%% WARNING: DO NOT EDIT, AUTO-GENERATED CODE! %% See https://github.com/aws-beam/aws-codegen for more details. %% @doc Neptune Data API %% %% The Amazon Neptune data API provides SDK support for more than 40 of %% Neptune's data operations, including data loading, query execution, %% data inquiry, and machine learning. %% %% It supports the Gremlin and openCypher query languages, and is available %% in all SDK languages. It automatically signs API requests and greatly %% simplifies integrating Neptune into your applications. -module(aws_neptunedata). -export([cancel_gremlin_query/3, cancel_gremlin_query/4, cancel_loader_job/3, cancel_loader_job/4, cancel_ml_data_processing_job/3, cancel_ml_data_processing_job/4, cancel_ml_model_training_job/3, cancel_ml_model_training_job/4, cancel_ml_model_transform_job/3, cancel_ml_model_transform_job/4, cancel_open_cypher_query/3, cancel_open_cypher_query/4, create_ml_endpoint/2, create_ml_endpoint/3, delete_ml_endpoint/3, delete_ml_endpoint/4, delete_propertygraph_statistics/2, delete_propertygraph_statistics/3, delete_sparql_statistics/2, delete_sparql_statistics/3, execute_fast_reset/2, execute_fast_reset/3, execute_gremlin_explain_query/2, execute_gremlin_explain_query/3, execute_gremlin_profile_query/2, execute_gremlin_profile_query/3, execute_gremlin_query/2, execute_gremlin_query/3, execute_open_cypher_explain_query/2, execute_open_cypher_explain_query/3, execute_open_cypher_query/2, execute_open_cypher_query/3, get_engine_status/1, get_engine_status/3, get_engine_status/4, get_gremlin_query_status/2, get_gremlin_query_status/4, get_gremlin_query_status/5, get_loader_job_status/2, get_loader_job_status/4, get_loader_job_status/5, get_ml_data_processing_job/2, get_ml_data_processing_job/4, get_ml_data_processing_job/5, get_ml_endpoint/2, get_ml_endpoint/4, get_ml_endpoint/5, get_ml_model_training_job/2, get_ml_model_training_job/4, get_ml_model_training_job/5, get_ml_model_transform_job/2, get_ml_model_transform_job/4, get_ml_model_transform_job/5, get_open_cypher_query_status/2, get_open_cypher_query_status/4, get_open_cypher_query_status/5, get_propertygraph_statistics/1, get_propertygraph_statistics/3, get_propertygraph_statistics/4, get_propertygraph_stream/1, get_propertygraph_stream/3, get_propertygraph_stream/4, get_propertygraph_summary/1, get_propertygraph_summary/3, get_propertygraph_summary/4, get_r_d_f_graph_summary/1, get_r_d_f_graph_summary/3, get_r_d_f_graph_summary/4, get_sparql_statistics/1, get_sparql_statistics/3, get_sparql_statistics/4, get_sparql_stream/1, get_sparql_stream/3, get_sparql_stream/4, list_gremlin_queries/1, list_gremlin_queries/3, list_gremlin_queries/4, list_loader_jobs/1, list_loader_jobs/3, list_loader_jobs/4, list_ml_data_processing_jobs/1, list_ml_data_processing_jobs/3, list_ml_data_processing_jobs/4, list_ml_endpoints/1, list_ml_endpoints/3, list_ml_endpoints/4, list_ml_model_training_jobs/1, list_ml_model_training_jobs/3, list_ml_model_training_jobs/4, list_ml_model_transform_jobs/1, list_ml_model_transform_jobs/3, list_ml_model_transform_jobs/4, list_open_cypher_queries/1, list_open_cypher_queries/3, list_open_cypher_queries/4, manage_propertygraph_statistics/2, manage_propertygraph_statistics/3, manage_sparql_statistics/2, manage_sparql_statistics/3, start_loader_job/2, start_loader_job/3, start_ml_data_processing_job/2, start_ml_data_processing_job/3, start_ml_model_training_job/2, start_ml_model_training_job/3, start_ml_model_transform_job/2, start_ml_model_transform_job/3]). -include_lib("hackney/include/hackney_lib.hrl"). %% Example: %% parsing_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type parsing_exception() :: #{binary() => any()}. %% Example: %% manage_sparql_statistics_input() :: #{ %% <<"mode">> => list(any()) %% } -type manage_sparql_statistics_input() :: #{binary() => any()}. %% Example: %% get_ml_model_training_job_input() :: #{ %% <<"neptuneIamRoleArn">> => [string()] %% } -type get_ml_model_training_job_input() :: #{binary() => any()}. %% Example: %% cancel_ml_data_processing_job_input() :: #{ %% <<"clean">> => [boolean()], %% <<"neptuneIamRoleArn">> => [string()] %% } -type cancel_ml_data_processing_job_input() :: #{binary() => any()}. %% Example: %% read_only_violation_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type read_only_violation_exception() :: #{binary() => any()}. %% Example: %% custom_model_training_parameters() :: #{ %% <<"sourceS3DirectoryPath">> => [string()], %% <<"trainingEntryPointScript">> => [string()], %% <<"transformEntryPointScript">> => [string()] %% } -type custom_model_training_parameters() :: #{binary() => any()}. %% Example: %% internal_failure_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type internal_failure_exception() :: #{binary() => any()}. %% Example: %% s3_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type s3_exception() :: #{binary() => any()}. %% Example: %% get_r_d_f_graph_summary_input() :: #{ %% <<"mode">> => list(any()) %% } -type get_r_d_f_graph_summary_input() :: #{binary() => any()}. %% Example: %% get_propertygraph_stream_output() :: #{ %% <<"format">> => [string()], %% <<"lastEventId">> => map(), %% <<"lastTrxTimestampInMillis">> => [float()], %% <<"records">> => list(propertygraph_record()), %% <<"totalRecords">> => [integer()] %% } -type get_propertygraph_stream_output() :: #{binary() => any()}. %% Example: %% statistics_not_available_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type statistics_not_available_exception() :: #{binary() => any()}. %% Example: %% query_language_version() :: #{ %% <<"version">> => [string()] %% } -type query_language_version() :: #{binary() => any()}. %% Example: %% unsupported_operation_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type unsupported_operation_exception() :: #{binary() => any()}. %% Example: %% delete_propertygraph_statistics_output() :: #{ %% <<"payload">> => delete_statistics_value_map(), %% <<"status">> => [string()], %% <<"statusCode">> => [integer()] %% } -type delete_propertygraph_statistics_output() :: #{binary() => any()}. %% Example: %% get_propertygraph_statistics_output() :: #{ %% <<"payload">> => statistics(), %% <<"status">> => [string()] %% } -type get_propertygraph_statistics_output() :: #{binary() => any()}. %% Example: %% execute_gremlin_profile_query_input() :: #{ %% <<"chop">> => [integer()], %% <<"gremlinQuery">> := [string()], %% <<"indexOps">> => [boolean()], %% <<"results">> => [boolean()], %% <<"serializer">> => [string()] %% } -type execute_gremlin_profile_query_input() :: #{binary() => any()}. %% Example: %% list_ml_model_transform_jobs_input() :: #{ %% <<"maxItems">> => integer(), %% <<"neptuneIamRoleArn">> => [string()] %% } -type list_ml_model_transform_jobs_input() :: #{binary() => any()}. %% Example: %% cancel_ml_data_processing_job_output() :: #{ %% <<"status">> => [string()] %% } -type cancel_ml_data_processing_job_output() :: #{binary() => any()}. %% Example: %% bulk_load_id_not_found_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type bulk_load_id_not_found_exception() :: #{binary() => any()}. %% Example: %% query_eval_stats() :: #{ %% <<"cancelled">> => [boolean()], %% <<"elapsed">> => [integer()], %% <<"subqueries">> => [any()], %% <<"waited">> => [integer()] %% } -type query_eval_stats() :: #{binary() => any()}. %% Example: %% manage_propertygraph_statistics_output() :: #{ %% <<"payload">> => refresh_statistics_id_map(), %% <<"status">> => [string()] %% } -type manage_propertygraph_statistics_output() :: #{binary() => any()}. %% Example: %% cancel_open_cypher_query_output() :: #{ %% <<"payload">> => [boolean()], %% <<"status">> => [string()] %% } -type cancel_open_cypher_query_output() :: #{binary() => any()}. %% Example: %% execute_open_cypher_query_output() :: #{ %% <<"results">> => [any()] %% } -type execute_open_cypher_query_output() :: #{binary() => any()}. %% Example: %% get_ml_model_transform_job_output() :: #{ %% <<"baseProcessingJob">> => ml_resource_definition(), %% <<"id">> => [string()], %% <<"models">> => list(ml_config_definition()), %% <<"remoteModelTransformJob">> => ml_resource_definition(), %% <<"status">> => [string()] %% } -type get_ml_model_transform_job_output() :: #{binary() => any()}. %% Example: %% cancel_ml_model_transform_job_output() :: #{ %% <<"status">> => [string()] %% } -type cancel_ml_model_transform_job_output() :: #{binary() => any()}. %% Example: %% execute_gremlin_explain_query_input() :: #{ %% <<"gremlinQuery">> := [string()] %% } -type execute_gremlin_explain_query_input() :: #{binary() => any()}. %% Example: %% method_not_allowed_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type method_not_allowed_exception() :: #{binary() => any()}. %% Example: %% get_propertygraph_summary_input() :: #{ %% <<"mode">> => list(any()) %% } -type get_propertygraph_summary_input() :: #{binary() => any()}. %% Example: %% ml_config_definition() :: #{ %% <<"arn">> => [string()], %% <<"name">> => [string()] %% } -type ml_config_definition() :: #{binary() => any()}. %% Example: %% execute_gremlin_profile_query_output() :: #{ %% <<"output">> => binary() %% } -type execute_gremlin_profile_query_output() :: #{binary() => any()}. %% Example: %% list_ml_model_training_jobs_input() :: #{ %% <<"maxItems">> => integer(), %% <<"neptuneIamRoleArn">> => [string()] %% } -type list_ml_model_training_jobs_input() :: #{binary() => any()}. %% Example: %% cancel_gremlin_query_output() :: #{ %% <<"status">> => [string()] %% } -type cancel_gremlin_query_output() :: #{binary() => any()}. %% Example: %% propertygraph_data() :: #{ %% <<"from">> => [string()], %% <<"id">> => [string()], %% <<"key">> => [string()], %% <<"to">> => [string()], %% <<"type">> => [string()], %% <<"value">> => [any()] %% } -type propertygraph_data() :: #{binary() => any()}. %% Example: %% cancel_loader_job_input() :: #{} -type cancel_loader_job_input() :: #{}. %% Example: %% execute_open_cypher_explain_query_input() :: #{ %% <<"explainMode">> := list(any()), %% <<"openCypherQuery">> := [string()], %% <<"parameters">> => [string()] %% } -type execute_open_cypher_explain_query_input() :: #{binary() => any()}. %% Example: %% failure_by_query_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type failure_by_query_exception() :: #{binary() => any()}. %% Example: %% get_sparql_stream_output() :: #{ %% <<"format">> => [string()], %% <<"lastEventId">> => map(), %% <<"lastTrxTimestampInMillis">> => [float()], %% <<"records">> => list(sparql_record()), %% <<"totalRecords">> => [integer()] %% } -type get_sparql_stream_output() :: #{binary() => any()}. %% Example: %% illegal_argument_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type illegal_argument_exception() :: #{binary() => any()}. %% Example: %% start_ml_model_training_job_output() :: #{ %% <<"arn">> => [string()], %% <<"creationTimeInMillis">> => [float()], %% <<"id">> => [string()] %% } -type start_ml_model_training_job_output() :: #{binary() => any()}. %% Example: %% too_many_requests_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type too_many_requests_exception() :: #{binary() => any()}. %% Example: %% start_loader_job_input() :: #{ %% <<"dependencies">> => list([string()]()), %% <<"edgeOnlyLoad">> => [boolean()], %% <<"failOnError">> => [boolean()], %% <<"format">> := list(any()), %% <<"iamRoleArn">> := [string()], %% <<"mode">> => list(any()), %% <<"parallelism">> => list(any()), %% <<"parserConfiguration">> => map(), %% <<"queueRequest">> => [boolean()], %% <<"s3BucketRegion">> := list(any()), %% <<"source">> := [string()], %% <<"updateSingleCardinalityProperties">> => [boolean()], %% <<"userProvidedEdgeIds">> => [boolean()] %% } -type start_loader_job_input() :: #{binary() => any()}. %% Example: %% get_gremlin_query_status_input() :: #{} -type get_gremlin_query_status_input() :: #{}. %% Example: %% start_ml_data_processing_job_output() :: #{ %% <<"arn">> => [string()], %% <<"creationTimeInMillis">> => [float()], %% <<"id">> => [string()] %% } -type start_ml_data_processing_job_output() :: #{binary() => any()}. %% Example: %% list_ml_model_transform_jobs_output() :: #{ %% <<"ids">> => list([string()]()) %% } -type list_ml_model_transform_jobs_output() :: #{binary() => any()}. %% Example: %% get_ml_data_processing_job_input() :: #{ %% <<"neptuneIamRoleArn">> => [string()] %% } -type get_ml_data_processing_job_input() :: #{binary() => any()}. %% Example: %% subject_structure() :: #{ %% <<"count">> => [float()], %% <<"predicates">> => list([string()]()) %% } -type subject_structure() :: #{binary() => any()}. %% Example: %% ml_resource_not_found_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type ml_resource_not_found_exception() :: #{binary() => any()}. %% Example: %% ml_resource_definition() :: #{ %% <<"arn">> => [string()], %% <<"cloudwatchLogUrl">> => [string()], %% <<"failureReason">> => [string()], %% <<"name">> => [string()], %% <<"outputLocation">> => [string()], %% <<"status">> => [string()] %% } -type ml_resource_definition() :: #{binary() => any()}. %% Example: %% query_limit_exceeded_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type query_limit_exceeded_exception() :: #{binary() => any()}. %% Example: %% list_ml_data_processing_jobs_output() :: #{ %% <<"ids">> => list([string()]()) %% } -type list_ml_data_processing_jobs_output() :: #{binary() => any()}. %% Example: %% edge_structure() :: #{ %% <<"count">> => [float()], %% <<"edgeProperties">> => list([string()]()) %% } -type edge_structure() :: #{binary() => any()}. %% Example: %% get_sparql_stream_input() :: #{ %% <<"commitNum">> => [float()], %% <<"encoding">> => list(any()), %% <<"iteratorType">> => list(any()), %% <<"limit">> => [float()], %% <<"opNum">> => [float()] %% } -type get_sparql_stream_input() :: #{binary() => any()}. %% Example: %% cancel_ml_model_training_job_output() :: #{ %% <<"status">> => [string()] %% } -type cancel_ml_model_training_job_output() :: #{binary() => any()}. %% Example: %% time_limit_exceeded_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type time_limit_exceeded_exception() :: #{binary() => any()}. %% Example: %% get_loader_job_status_output() :: #{ %% <<"payload">> => [any()], %% <<"status">> => [string()] %% } -type get_loader_job_status_output() :: #{binary() => any()}. %% Example: %% start_ml_model_training_job_input() :: #{ %% <<"baseProcessingInstanceType">> => [string()], %% <<"customModelTrainingParameters">> => custom_model_training_parameters(), %% <<"dataProcessingJobId">> := [string()], %% <<"enableManagedSpotTraining">> => [boolean()], %% <<"id">> => [string()], %% <<"maxHPONumberOfTrainingJobs">> => [integer()], %% <<"maxHPOParallelTrainingJobs">> => [integer()], %% <<"neptuneIamRoleArn">> => [string()], %% <<"previousModelTrainingJobId">> => [string()], %% <<"s3OutputEncryptionKMSKey">> => [string()], %% <<"sagemakerIamRoleArn">> => [string()], %% <<"securityGroupIds">> => list([string()]()), %% <<"subnets">> => list([string()]()), %% <<"trainModelS3Location">> := [string()], %% <<"trainingInstanceType">> => [string()], %% <<"trainingInstanceVolumeSizeInGB">> => [integer()], %% <<"trainingTimeOutInSeconds">> => [integer()], %% <<"volumeEncryptionKMSKey">> => [string()] %% } -type start_ml_model_training_job_input() :: #{binary() => any()}. %% Example: %% memory_limit_exceeded_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type memory_limit_exceeded_exception() :: #{binary() => any()}. %% Example: %% start_ml_data_processing_job_input() :: #{ %% <<"configFileName">> => [string()], %% <<"id">> => [string()], %% <<"inputDataS3Location">> := [string()], %% <<"modelType">> => [string()], %% <<"neptuneIamRoleArn">> => [string()], %% <<"previousDataProcessingJobId">> => [string()], %% <<"processedDataS3Location">> := [string()], %% <<"processingInstanceType">> => [string()], %% <<"processingInstanceVolumeSizeInGB">> => [integer()], %% <<"processingTimeOutInSeconds">> => [integer()], %% <<"s3OutputEncryptionKMSKey">> => [string()], %% <<"sagemakerIamRoleArn">> => [string()], %% <<"securityGroupIds">> => list([string()]()), %% <<"subnets">> => list([string()]()), %% <<"volumeEncryptionKMSKey">> => [string()] %% } -type start_ml_data_processing_job_input() :: #{binary() => any()}. %% Example: %% malformed_query_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type malformed_query_exception() :: #{binary() => any()}. %% Example: %% query_limit_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type query_limit_exception() :: #{binary() => any()}. %% Example: %% sparql_record() :: #{ %% <<"commitTimestampInMillis">> => [float()], %% <<"data">> => sparql_data(), %% <<"eventId">> => map(), %% <<"isLastOp">> => [boolean()], %% <<"op">> => [string()] %% } -type sparql_record() :: #{binary() => any()}. %% Example: %% gremlin_query_status() :: #{ %% <<"queryEvalStats">> => query_eval_stats(), %% <<"queryId">> => [string()], %% <<"queryString">> => [string()] %% } -type gremlin_query_status() :: #{binary() => any()}. %% Example: %% get_propertygraph_summary_output() :: #{ %% <<"payload">> => propertygraph_summary_value_map(), %% <<"statusCode">> => [integer()] %% } -type get_propertygraph_summary_output() :: #{binary() => any()}. %% Example: %% list_ml_endpoints_output() :: #{ %% <<"ids">> => list([string()]()) %% } -type list_ml_endpoints_output() :: #{binary() => any()}. %% Example: %% r_d_f_graph_summary_value_map() :: #{ %% <<"graphSummary">> => r_d_f_graph_summary(), %% <<"lastStatisticsComputationTime">> => [non_neg_integer()], %% <<"version">> => [string()] %% } -type r_d_f_graph_summary_value_map() :: #{binary() => any()}. %% Example: %% execute_open_cypher_query_input() :: #{ %% <<"openCypherQuery">> := [string()], %% <<"parameters">> => [string()] %% } -type execute_open_cypher_query_input() :: #{binary() => any()}. %% Example: %% cancel_ml_model_transform_job_input() :: #{ %% <<"clean">> => [boolean()], %% <<"neptuneIamRoleArn">> => [string()] %% } -type cancel_ml_model_transform_job_input() :: #{binary() => any()}. %% Example: %% cancel_open_cypher_query_input() :: #{ %% <<"silent">> => [boolean()] %% } -type cancel_open_cypher_query_input() :: #{binary() => any()}. %% Example: %% list_ml_model_training_jobs_output() :: #{ %% <<"ids">> => list([string()]()) %% } -type list_ml_model_training_jobs_output() :: #{binary() => any()}. %% Example: %% get_loader_job_status_input() :: #{ %% <<"details">> => [boolean()], %% <<"errors">> => [boolean()], %% <<"errorsPerPage">> => integer(), %% <<"page">> => integer() %% } -type get_loader_job_status_input() :: #{binary() => any()}. %% Example: %% get_open_cypher_query_status_output() :: #{ %% <<"queryEvalStats">> => query_eval_stats(), %% <<"queryId">> => [string()], %% <<"queryString">> => [string()] %% } -type get_open_cypher_query_status_output() :: #{binary() => any()}. %% Example: %% start_ml_model_transform_job_output() :: #{ %% <<"arn">> => [string()], %% <<"creationTimeInMillis">> => [float()], %% <<"id">> => [string()] %% } -type start_ml_model_transform_job_output() :: #{binary() => any()}. %% Example: %% propertygraph_summary() :: #{ %% <<"edgeLabels">> => list([string()]()), %% <<"edgeProperties">> => list(map()), %% <<"edgeStructures">> => list(edge_structure()), %% <<"nodeLabels">> => list([string()]()), %% <<"nodeProperties">> => list(map()), %% <<"nodeStructures">> => list(node_structure()), %% <<"numEdgeLabels">> => [float()], %% <<"numEdgeProperties">> => [float()], %% <<"numEdges">> => [float()], %% <<"numNodeLabels">> => [float()], %% <<"numNodeProperties">> => [float()], %% <<"numNodes">> => [float()], %% <<"totalEdgePropertyValues">> => [float()], %% <<"totalNodePropertyValues">> => [float()] %% } -type propertygraph_summary() :: #{binary() => any()}. %% Example: %% fast_reset_token() :: #{ %% <<"token">> => [string()] %% } -type fast_reset_token() :: #{binary() => any()}. %% Example: %% create_ml_endpoint_input() :: #{ %% <<"id">> => [string()], %% <<"instanceCount">> => [integer()], %% <<"instanceType">> => [string()], %% <<"mlModelTrainingJobId">> => [string()], %% <<"mlModelTransformJobId">> => [string()], %% <<"modelName">> => [string()], %% <<"neptuneIamRoleArn">> => [string()], %% <<"update">> => [boolean()], %% <<"volumeEncryptionKMSKey">> => [string()] %% } -type create_ml_endpoint_input() :: #{binary() => any()}. %% Example: %% get_ml_model_transform_job_input() :: #{ %% <<"neptuneIamRoleArn">> => [string()] %% } -type get_ml_model_transform_job_input() :: #{binary() => any()}. %% Example: %% get_ml_endpoint_output() :: #{ %% <<"endpoint">> => ml_resource_definition(), %% <<"endpointConfig">> => ml_config_definition(), %% <<"id">> => [string()], %% <<"status">> => [string()] %% } -type get_ml_endpoint_output() :: #{binary() => any()}. %% Example: %% r_d_f_graph_summary() :: #{ %% <<"classes">> => list([string()]()), %% <<"numClasses">> => [float()], %% <<"numDistinctPredicates">> => [float()], %% <<"numDistinctSubjects">> => [float()], %% <<"numQuads">> => [float()], %% <<"predicates">> => list(map()), %% <<"subjectStructures">> => list(subject_structure()) %% } -type r_d_f_graph_summary() :: #{binary() => any()}. %% Example: %% statistics_summary() :: #{ %% <<"instanceCount">> => [integer()], %% <<"predicateCount">> => [integer()], %% <<"signatureCount">> => [integer()] %% } -type statistics_summary() :: #{binary() => any()}. %% Example: %% missing_parameter_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type missing_parameter_exception() :: #{binary() => any()}. %% Example: %% server_shutdown_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type server_shutdown_exception() :: #{binary() => any()}. %% Example: %% get_open_cypher_query_status_input() :: #{} -type get_open_cypher_query_status_input() :: #{}. %% Example: %% list_ml_data_processing_jobs_input() :: #{ %% <<"maxItems">> => integer(), %% <<"neptuneIamRoleArn">> => [string()] %% } -type list_ml_data_processing_jobs_input() :: #{binary() => any()}. %% Example: %% get_gremlin_query_status_output() :: #{ %% <<"queryEvalStats">> => query_eval_stats(), %% <<"queryId">> => [string()], %% <<"queryString">> => [string()] %% } -type get_gremlin_query_status_output() :: #{binary() => any()}. %% Example: %% list_ml_endpoints_input() :: #{ %% <<"maxItems">> => integer(), %% <<"neptuneIamRoleArn">> => [string()] %% } -type list_ml_endpoints_input() :: #{binary() => any()}. %% Example: %% list_gremlin_queries_output() :: #{ %% <<"acceptedQueryCount">> => [integer()], %% <<"queries">> => list(gremlin_query_status()), %% <<"runningQueryCount">> => [integer()] %% } -type list_gremlin_queries_output() :: #{binary() => any()}. %% Example: %% cancel_ml_model_training_job_input() :: #{ %% <<"clean">> => [boolean()], %% <<"neptuneIamRoleArn">> => [string()] %% } -type cancel_ml_model_training_job_input() :: #{binary() => any()}. %% Example: %% cancelled_by_user_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type cancelled_by_user_exception() :: #{binary() => any()}. %% Example: %% get_ml_data_processing_job_output() :: #{ %% <<"id">> => [string()], %% <<"processingJob">> => ml_resource_definition(), %% <<"status">> => [string()] %% } -type get_ml_data_processing_job_output() :: #{binary() => any()}. %% Example: %% delete_sparql_statistics_output() :: #{ %% <<"payload">> => delete_statistics_value_map(), %% <<"status">> => [string()], %% <<"statusCode">> => [integer()] %% } -type delete_sparql_statistics_output() :: #{binary() => any()}. %% Example: %% get_propertygraph_stream_input() :: #{ %% <<"commitNum">> => [float()], %% <<"encoding">> => list(any()), %% <<"iteratorType">> => list(any()), %% <<"limit">> => [float()], %% <<"opNum">> => [float()] %% } -type get_propertygraph_stream_input() :: #{binary() => any()}. %% Example: %% execute_gremlin_query_input() :: #{ %% <<"gremlinQuery">> := [string()], %% <<"serializer">> => [string()] %% } -type execute_gremlin_query_input() :: #{binary() => any()}. %% Example: %% get_engine_status_output() :: #{ %% <<"dbEngineVersion">> => [string()], %% <<"dfeQueryEngine">> => [string()], %% <<"features">> => map(), %% <<"gremlin">> => query_language_version(), %% <<"labMode">> => map(), %% <<"opencypher">> => query_language_version(), %% <<"role">> => [string()], %% <<"rollingBackTrxCount">> => [integer()], %% <<"rollingBackTrxEarliestStartTime">> => [string()], %% <<"settings">> => map(), %% <<"sparql">> => query_language_version(), %% <<"startTime">> => [string()], %% <<"status">> => [string()] %% } -type get_engine_status_output() :: #{binary() => any()}. %% Example: %% create_ml_endpoint_output() :: #{ %% <<"arn">> => [string()], %% <<"creationTimeInMillis">> => [float()], %% <<"id">> => [string()] %% } -type create_ml_endpoint_output() :: #{binary() => any()}. %% Example: %% propertygraph_record() :: #{ %% <<"commitTimestampInMillis">> => [float()], %% <<"data">> => propertygraph_data(), %% <<"eventId">> => map(), %% <<"isLastOp">> => [boolean()], %% <<"op">> => [string()] %% } -type propertygraph_record() :: #{binary() => any()}. %% Example: %% list_loader_jobs_input() :: #{ %% <<"includeQueuedLoads">> => [boolean()], %% <<"limit">> => integer() %% } -type list_loader_jobs_input() :: #{binary() => any()}. %% Example: %% refresh_statistics_id_map() :: #{ %% <<"statisticsId">> => [string()] %% } -type refresh_statistics_id_map() :: #{binary() => any()}. %% Example: %% access_denied_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type access_denied_exception() :: #{binary() => any()}. %% Example: %% invalid_parameter_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type invalid_parameter_exception() :: #{binary() => any()}. %% Example: %% execute_fast_reset_output() :: #{ %% <<"payload">> => fast_reset_token(), %% <<"status">> => [string()] %% } -type execute_fast_reset_output() :: #{binary() => any()}. %% Example: %% propertygraph_summary_value_map() :: #{ %% <<"graphSummary">> => propertygraph_summary(), %% <<"lastStatisticsComputationTime">> => [non_neg_integer()], %% <<"version">> => [string()] %% } -type propertygraph_summary_value_map() :: #{binary() => any()}. %% Example: %% invalid_argument_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type invalid_argument_exception() :: #{binary() => any()}. %% Example: %% list_open_cypher_queries_input() :: #{ %% <<"includeWaiting">> => [boolean()] %% } -type list_open_cypher_queries_input() :: #{binary() => any()}. %% Example: %% statistics() :: #{ %% <<"active">> => [boolean()], %% <<"autoCompute">> => [boolean()], %% <<"date">> => [non_neg_integer()], %% <<"note">> => [string()], %% <<"signatureInfo">> => statistics_summary(), %% <<"statisticsId">> => [string()] %% } -type statistics() :: #{binary() => any()}. %% Example: %% concurrent_modification_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type concurrent_modification_exception() :: #{binary() => any()}. %% Example: %% manage_sparql_statistics_output() :: #{ %% <<"payload">> => refresh_statistics_id_map(), %% <<"status">> => [string()] %% } -type manage_sparql_statistics_output() :: #{binary() => any()}. %% Example: %% node_structure() :: #{ %% <<"count">> => [float()], %% <<"distinctOutgoingEdgeLabels">> => list([string()]()), %% <<"nodeProperties">> => list([string()]()) %% } -type node_structure() :: #{binary() => any()}. %% Example: %% constraint_violation_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type constraint_violation_exception() :: #{binary() => any()}. %% Example: %% query_too_large_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type query_too_large_exception() :: #{binary() => any()}. %% Example: %% cancel_loader_job_output() :: #{ %% <<"status">> => [string()] %% } -type cancel_loader_job_output() :: #{binary() => any()}. %% Example: %% list_gremlin_queries_input() :: #{ %% <<"includeWaiting">> => [boolean()] %% } -type list_gremlin_queries_input() :: #{binary() => any()}. %% Example: %% throttling_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type throttling_exception() :: #{binary() => any()}. %% Example: %% execute_gremlin_query_output() :: #{ %% <<"meta">> => [any()], %% <<"requestId">> => [string()], %% <<"result">> => [any()], %% <<"status">> => gremlin_query_status_attributes() %% } -type execute_gremlin_query_output() :: #{binary() => any()}. %% Example: %% stream_records_not_found_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type stream_records_not_found_exception() :: #{binary() => any()}. %% Example: %% get_r_d_f_graph_summary_output() :: #{ %% <<"payload">> => r_d_f_graph_summary_value_map(), %% <<"statusCode">> => [integer()] %% } -type get_r_d_f_graph_summary_output() :: #{binary() => any()}. %% Example: %% manage_propertygraph_statistics_input() :: #{ %% <<"mode">> => list(any()) %% } -type manage_propertygraph_statistics_input() :: #{binary() => any()}. %% Example: %% invalid_numeric_data_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type invalid_numeric_data_exception() :: #{binary() => any()}. %% Example: %% execute_gremlin_explain_query_output() :: #{ %% <<"output">> => binary() %% } -type execute_gremlin_explain_query_output() :: #{binary() => any()}. %% Example: %% delete_ml_endpoint_output() :: #{ %% <<"status">> => [string()] %% } -type delete_ml_endpoint_output() :: #{binary() => any()}. %% Example: %% load_url_access_denied_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type load_url_access_denied_exception() :: #{binary() => any()}. %% Example: %% delete_ml_endpoint_input() :: #{ %% <<"clean">> => [boolean()], %% <<"neptuneIamRoleArn">> => [string()] %% } -type delete_ml_endpoint_input() :: #{binary() => any()}. %% Example: %% expired_stream_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type expired_stream_exception() :: #{binary() => any()}. %% Example: %% bad_request_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type bad_request_exception() :: #{binary() => any()}. %% Example: %% gremlin_query_status_attributes() :: #{ %% <<"attributes">> => [any()], %% <<"code">> => [integer()], %% <<"message">> => [string()] %% } -type gremlin_query_status_attributes() :: #{binary() => any()}. %% Example: %% start_loader_job_output() :: #{ %% <<"payload">> => map(), %% <<"status">> => [string()] %% } -type start_loader_job_output() :: #{binary() => any()}. %% Example: %% delete_statistics_value_map() :: #{ %% <<"active">> => [boolean()], %% <<"statisticsId">> => [string()] %% } -type delete_statistics_value_map() :: #{binary() => any()}. %% Example: %% execute_open_cypher_explain_query_output() :: #{ %% <<"results">> => [binary()] %% } -type execute_open_cypher_explain_query_output() :: #{binary() => any()}. %% Example: %% list_open_cypher_queries_output() :: #{ %% <<"acceptedQueryCount">> => [integer()], %% <<"queries">> => list(gremlin_query_status()), %% <<"runningQueryCount">> => [integer()] %% } -type list_open_cypher_queries_output() :: #{binary() => any()}. %% Example: %% start_ml_model_transform_job_input() :: #{ %% <<"baseProcessingInstanceType">> => [string()], %% <<"baseProcessingInstanceVolumeSizeInGB">> => [integer()], %% <<"customModelTransformParameters">> => custom_model_transform_parameters(), %% <<"dataProcessingJobId">> => [string()], %% <<"id">> => [string()], %% <<"mlModelTrainingJobId">> => [string()], %% <<"modelTransformOutputS3Location">> := [string()], %% <<"neptuneIamRoleArn">> => [string()], %% <<"s3OutputEncryptionKMSKey">> => [string()], %% <<"sagemakerIamRoleArn">> => [string()], %% <<"securityGroupIds">> => list([string()]()), %% <<"subnets">> => list([string()]()), %% <<"trainingJobName">> => [string()], %% <<"volumeEncryptionKMSKey">> => [string()] %% } -type start_ml_model_transform_job_input() :: #{binary() => any()}. %% Example: %% custom_model_transform_parameters() :: #{ %% <<"sourceS3DirectoryPath">> => [string()], %% <<"transformEntryPointScript">> => [string()] %% } -type custom_model_transform_parameters() :: #{binary() => any()}. %% Example: %% loader_id_result() :: #{ %% <<"loadIds">> => list([string()]()) %% } -type loader_id_result() :: #{binary() => any()}. %% Example: %% get_ml_model_training_job_output() :: #{ %% <<"hpoJob">> => ml_resource_definition(), %% <<"id">> => [string()], %% <<"mlModels">> => list(ml_config_definition()), %% <<"modelTransformJob">> => ml_resource_definition(), %% <<"processingJob">> => ml_resource_definition(), %% <<"status">> => [string()] %% } -type get_ml_model_training_job_output() :: #{binary() => any()}. %% Example: %% preconditions_failed_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type preconditions_failed_exception() :: #{binary() => any()}. %% Example: %% client_timeout_exception() :: #{ %% <<"code">> => [string()], %% <<"detailedMessage">> => [string()], %% <<"requestId">> => [string()] %% } -type client_timeout_exception() :: #{binary() => any()}. %% Example: %% sparql_data() :: #{ %% <<"stmt">> => [string()] %% } -type sparql_data() :: #{binary() => any()}. %% Example: %% list_loader_jobs_output() :: #{ %% <<"payload">> => loader_id_result(), %% <<"status">> => [string()] %% } -type list_loader_jobs_output() :: #{binary() => any()}. %% Example: %% cancel_gremlin_query_input() :: #{} -type cancel_gremlin_query_input() :: #{}. %% Example: %% get_ml_endpoint_input() :: #{ %% <<"neptuneIamRoleArn">> => [string()] %% } -type get_ml_endpoint_input() :: #{binary() => any()}. %% Example: %% get_sparql_statistics_output() :: #{ %% <<"payload">> => statistics(), %% <<"status">> => [string()] %% } -type get_sparql_statistics_output() :: #{binary() => any()}. %% Example: %% execute_fast_reset_input() :: #{ %% <<"action">> := list(any()), %% <<"token">> => [string()] %% } -type execute_fast_reset_input() :: #{binary() => any()}. -type cancel_gremlin_query_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | time_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | parsing_exception(). -type cancel_loader_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | load_url_access_denied_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | bulk_load_id_not_found_exception() | unsupported_operation_exception() | internal_failure_exception(). -type cancel_ml_data_processing_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type cancel_ml_model_training_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type cancel_ml_model_transform_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type cancel_open_cypher_query_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | invalid_numeric_data_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | time_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | parsing_exception(). -type create_ml_endpoint_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type delete_ml_endpoint_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type delete_propertygraph_statistics_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | statistics_not_available_exception() | read_only_violation_exception(). -type delete_sparql_statistics_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | statistics_not_available_exception() | read_only_violation_exception(). -type execute_fast_reset_errors() :: client_timeout_exception() | preconditions_failed_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | server_shutdown_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | method_not_allowed_exception() | unsupported_operation_exception() | read_only_violation_exception(). -type execute_gremlin_explain_query_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | query_too_large_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | cancelled_by_user_exception() | missing_parameter_exception() | query_limit_exception() | malformed_query_exception() | memory_limit_exceeded_exception() | time_limit_exceeded_exception() | query_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | parsing_exception(). -type execute_gremlin_profile_query_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | query_too_large_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | cancelled_by_user_exception() | missing_parameter_exception() | query_limit_exception() | malformed_query_exception() | memory_limit_exceeded_exception() | time_limit_exceeded_exception() | query_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | parsing_exception(). -type execute_gremlin_query_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | query_too_large_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | cancelled_by_user_exception() | missing_parameter_exception() | query_limit_exception() | malformed_query_exception() | memory_limit_exceeded_exception() | time_limit_exceeded_exception() | query_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | parsing_exception(). -type execute_open_cypher_explain_query_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | invalid_numeric_data_exception() | query_too_large_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | cancelled_by_user_exception() | missing_parameter_exception() | query_limit_exception() | malformed_query_exception() | memory_limit_exceeded_exception() | time_limit_exceeded_exception() | query_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | parsing_exception(). -type execute_open_cypher_query_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | invalid_numeric_data_exception() | query_too_large_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | cancelled_by_user_exception() | missing_parameter_exception() | query_limit_exception() | malformed_query_exception() | memory_limit_exceeded_exception() | time_limit_exceeded_exception() | query_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | parsing_exception(). -type get_engine_status_errors() :: client_timeout_exception() | preconditions_failed_exception() | constraint_violation_exception() | invalid_argument_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | internal_failure_exception(). -type get_gremlin_query_status_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | time_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | read_only_violation_exception() | parsing_exception(). -type get_loader_job_status_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | load_url_access_denied_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | bulk_load_id_not_found_exception() | unsupported_operation_exception() | internal_failure_exception(). -type get_ml_data_processing_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type get_ml_endpoint_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type get_ml_model_training_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type get_ml_model_transform_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type get_open_cypher_query_status_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | invalid_numeric_data_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | time_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | read_only_violation_exception() | parsing_exception(). -type get_propertygraph_statistics_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | statistics_not_available_exception() | read_only_violation_exception(). -type get_propertygraph_stream_errors() :: client_timeout_exception() | preconditions_failed_exception() | expired_stream_exception() | stream_records_not_found_exception() | throttling_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | memory_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type get_propertygraph_summary_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | statistics_not_available_exception() | read_only_violation_exception(). -type get_r_d_f_graph_summary_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | statistics_not_available_exception() | read_only_violation_exception(). -type get_sparql_statistics_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | statistics_not_available_exception() | read_only_violation_exception(). -type get_sparql_stream_errors() :: client_timeout_exception() | preconditions_failed_exception() | expired_stream_exception() | stream_records_not_found_exception() | throttling_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | memory_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type list_gremlin_queries_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | time_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | read_only_violation_exception() | parsing_exception(). -type list_loader_jobs_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | load_url_access_denied_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | bulk_load_id_not_found_exception() | unsupported_operation_exception() | internal_failure_exception(). -type list_ml_data_processing_jobs_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type list_ml_endpoints_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type list_ml_model_training_jobs_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type list_ml_model_transform_jobs_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type list_open_cypher_queries_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | invalid_numeric_data_exception() | constraint_violation_exception() | concurrent_modification_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | time_limit_exceeded_exception() | too_many_requests_exception() | illegal_argument_exception() | failure_by_query_exception() | unsupported_operation_exception() | read_only_violation_exception() | parsing_exception(). -type manage_propertygraph_statistics_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | statistics_not_available_exception() | read_only_violation_exception(). -type manage_sparql_statistics_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | access_denied_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception() | statistics_not_available_exception() | read_only_violation_exception(). -type start_loader_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | load_url_access_denied_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | too_many_requests_exception() | illegal_argument_exception() | bulk_load_id_not_found_exception() | unsupported_operation_exception() | s3_exception() | internal_failure_exception(). -type start_ml_data_processing_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type start_ml_model_training_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). -type start_ml_model_transform_job_errors() :: client_timeout_exception() | preconditions_failed_exception() | bad_request_exception() | constraint_violation_exception() | invalid_argument_exception() | invalid_parameter_exception() | missing_parameter_exception() | ml_resource_not_found_exception() | too_many_requests_exception() | illegal_argument_exception() | unsupported_operation_exception(). %%==================================================================== %% API %%==================================================================== %% @doc Cancels a Gremlin query. %% %% See Gremlin query cancellation: %% https://docs.aws.amazon.com/neptune/latest/userguide/gremlin-api-status-cancel.html %% for more information. %% %% 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:CancelQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#cancelquery %% IAM action in that cluster. -spec cancel_gremlin_query(aws_client:aws_client(), binary() | list(), cancel_gremlin_query_input()) -> {ok, cancel_gremlin_query_output(), tuple()} | {error, any()} | {error, cancel_gremlin_query_errors(), tuple()}. cancel_gremlin_query(Client, QueryId, Input) -> cancel_gremlin_query(Client, QueryId, Input, []). -spec cancel_gremlin_query(aws_client:aws_client(), binary() | list(), cancel_gremlin_query_input(), proplists:proplist()) -> {ok, cancel_gremlin_query_output(), tuple()} | {error, any()} | {error, cancel_gremlin_query_errors(), tuple()}. cancel_gremlin_query(Client, QueryId, Input0, Options0) -> Method = delete, Path = ["/gremlin/status/", aws_util:encode_uri(QueryId), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Cancels a specified load job. %% %% This is an HTTP `DELETE' request. See Neptune Loader Get-Status API: %% https://docs.aws.amazon.com/neptune/latest/userguide/load-api-reference-status.htm %% for more information. %% %% 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:CancelLoaderJob: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#cancelloaderjob %% IAM action in that cluster.. -spec cancel_loader_job(aws_client:aws_client(), binary() | list(), cancel_loader_job_input()) -> {ok, cancel_loader_job_output(), tuple()} | {error, any()} | {error, cancel_loader_job_errors(), tuple()}. cancel_loader_job(Client, LoadId, Input) -> cancel_loader_job(Client, LoadId, Input, []). -spec cancel_loader_job(aws_client:aws_client(), binary() | list(), cancel_loader_job_input(), proplists:proplist()) -> {ok, cancel_loader_job_output(), tuple()} | {error, any()} | {error, cancel_loader_job_errors(), tuple()}. cancel_loader_job(Client, LoadId, Input0, Options0) -> Method = delete, Path = ["/loader/", aws_util:encode_uri(LoadId), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Cancels a Neptune ML data processing job. %% %% See The `dataprocessing' command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-dataprocessing.html. %% %% 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:CancelMLDataProcessingJob: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#cancelmldataprocessingjob %% IAM action in that cluster. -spec cancel_ml_data_processing_job(aws_client:aws_client(), binary() | list(), cancel_ml_data_processing_job_input()) -> {ok, cancel_ml_data_processing_job_output(), tuple()} | {error, any()} | {error, cancel_ml_data_processing_job_errors(), tuple()}. cancel_ml_data_processing_job(Client, Id, Input) -> cancel_ml_data_processing_job(Client, Id, Input, []). -spec cancel_ml_data_processing_job(aws_client:aws_client(), binary() | list(), cancel_ml_data_processing_job_input(), proplists:proplist()) -> {ok, cancel_ml_data_processing_job_output(), tuple()} | {error, any()} | {error, cancel_ml_data_processing_job_errors(), tuple()}. cancel_ml_data_processing_job(Client, Id, Input0, Options0) -> Method = delete, Path = ["/ml/dataprocessing/", aws_util:encode_uri(Id), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, QueryMapping = [ {<<"clean">>, <<"clean">>}, {<<"neptuneIamRoleArn">>, <<"neptuneIamRoleArn">>} ], {Query_, Input} = aws_request:build_headers(QueryMapping, Input2), request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Cancels a Neptune ML model training job. %% %% See Model training using the `modeltraining' command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-modeltraining.html. %% %% 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:CancelMLModelTrainingJob: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#cancelmlmodeltrainingjob %% IAM action in that cluster. -spec cancel_ml_model_training_job(aws_client:aws_client(), binary() | list(), cancel_ml_model_training_job_input()) -> {ok, cancel_ml_model_training_job_output(), tuple()} | {error, any()} | {error, cancel_ml_model_training_job_errors(), tuple()}. cancel_ml_model_training_job(Client, Id, Input) -> cancel_ml_model_training_job(Client, Id, Input, []). -spec cancel_ml_model_training_job(aws_client:aws_client(), binary() | list(), cancel_ml_model_training_job_input(), proplists:proplist()) -> {ok, cancel_ml_model_training_job_output(), tuple()} | {error, any()} | {error, cancel_ml_model_training_job_errors(), tuple()}. cancel_ml_model_training_job(Client, Id, Input0, Options0) -> Method = delete, Path = ["/ml/modeltraining/", aws_util:encode_uri(Id), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, QueryMapping = [ {<<"clean">>, <<"clean">>}, {<<"neptuneIamRoleArn">>, <<"neptuneIamRoleArn">>} ], {Query_, Input} = aws_request:build_headers(QueryMapping, Input2), request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Cancels a specified model transform job. %% %% See Use a trained model to generate new model artifacts: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-model-transform.html. %% %% 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:CancelMLModelTransformJob: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#cancelmlmodeltransformjob %% IAM action in that cluster. -spec cancel_ml_model_transform_job(aws_client:aws_client(), binary() | list(), cancel_ml_model_transform_job_input()) -> {ok, cancel_ml_model_transform_job_output(), tuple()} | {error, any()} | {error, cancel_ml_model_transform_job_errors(), tuple()}. cancel_ml_model_transform_job(Client, Id, Input) -> cancel_ml_model_transform_job(Client, Id, Input, []). -spec cancel_ml_model_transform_job(aws_client:aws_client(), binary() | list(), cancel_ml_model_transform_job_input(), proplists:proplist()) -> {ok, cancel_ml_model_transform_job_output(), tuple()} | {error, any()} | {error, cancel_ml_model_transform_job_errors(), tuple()}. cancel_ml_model_transform_job(Client, Id, Input0, Options0) -> Method = delete, Path = ["/ml/modeltransform/", aws_util:encode_uri(Id), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, QueryMapping = [ {<<"clean">>, <<"clean">>}, {<<"neptuneIamRoleArn">>, <<"neptuneIamRoleArn">>} ], {Query_, Input} = aws_request:build_headers(QueryMapping, Input2), request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Cancels a specified openCypher query. %% %% See Neptune openCypher status endpoint: %% https://docs.aws.amazon.com/neptune/latest/userguide/access-graph-opencypher-status.html %% for more information. %% %% 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:CancelQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#cancelquery %% IAM action in that cluster. -spec cancel_open_cypher_query(aws_client:aws_client(), binary() | list(), cancel_open_cypher_query_input()) -> {ok, cancel_open_cypher_query_output(), tuple()} | {error, any()} | {error, cancel_open_cypher_query_errors(), tuple()}. cancel_open_cypher_query(Client, QueryId, Input) -> cancel_open_cypher_query(Client, QueryId, Input, []). -spec cancel_open_cypher_query(aws_client:aws_client(), binary() | list(), cancel_open_cypher_query_input(), proplists:proplist()) -> {ok, cancel_open_cypher_query_output(), tuple()} | {error, any()} | {error, cancel_open_cypher_query_errors(), tuple()}. cancel_open_cypher_query(Client, QueryId, Input0, Options0) -> Method = delete, Path = ["/opencypher/status/", aws_util:encode_uri(QueryId), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, QueryMapping = [ {<<"silent">>, <<"silent">>} ], {Query_, Input} = aws_request:build_headers(QueryMapping, Input2), request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Creates a new Neptune ML inference endpoint that lets you query one %% specific model that the model-training process constructed. %% %% See Managing inference endpoints using the endpoints command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-endpoints.html. %% %% 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:CreateMLEndpoint: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#createmlendpoint %% IAM action in that cluster. -spec create_ml_endpoint(aws_client:aws_client(), create_ml_endpoint_input()) -> {ok, create_ml_endpoint_output(), tuple()} | {error, any()} | {error, create_ml_endpoint_errors(), tuple()}. create_ml_endpoint(Client, Input) -> create_ml_endpoint(Client, Input, []). -spec create_ml_endpoint(aws_client:aws_client(), create_ml_endpoint_input(), proplists:proplist()) -> {ok, create_ml_endpoint_output(), tuple()} | {error, any()} | {error, create_ml_endpoint_errors(), tuple()}. create_ml_endpoint(Client, Input0, Options0) -> Method = post, Path = ["/ml/endpoints"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Cancels the creation of a Neptune ML inference endpoint. %% %% See Managing inference endpoints using the endpoints command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-endpoints.html. %% %% 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:DeleteMLEndpoint: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#deletemlendpoint %% IAM action in that cluster. -spec delete_ml_endpoint(aws_client:aws_client(), binary() | list(), delete_ml_endpoint_input()) -> {ok, delete_ml_endpoint_output(), tuple()} | {error, any()} | {error, delete_ml_endpoint_errors(), tuple()}. delete_ml_endpoint(Client, Id, Input) -> delete_ml_endpoint(Client, Id, Input, []). -spec delete_ml_endpoint(aws_client:aws_client(), binary() | list(), delete_ml_endpoint_input(), proplists:proplist()) -> {ok, delete_ml_endpoint_output(), tuple()} | {error, any()} | {error, delete_ml_endpoint_errors(), tuple()}. delete_ml_endpoint(Client, Id, Input0, Options0) -> Method = delete, Path = ["/ml/endpoints/", aws_util:encode_uri(Id), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, QueryMapping = [ {<<"clean">>, <<"clean">>}, {<<"neptuneIamRoleArn">>, <<"neptuneIamRoleArn">>} ], {Query_, Input} = aws_request:build_headers(QueryMapping, Input2), request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Deletes statistics for Gremlin and openCypher (property graph) data. %% %% 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:DeleteStatistics: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#deletestatistics %% IAM action in that cluster. -spec delete_propertygraph_statistics(aws_client:aws_client(), #{}) -> {ok, delete_propertygraph_statistics_output(), tuple()} | {error, any()} | {error, delete_propertygraph_statistics_errors(), tuple()}. delete_propertygraph_statistics(Client, Input) -> delete_propertygraph_statistics(Client, Input, []). -spec delete_propertygraph_statistics(aws_client:aws_client(), #{}, proplists:proplist()) -> {ok, delete_propertygraph_statistics_output(), tuple()} | {error, any()} | {error, delete_propertygraph_statistics_errors(), tuple()}. delete_propertygraph_statistics(Client, Input0, Options0) -> Method = delete, Path = ["/propertygraph/statistics"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Deletes SPARQL statistics %% %% 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:DeleteStatistics: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#deletestatistics %% IAM action in that cluster. -spec delete_sparql_statistics(aws_client:aws_client(), #{}) -> {ok, delete_sparql_statistics_output(), tuple()} | {error, any()} | {error, delete_sparql_statistics_errors(), tuple()}. delete_sparql_statistics(Client, Input) -> delete_sparql_statistics(Client, Input, []). -spec delete_sparql_statistics(aws_client:aws_client(), #{}, proplists:proplist()) -> {ok, delete_sparql_statistics_output(), tuple()} | {error, any()} | {error, delete_sparql_statistics_errors(), tuple()}. delete_sparql_statistics(Client, Input0, Options0) -> Method = delete, Path = ["/sparql/statistics"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc The fast reset REST API lets you reset a Neptune graph quicky and %% easily, removing all of its data. %% %% Neptune fast reset is a two-step process. First you call %% `ExecuteFastReset' with `action' set to %% `initiateDatabaseReset'. This returns a UUID token which you then %% include when calling `ExecuteFastReset' again with `action' set to %% `performDatabaseReset'. See Empty an Amazon Neptune DB cluster using %% the fast reset API: %% https://docs.aws.amazon.com/neptune/latest/userguide/manage-console-fast-reset.html. %% %% 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:ResetDatabase: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#resetdatabase %% IAM action in that cluster. -spec execute_fast_reset(aws_client:aws_client(), execute_fast_reset_input()) -> {ok, execute_fast_reset_output(), tuple()} | {error, any()} | {error, execute_fast_reset_errors(), tuple()}. execute_fast_reset(Client, Input) -> execute_fast_reset(Client, Input, []). -spec execute_fast_reset(aws_client:aws_client(), execute_fast_reset_input(), proplists:proplist()) -> {ok, execute_fast_reset_output(), tuple()} | {error, any()} | {error, execute_fast_reset_errors(), tuple()}. execute_fast_reset(Client, Input0, Options0) -> Method = post, Path = ["/system"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Executes a Gremlin Explain query. %% %% Amazon Neptune has added a Gremlin feature named `explain' that %% provides is a self-service tool for understanding the execution approach %% being taken by the Neptune engine for the query. You invoke it by adding %% an `explain' parameter to an HTTP call that submits a Gremlin query. %% %% The explain feature provides information about the logical structure of %% query execution plans. You can use this information to identify potential %% evaluation and execution bottlenecks and to tune your query, as explained %% in Tuning Gremlin queries: %% https://docs.aws.amazon.com/neptune/latest/userguide/gremlin-traversal-tuning.html. %% You can also use query hints to improve query execution plans. %% %% 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 one of the following IAM actions in that %% cluster, depending on the query: %% %% neptune-db:ReadDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#readdataviaquery %% %% neptune-db:WriteDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#writedataviaquery %% %% neptune-db:DeleteDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#deletedataviaquery %% %% Note that the neptune-db:QueryLanguage:Gremlin: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% 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: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec execute_gremlin_explain_query(aws_client:aws_client(), execute_gremlin_explain_query_input()) -> {ok, execute_gremlin_explain_query_output(), tuple()} | {error, any()} | {error, execute_gremlin_explain_query_errors(), tuple()}. execute_gremlin_explain_query(Client, Input) -> execute_gremlin_explain_query(Client, Input, []). -spec execute_gremlin_explain_query(aws_client:aws_client(), execute_gremlin_explain_query_input(), proplists:proplist()) -> {ok, execute_gremlin_explain_query_output(), tuple()} | {error, any()} | {error, execute_gremlin_explain_query_errors(), tuple()}. execute_gremlin_explain_query(Client, Input0, Options0) -> Method = post, Path = ["/gremlin/explain"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc 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: %% https://docs.aws.amazon.com/neptune/latest/userguide/gremlin-profile-api.html %% 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: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#readdataviaquery %% IAM action in that cluster. %% %% Note that the neptune-db:QueryLanguage:Gremlin: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% 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: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec execute_gremlin_profile_query(aws_client:aws_client(), execute_gremlin_profile_query_input()) -> {ok, execute_gremlin_profile_query_output(), tuple()} | {error, any()} | {error, execute_gremlin_profile_query_errors(), tuple()}. execute_gremlin_profile_query(Client, Input) -> execute_gremlin_profile_query(Client, Input, []). -spec execute_gremlin_profile_query(aws_client:aws_client(), execute_gremlin_profile_query_input(), proplists:proplist()) -> {ok, execute_gremlin_profile_query_output(), tuple()} | {error, any()} | {error, execute_gremlin_profile_query_errors(), tuple()}. execute_gremlin_profile_query(Client, Input0, Options0) -> Method = post, Path = ["/gremlin/profile"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc This commands executes a Gremlin query. %% %% Amazon Neptune is compatible with Apache TinkerPop3 and Gremlin, so you %% can use the Gremlin traversal language to query the graph, as described %% under The Graph: %% https://tinkerpop.apache.org/docs/current/reference/#graph in the Apache %% TinkerPop3 documentation. More details can also be found in Accessing a %% Neptune graph with Gremlin: %% https://docs.aws.amazon.com/neptune/latest/userguide/access-graph-gremlin.html. %% %% 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 enables one of the following IAM actions in that %% cluster, depending on the query: %% %% neptune-db:ReadDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#readdataviaquery %% %% neptune-db:WriteDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#writedataviaquery %% %% neptune-db:DeleteDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#deletedataviaquery %% %% Note that the neptune-db:QueryLanguage:Gremlin: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% 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: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec execute_gremlin_query(aws_client:aws_client(), execute_gremlin_query_input()) -> {ok, execute_gremlin_query_output(), tuple()} | {error, any()} | {error, execute_gremlin_query_errors(), tuple()}. execute_gremlin_query(Client, Input) -> execute_gremlin_query(Client, Input, []). -spec execute_gremlin_query(aws_client:aws_client(), execute_gremlin_query_input(), proplists:proplist()) -> {ok, execute_gremlin_query_output(), tuple()} | {error, any()} | {error, execute_gremlin_query_errors(), tuple()}. execute_gremlin_query(Client, Input0, Options0) -> Method = post, Path = ["/gremlin"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], HeadersMapping = [ {<<"accept">>, <<"serializer">>} ], {Headers, Input1} = aws_request:build_headers(HeadersMapping, Input0), CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Executes an openCypher `explain' request. %% %% See The openCypher explain feature: %% https://docs.aws.amazon.com/neptune/latest/userguide/access-graph-opencypher-explain.html %% for more information. %% %% 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: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#readdataviaquery %% IAM action in that cluster. %% %% Note that the neptune-db:QueryLanguage:OpenCypher: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% IAM condition key can be used in the policy document to restrict the use %% of openCypher queries (see Condition keys available in Neptune IAM %% data-access policy statements: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec execute_open_cypher_explain_query(aws_client:aws_client(), execute_open_cypher_explain_query_input()) -> {ok, execute_open_cypher_explain_query_output(), tuple()} | {error, any()} | {error, execute_open_cypher_explain_query_errors(), tuple()}. execute_open_cypher_explain_query(Client, Input) -> execute_open_cypher_explain_query(Client, Input, []). -spec execute_open_cypher_explain_query(aws_client:aws_client(), execute_open_cypher_explain_query_input(), proplists:proplist()) -> {ok, execute_open_cypher_explain_query_output(), tuple()} | {error, any()} | {error, execute_open_cypher_explain_query_errors(), tuple()}. execute_open_cypher_explain_query(Client, Input0, Options0) -> Method = post, Path = ["/opencypher/explain"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Executes an openCypher query. %% %% See Accessing the Neptune Graph with openCypher: %% https://docs.aws.amazon.com/neptune/latest/userguide/access-graph-opencypher.html %% for more information. %% %% Neptune supports building graph applications using openCypher, which is %% currently one of the most popular query languages among developers working %% with graph databases. Developers, business analysts, and data scientists %% like openCypher's declarative, SQL-inspired syntax because it provides %% a familiar structure in which to querying property graphs. %% %% The openCypher language was originally developed by Neo4j, then %% open-sourced in 2015 and contributed to the openCypher project: %% https://opencypher.org/ under an Apache 2 open-source license. %% %% Note that 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 one of the following IAM actions in that %% cluster, depending on the query: %% %% neptune-db:ReadDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#readdataviaquery %% %% neptune-db:WriteDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#writedataviaquery %% %% neptune-db:DeleteDataViaQuery: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#deletedataviaquery %% %% Note also that the neptune-db:QueryLanguage:OpenCypher: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% IAM condition key can be used in the policy document to restrict the use %% of openCypher queries (see Condition keys available in Neptune IAM %% data-access policy statements: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec execute_open_cypher_query(aws_client:aws_client(), execute_open_cypher_query_input()) -> {ok, execute_open_cypher_query_output(), tuple()} | {error, any()} | {error, execute_open_cypher_query_errors(), tuple()}. execute_open_cypher_query(Client, Input) -> execute_open_cypher_query(Client, Input, []). -spec execute_open_cypher_query(aws_client:aws_client(), execute_open_cypher_query_input(), proplists:proplist()) -> {ok, execute_open_cypher_query_output(), tuple()} | {error, any()} | {error, execute_open_cypher_query_errors(), tuple()}. execute_open_cypher_query(Client, Input0, Options0) -> Method = post, Path = ["/opencypher"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Retrieves the status of the graph database on the host. %% %% 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:GetEngineStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getenginestatus %% IAM action in that cluster. -spec get_engine_status(aws_client:aws_client()) -> {ok, get_engine_status_output(), tuple()} | {error, any()} | {error, get_engine_status_errors(), tuple()}. get_engine_status(Client) when is_map(Client) -> get_engine_status(Client, #{}, #{}). -spec get_engine_status(aws_client:aws_client(), map(), map()) -> {ok, get_engine_status_output(), tuple()} | {error, any()} | {error, get_engine_status_errors(), tuple()}. get_engine_status(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_engine_status(Client, QueryMap, HeadersMap, []). -spec get_engine_status(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, get_engine_status_output(), tuple()} | {error, any()} | {error, get_engine_status_errors(), tuple()}. get_engine_status(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/status"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query_ = [], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets the status of a specified Gremlin query. %% %% 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:GetQueryStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getquerystatus %% IAM action in that cluster. %% %% Note that the neptune-db:QueryLanguage:Gremlin: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% 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: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec get_gremlin_query_status(aws_client:aws_client(), binary() | list()) -> {ok, get_gremlin_query_status_output(), tuple()} | {error, any()} | {error, get_gremlin_query_status_errors(), tuple()}. get_gremlin_query_status(Client, QueryId) when is_map(Client) -> get_gremlin_query_status(Client, QueryId, #{}, #{}). -spec get_gremlin_query_status(aws_client:aws_client(), binary() | list(), map(), map()) -> {ok, get_gremlin_query_status_output(), tuple()} | {error, any()} | {error, get_gremlin_query_status_errors(), tuple()}. get_gremlin_query_status(Client, QueryId, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_gremlin_query_status(Client, QueryId, QueryMap, HeadersMap, []). -spec get_gremlin_query_status(aws_client:aws_client(), binary() | list(), map(), map(), proplists:proplist()) -> {ok, get_gremlin_query_status_output(), tuple()} | {error, any()} | {error, get_gremlin_query_status_errors(), tuple()}. get_gremlin_query_status(Client, QueryId, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/gremlin/status/", aws_util:encode_uri(QueryId), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query_ = [], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets status information about a specified load job. %% %% Neptune keeps track of the most recent 1,024 bulk load jobs, and stores %% the last 10,000 error details per job. %% %% See Neptune Loader Get-Status API: %% https://docs.aws.amazon.com/neptune/latest/userguide/load-api-reference-status.htm %% for more information. %% %% 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:GetLoaderJobStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getloaderjobstatus %% IAM action in that cluster.. -spec get_loader_job_status(aws_client:aws_client(), binary() | list()) -> {ok, get_loader_job_status_output(), tuple()} | {error, any()} | {error, get_loader_job_status_errors(), tuple()}. get_loader_job_status(Client, LoadId) when is_map(Client) -> get_loader_job_status(Client, LoadId, #{}, #{}). -spec get_loader_job_status(aws_client:aws_client(), binary() | list(), map(), map()) -> {ok, get_loader_job_status_output(), tuple()} | {error, any()} | {error, get_loader_job_status_errors(), tuple()}. get_loader_job_status(Client, LoadId, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_loader_job_status(Client, LoadId, QueryMap, HeadersMap, []). -spec get_loader_job_status(aws_client:aws_client(), binary() | list(), map(), map(), proplists:proplist()) -> {ok, get_loader_job_status_output(), tuple()} | {error, any()} | {error, get_loader_job_status_errors(), tuple()}. get_loader_job_status(Client, LoadId, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/loader/", aws_util:encode_uri(LoadId), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"details">>, maps:get(<<"details">>, QueryMap, undefined)}, {<<"errors">>, maps:get(<<"errors">>, QueryMap, undefined)}, {<<"errorsPerPage">>, maps:get(<<"errorsPerPage">>, QueryMap, undefined)}, {<<"page">>, maps:get(<<"page">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Retrieves information about a specified data processing job. %% %% See The `dataprocessing' command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-dataprocessing.html. %% %% 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:neptune-db:GetMLDataProcessingJobStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getmldataprocessingjobstatus %% IAM action in that cluster. -spec get_ml_data_processing_job(aws_client:aws_client(), binary() | list()) -> {ok, get_ml_data_processing_job_output(), tuple()} | {error, any()} | {error, get_ml_data_processing_job_errors(), tuple()}. get_ml_data_processing_job(Client, Id) when is_map(Client) -> get_ml_data_processing_job(Client, Id, #{}, #{}). -spec get_ml_data_processing_job(aws_client:aws_client(), binary() | list(), map(), map()) -> {ok, get_ml_data_processing_job_output(), tuple()} | {error, any()} | {error, get_ml_data_processing_job_errors(), tuple()}. get_ml_data_processing_job(Client, Id, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_ml_data_processing_job(Client, Id, QueryMap, HeadersMap, []). -spec get_ml_data_processing_job(aws_client:aws_client(), binary() | list(), map(), map(), proplists:proplist()) -> {ok, get_ml_data_processing_job_output(), tuple()} | {error, any()} | {error, get_ml_data_processing_job_errors(), tuple()}. get_ml_data_processing_job(Client, Id, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/ml/dataprocessing/", aws_util:encode_uri(Id), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"neptuneIamRoleArn">>, maps:get(<<"neptuneIamRoleArn">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Retrieves details about an inference endpoint. %% %% See Managing inference endpoints using the endpoints command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-endpoints.html. %% %% 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:GetMLEndpointStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getmlendpointstatus %% IAM action in that cluster. -spec get_ml_endpoint(aws_client:aws_client(), binary() | list()) -> {ok, get_ml_endpoint_output(), tuple()} | {error, any()} | {error, get_ml_endpoint_errors(), tuple()}. get_ml_endpoint(Client, Id) when is_map(Client) -> get_ml_endpoint(Client, Id, #{}, #{}). -spec get_ml_endpoint(aws_client:aws_client(), binary() | list(), map(), map()) -> {ok, get_ml_endpoint_output(), tuple()} | {error, any()} | {error, get_ml_endpoint_errors(), tuple()}. get_ml_endpoint(Client, Id, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_ml_endpoint(Client, Id, QueryMap, HeadersMap, []). -spec get_ml_endpoint(aws_client:aws_client(), binary() | list(), map(), map(), proplists:proplist()) -> {ok, get_ml_endpoint_output(), tuple()} | {error, any()} | {error, get_ml_endpoint_errors(), tuple()}. get_ml_endpoint(Client, Id, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/ml/endpoints/", aws_util:encode_uri(Id), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"neptuneIamRoleArn">>, maps:get(<<"neptuneIamRoleArn">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Retrieves information about a Neptune ML model training job. %% %% See Model training using the `modeltraining' command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-modeltraining.html. %% %% 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:GetMLModelTrainingJobStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getmlmodeltrainingjobstatus %% IAM action in that cluster. -spec get_ml_model_training_job(aws_client:aws_client(), binary() | list()) -> {ok, get_ml_model_training_job_output(), tuple()} | {error, any()} | {error, get_ml_model_training_job_errors(), tuple()}. get_ml_model_training_job(Client, Id) when is_map(Client) -> get_ml_model_training_job(Client, Id, #{}, #{}). -spec get_ml_model_training_job(aws_client:aws_client(), binary() | list(), map(), map()) -> {ok, get_ml_model_training_job_output(), tuple()} | {error, any()} | {error, get_ml_model_training_job_errors(), tuple()}. get_ml_model_training_job(Client, Id, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_ml_model_training_job(Client, Id, QueryMap, HeadersMap, []). -spec get_ml_model_training_job(aws_client:aws_client(), binary() | list(), map(), map(), proplists:proplist()) -> {ok, get_ml_model_training_job_output(), tuple()} | {error, any()} | {error, get_ml_model_training_job_errors(), tuple()}. get_ml_model_training_job(Client, Id, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/ml/modeltraining/", aws_util:encode_uri(Id), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"neptuneIamRoleArn">>, maps:get(<<"neptuneIamRoleArn">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets information about a specified model transform job. %% %% See Use a trained model to generate new model artifacts: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-model-transform.html. %% %% 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:GetMLModelTransformJobStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getmlmodeltransformjobstatus %% IAM action in that cluster. -spec get_ml_model_transform_job(aws_client:aws_client(), binary() | list()) -> {ok, get_ml_model_transform_job_output(), tuple()} | {error, any()} | {error, get_ml_model_transform_job_errors(), tuple()}. get_ml_model_transform_job(Client, Id) when is_map(Client) -> get_ml_model_transform_job(Client, Id, #{}, #{}). -spec get_ml_model_transform_job(aws_client:aws_client(), binary() | list(), map(), map()) -> {ok, get_ml_model_transform_job_output(), tuple()} | {error, any()} | {error, get_ml_model_transform_job_errors(), tuple()}. get_ml_model_transform_job(Client, Id, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_ml_model_transform_job(Client, Id, QueryMap, HeadersMap, []). -spec get_ml_model_transform_job(aws_client:aws_client(), binary() | list(), map(), map(), proplists:proplist()) -> {ok, get_ml_model_transform_job_output(), tuple()} | {error, any()} | {error, get_ml_model_transform_job_errors(), tuple()}. get_ml_model_transform_job(Client, Id, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/ml/modeltransform/", aws_util:encode_uri(Id), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"neptuneIamRoleArn">>, maps:get(<<"neptuneIamRoleArn">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Retrieves the status of a specified openCypher query. %% %% 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:GetQueryStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getquerystatus %% IAM action in that cluster. %% %% Note that the neptune-db:QueryLanguage:OpenCypher: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% IAM condition key can be used in the policy