ExecuteGremlinProfileQuery - Neptune Data API
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Executes a Gremlin Profile query, which runs a specified traversal, collects various metrics about the run, and produces a profile report as output. See Gremlin profile API in Neptune for details.

When invoking this operation in a Neptune cluster that has IAM authentication enabled, the IAM user or role making the request must have a policy attached that allows the neptune-db:ReadDataViaQuery IAM action in that cluster.

Note that the neptune-db:QueryLanguage:Gremlin IAM condition key can be used in the policy document to restrict the use of Gremlin queries (see Condition keys available in Neptune IAM data-access policy statements).

Request Syntax

POST /gremlin/profile HTTP/1.1 Content-type: application/json { "profile.chop": number, "gremlin": "string", "profile.indexOps": boolean, "profile.results": boolean, "profile.serializer": "string" }

URI Request Parameters

The request does not use any URI parameters.

Request Body

The request accepts the following data in JSON format.


If non-zero, causes the results string to be truncated at that number of characters. If set to zero, the string contains all the results.

Type: Integer

Required: No


The Gremlin query string to profile.

Type: String

Required: Yes


If this flag is set to TRUE, the results include a detailed report of all index operations that took place during query execution and serialization.

Type: Boolean

Required: No


If this flag is set to TRUE, the query results are gathered and displayed as part of the profile report. If FALSE, only the result count is displayed.

Type: Boolean

Required: No


If non-null, the gathered results are returned in a serialized response message in the format specified by this parameter. See Gremlin profile API in Neptune for more information.

Type: String

Required: No

Response Syntax

HTTP/1.1 200 output

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The response returns the following as the HTTP body.


A text blob containing the Gremlin Profile result. See Gremlin profile API in Neptune for details.


For information about the errors that are common to all actions, see Common Errors.


Raised when a request is submitted that cannot be processed.

HTTP Status Code: 400


Raised when a user cancelled a request.

HTTP Status Code: 500


Raised when a request timed out in the client.

HTTP Status Code: 408


Raised when a request attempts to modify data that is concurrently being modified by another process.

HTTP Status Code: 500


Raised when a value in a request field did not satisfy required constraints.

HTTP Status Code: 400


Raised when a request fails.

HTTP Status Code: 500


Raised when an argument in a request is not supported.

HTTP Status Code: 400


Raised when an argument in a request has an invalid value.

HTTP Status Code: 400


Raised when a parameter value is not valid.

HTTP Status Code: 400


Raised when a query is submitted that is syntactically incorrect or does not pass additional validation.

HTTP Status Code: 400


Raised when a request fails because of insufficient memory resources. The request can be retried.

HTTP Status Code: 500


Raised when a required parameter is missing.

HTTP Status Code: 400


Raised when a parsing issue is encountered.

HTTP Status Code: 400


Raised when a precondition for processing a request is not satisfied.

HTTP Status Code: 400


Raised when the number of active queries exceeds what the server can process. The query in question can be retried when the system is less busy.

HTTP Status Code: 500


Raised when the size of a query exceeds the system limit.

HTTP Status Code: 400


Raised when the body of a query is too large.

HTTP Status Code: 400


Raised when the an operation exceeds the time limit allowed for it.

HTTP Status Code: 500


Raised when the number of requests being processed exceeds the limit.

HTTP Status Code: 429


Raised when a request attempts to initiate an operation that is not supported.

HTTP Status Code: 400

See Also

For more information about using this API in one of the language-specific Amazon SDKs, see the following: