectType will result in an entry in the response map. Field execution first coerces any provided argument values, then resolves a value for the field, and finally completes that value either by recursively executing another selection set or coercing a scalar value.

ExecuteField(objectType, objectValue, fieldType, fields, variableValues):

• Let {field} be the first entry in {fields}.
• Let {fieldName} be the field name of {field}.
• Let {argumentValues} be the result of {CoerceArgumentValues(objectType, field, variableValues)}
• Let {resolvedValue} be {ResolveFieldValue(objectType, objectValue, fieldName, argumentValues)}.
• Return the result of {CompleteValue(fieldType, fields, resolvedValue, variableValues)}.

Coercing Field Arguments

Fields may include arguments which are provided to the underlying runtime in order to correctly produce a value. These arguments are defined by the field in the type system to have a specific input type.

At each argument position in an operation may be a literal {Value}, or a {Variable} to be provided at runtime.

CoerceArgumentValues(objectType, field, variableValues):

• Let {coercedValues} be an empty unordered Map.
• Let {argumentValues} be the argument values provided in {field}.
• Let {fieldName} be the name of {field}.
• Let {argumentDefinitions} be the arguments defined by {objectType} for the field named {fieldName}.
• For each {argumentDefinition} in {argumentDefinitions}:
  • Let {argumentName} be the name of {argumentDefinition}.
  • Let {argumentType} be the expected type of {argumentDefinition}.
  • Let {defaultValue} be the default value for {argumentDefinition}.
  • Let {hasValue} be {true} if {argumentValues} provides a value for the name {argumentName}.
  • Let {argumentValue} be the value provided in {argumentValues} for the name {argumentName}.
  • If {argumentValue} is a {Variable}:
    • Let {variableName} be the name of {argumentValue}.
    • Let {hasValue} be {true} if {variableValues} provides a value for the name {variableName}.
    • Let {value} be the value provided in {variableValues} for the name {variableName}.
  • Otherwise, let {value} be {argumentValue}.
  • If {hasValue} is not {true} and {defaultValue} exists (including {null}):
    • Add an entry to {coercedValues} named {argumentName} with the value {defaultValue}.
  • Otherwise if {argumentType} is a Non-Nullable type, and either {hasValue} is not {true} or {value} is {null}, raise a field error.
  • Otherwise if {hasValue} is true:
    • If {value} is {null}:
      • Add an entry to {coercedValues} named {argumentName} with the value {null}.
    • Otherwise, if {argumentValue} is a {Variable}:
      • Add an entry to {coercedValues} named {argumentName} with the value {value}.
    • Otherwise:
      • If {value} cannot be coerced according to the input coercion rules of {argumentType}, raise a field error.
      • Let {coercedValue} be the result of coercing {value} according to the input coercion rules of {argumentType}.
      • Add an entry to {coercedValues} named {argumentName} with the value {coercedValue}.
• Return {coercedValues}.

Note: Variable values are not coerced because they are expected to be coerced before executing the operation in {CoerceVariableValues()}, and valid operations must only allow usage of variables of appropriate types.

Value Resolution

While nearly all of GraphQL execution can be described generically, ultimately the internal system exposing the GraphQL interface must provide values. This is exposed via {ResolveFieldValue}, which produces a value for a given field on a type for a real value.

As an example, this might accept the {objectType} Person, the {field} {"soulMate"}, and the {objectValue} representing John Lennon. It would be expected to yield the value representing Yoko Ono.

ResolveFieldValue(objectType, objectValue, fieldName, argumentValues):

• Let {resolver} be the internal function provided by {objectType} for determining the resolved value of a field named {fieldName}.
• Return the result of calling {resolver}, providing {objectValue} and {argumentValues}.

Note: It is common for {resolver} to be asynchronous due to relying on reading an underlying database or networked service to produce a value. This necessitates the rest of a GraphQL executor to handle an asynchronous execution flow.

Value Completion

After resolving the value for a field, it is completed by ensuring it adheres to the expected return type. If the return type is another Object type, then the field execution process continues recursively.

CompleteValue(fieldType, fields, result, variableValues):

• If the {fieldType} is a Non-Null type:
  • Let {innerType} be the inner type of {fieldType}.
  • Let {completedResult} be the result of calling {CompleteValue(innerType, fields, result, variableValues)}.
  • If {completedResult} is {null}, raise a field error.
  • Return {completedResult}.
• If {result} is {null} (or another internal value similar to {null} such as {undefined}), return {null}.
• If {fieldType} is a List type:
  • If {result} is not a collection of values, raise a field error.
  • Let {innerType} be the inner type of {fieldType}.
  • Return a list where each list item is the result of calling {CompleteValue(innerType, fields, resultItem, variableValues)}, where {resultItem} is each item in {result}.
• If {fieldType} is a Scalar or Enum type:
  • Return the result of {CoerceResult(fieldType, result)}.
• If {fieldType} is an Object, Interface, or Union type:
  • If {fieldType} is an Object type.
    • Let {objectType} be {fieldType}.
  • Otherwise if {fieldType} is an Interface or Union type.
    • Let {objectType} be {ResolveAbstractType(fieldType, result)}.
  • Let {subSelectionSet} be the result of calling {MergeSelectionSets(fields)}.
  • Return the result of evaluating {ExecuteSelectionSet(subSelectionSet, objectType, result, variableValues)} normally (allowing for parallelization).

Coercing Results

The primary purpose of value completion is to ensure that the values returned by field resolvers are valid according to the GraphQL type system and a service's schema. This "dynamic type checking" allows GraphQL to provide consistent guarantees about returned types atop any service's internal runtime.

See the Scalars Result Coercion and Serialization sub-section for more detailed information about how GraphQL's built-in scalars coerce result values.

CoerceResult(leafType, value):

• Assert {value} is not {null}.
• Return the result of calling the internal method provided by the type system for determining the "result coercion" of {leafType} given the value {value}. This internal method must return a valid value for the type and not {null}. Otherwise throw a field error.

Note: If a field resolver returns {null} then it is handled within {CompleteValue()} before {CoerceResult()} is called. Therefore both the input and output of {CoerceResult()} must not be {null}.

Resolving Abstract Types

When completing a field with an abstract return type, that is an Interface or Union return type, first the abstract type must be resolved to a relevant Object type. This determination is made by the internal system using whatever means appropriate.

Note: A common method of determining the Object type for an {objectValue} in object-oriented environments, such as Java or C#, is to use the class name of the {objectValue}.

ResolveAbstractType(abstractType, objectValue):

• Return the result of calling the internal method provided by the type system for determining the Object type of {abstractType} given the value {objectValue}.

Merging Selection Sets

When more than one field of the same name is executed in parallel, their selection sets are merged together when completing the value in order to continue execution of the sub-selection sets.

An example operation illustrating parallel fields with the same name with sub-selections.

{
  me {
    firstName
  }
  me {
    lastName
  }
}

After resolving the value for me, the selection sets are merged together so firstName and lastName can be resolved for one value.

MergeSelectionSets(fields):

• Let {selectionSet} be an empty list.
• For each {field} in {fields}:
  • Let {fieldSelectionSet} be the selection set of {field}.
  • If {fieldSelectionSet} is null or empty, continue to the next field.
  • Append all selections in {fieldSelectionSet} to {selectionSet}.
• Return {selectionSet}.

Handling Field Errors

"Field errors" are raised from a particular field during value resolution or coercion. While these errors should be reported in the response, they are "handled" by producing a partial response.

Note: This is distinct from "request errors" which are raised before execution begins. If a request error is encountered, execution does not begin and no data is returned in the response.

If a field error is raised while resolving a field, it is handled as though the field returned {null}, and the error must be added to the {"errors"} list in the response.

If the result of resolving a field is {null} (either because the function to resolve the field returned {null} or because a field error was raised), and that field is of a Non-Null type, then a field error is raised. The error must be added to the {"errors"} list in the response.

If the field returns {null} because of a field error which has already been added to the {"errors"} list in the response, the {"errors"} list must not be further affected. That is, only one error should be added to the errors list per field.

Since Non-Null type fields cannot be {null}, field errors are propagated to be handled by the parent field. If the parent field may be {null} then it resolves to {null}, otherwise if it is a Non-Null type, the field error is further propagated to it's parent field.

If a List type wraps a Non-Null type, and one of the elements of that list resolves to {null}, then the entire list must resolve to {null}. If the List type is also wrapped in a Non-Null, the field error continues to propagate upwards.

If all fields from the root of the request to the source of the field error return Non-Null types, then the {"data"} entry in the response should be {null}.