document to restrict the use %% of openCypher queries (see Condition keys available in Neptune IAM %% data-access policy statements: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec get_open_cypher_query_status(aws_client:aws_client(), binary() | list()) -> {ok, get_open_cypher_query_status_output(), tuple()} | {error, any()} | {error, get_open_cypher_query_status_errors(), tuple()}. get_open_cypher_query_status(Client, QueryId) when is_map(Client) -> get_open_cypher_query_status(Client, QueryId, #{}, #{}). -spec get_open_cypher_query_status(aws_client:aws_client(), binary() | list(), map(), map()) -> {ok, get_open_cypher_query_status_output(), tuple()} | {error, any()} | {error, get_open_cypher_query_status_errors(), tuple()}. get_open_cypher_query_status(Client, QueryId, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_open_cypher_query_status(Client, QueryId, QueryMap, HeadersMap, []). -spec get_open_cypher_query_status(aws_client:aws_client(), binary() | list(), map(), map(), proplists:proplist()) -> {ok, get_open_cypher_query_status_output(), tuple()} | {error, any()} | {error, get_open_cypher_query_status_errors(), tuple()}. get_open_cypher_query_status(Client, QueryId, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/opencypher/status/", aws_util:encode_uri(QueryId), ""], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query_ = [], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets property graph statistics (Gremlin and openCypher). %% %% 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:GetStatisticsStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getstatisticsstatus %% IAM action in that cluster. -spec get_propertygraph_statistics(aws_client:aws_client()) -> {ok, get_propertygraph_statistics_output(), tuple()} | {error, any()} | {error, get_propertygraph_statistics_errors(), tuple()}. get_propertygraph_statistics(Client) when is_map(Client) -> get_propertygraph_statistics(Client, #{}, #{}). -spec get_propertygraph_statistics(aws_client:aws_client(), map(), map()) -> {ok, get_propertygraph_statistics_output(), tuple()} | {error, any()} | {error, get_propertygraph_statistics_errors(), tuple()}. get_propertygraph_statistics(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_propertygraph_statistics(Client, QueryMap, HeadersMap, []). -spec get_propertygraph_statistics(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, get_propertygraph_statistics_output(), tuple()} | {error, any()} | {error, get_propertygraph_statistics_errors(), tuple()}. get_propertygraph_statistics(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/propertygraph/statistics"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query_ = [], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets a stream for a property graph. %% %% With the Neptune Streams feature, you can generate a complete sequence of %% change-log entries that record every change made to your graph data as it %% happens. `GetPropertygraphStream' lets you collect these change-log %% entries for a property graph. %% %% The Neptune streams feature needs to be enabled on your Neptune DBcluster. %% To enable streams, set the neptune_streams: %% https://docs.aws.amazon.com/neptune/latest/userguide/parameters.html#parameters-db-cluster-parameters-neptune_streams %% DB cluster parameter to `1'. %% %% See Capturing graph changes in real time using Neptune streams: %% https://docs.aws.amazon.com/neptune/latest/userguide/streams.html. %% %% 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:GetStreamRecords: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getstreamrecords %% IAM action in that cluster. %% %% 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 enables one of the following IAM actions, depending %% on the query: %% %% Note that you can restrict property-graph queries using the following IAM %% context keys: %% %% neptune-db:QueryLanguage:Gremlin: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% %% neptune-db:QueryLanguage:OpenCypher: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% %% See Condition keys available in Neptune IAM data-access policy statements: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec get_propertygraph_stream(aws_client:aws_client()) -> {ok, get_propertygraph_stream_output(), tuple()} | {error, any()} | {error, get_propertygraph_stream_errors(), tuple()}. get_propertygraph_stream(Client) when is_map(Client) -> get_propertygraph_stream(Client, #{}, #{}). -spec get_propertygraph_stream(aws_client:aws_client(), map(), map()) -> {ok, get_propertygraph_stream_output(), tuple()} | {error, any()} | {error, get_propertygraph_stream_errors(), tuple()}. get_propertygraph_stream(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_propertygraph_stream(Client, QueryMap, HeadersMap, []). -spec get_propertygraph_stream(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, get_propertygraph_stream_output(), tuple()} | {error, any()} | {error, get_propertygraph_stream_errors(), tuple()}. get_propertygraph_stream(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/propertygraph/stream"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers0 = [ {<<"Accept-Encoding">>, maps:get(<<"Accept-Encoding">>, HeadersMap, undefined)} ], Headers = [H || {_, V} = H <- Headers0, V =/= undefined], Query0_ = [ {<<"commitNum">>, maps:get(<<"commitNum">>, QueryMap, undefined)}, {<<"iteratorType">>, maps:get(<<"iteratorType">>, QueryMap, undefined)}, {<<"limit">>, maps:get(<<"limit">>, QueryMap, undefined)}, {<<"opNum">>, maps:get(<<"opNum">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets a graph summary for a property graph. %% %% 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:GetGraphSummary: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getgraphsummary %% IAM action in that cluster. -spec get_propertygraph_summary(aws_client:aws_client()) -> {ok, get_propertygraph_summary_output(), tuple()} | {error, any()} | {error, get_propertygraph_summary_errors(), tuple()}. get_propertygraph_summary(Client) when is_map(Client) -> get_propertygraph_summary(Client, #{}, #{}). -spec get_propertygraph_summary(aws_client:aws_client(), map(), map()) -> {ok, get_propertygraph_summary_output(), tuple()} | {error, any()} | {error, get_propertygraph_summary_errors(), tuple()}. get_propertygraph_summary(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_propertygraph_summary(Client, QueryMap, HeadersMap, []). -spec get_propertygraph_summary(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, get_propertygraph_summary_output(), tuple()} | {error, any()} | {error, get_propertygraph_summary_errors(), tuple()}. get_propertygraph_summary(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/propertygraph/statistics/summary"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"mode">>, maps:get(<<"mode">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets a graph summary for an RDF graph. %% %% 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:GetGraphSummary: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getgraphsummary %% IAM action in that cluster. -spec get_r_d_f_graph_summary(aws_client:aws_client()) -> {ok, get_r_d_f_graph_summary_output(), tuple()} | {error, any()} | {error, get_r_d_f_graph_summary_errors(), tuple()}. get_r_d_f_graph_summary(Client) when is_map(Client) -> get_r_d_f_graph_summary(Client, #{}, #{}). -spec get_r_d_f_graph_summary(aws_client:aws_client(), map(), map()) -> {ok, get_r_d_f_graph_summary_output(), tuple()} | {error, any()} | {error, get_r_d_f_graph_summary_errors(), tuple()}. get_r_d_f_graph_summary(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_r_d_f_graph_summary(Client, QueryMap, HeadersMap, []). -spec get_r_d_f_graph_summary(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, get_r_d_f_graph_summary_output(), tuple()} | {error, any()} | {error, get_r_d_f_graph_summary_errors(), tuple()}. get_r_d_f_graph_summary(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/rdf/statistics/summary"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"mode">>, maps:get(<<"mode">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets RDF statistics (SPARQL). -spec get_sparql_statistics(aws_client:aws_client()) -> {ok, get_sparql_statistics_output(), tuple()} | {error, any()} | {error, get_sparql_statistics_errors(), tuple()}. get_sparql_statistics(Client) when is_map(Client) -> get_sparql_statistics(Client, #{}, #{}). -spec get_sparql_statistics(aws_client:aws_client(), map(), map()) -> {ok, get_sparql_statistics_output(), tuple()} | {error, any()} | {error, get_sparql_statistics_errors(), tuple()}. get_sparql_statistics(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_sparql_statistics(Client, QueryMap, HeadersMap, []). -spec get_sparql_statistics(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, get_sparql_statistics_output(), tuple()} | {error, any()} | {error, get_sparql_statistics_errors(), tuple()}. get_sparql_statistics(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/sparql/statistics"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query_ = [], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Gets a stream for an RDF graph. %% %% With the Neptune Streams feature, you can generate a complete sequence of %% change-log entries that record every change made to your graph data as it %% happens. `GetSparqlStream' lets you collect these change-log entries %% for an RDF graph. %% %% The Neptune streams feature needs to be enabled on your Neptune DBcluster. %% To enable streams, set the neptune_streams: %% https://docs.aws.amazon.com/neptune/latest/userguide/parameters.html#parameters-db-cluster-parameters-neptune_streams %% DB cluster parameter to `1'. %% %% See Capturing graph changes in real time using Neptune streams: %% https://docs.aws.amazon.com/neptune/latest/userguide/streams.html. %% %% 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:GetStreamRecords: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getstreamrecords %% IAM action in that cluster. %% %% Note that the neptune-db:QueryLanguage:Sparql: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% IAM condition key can be used in the policy document to restrict the use %% of SPARQL queries (see Condition keys available in Neptune IAM data-access %% policy statements: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec get_sparql_stream(aws_client:aws_client()) -> {ok, get_sparql_stream_output(), tuple()} | {error, any()} | {error, get_sparql_stream_errors(), tuple()}. get_sparql_stream(Client) when is_map(Client) -> get_sparql_stream(Client, #{}, #{}). -spec get_sparql_stream(aws_client:aws_client(), map(), map()) -> {ok, get_sparql_stream_output(), tuple()} | {error, any()} | {error, get_sparql_stream_errors(), tuple()}. get_sparql_stream(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> get_sparql_stream(Client, QueryMap, HeadersMap, []). -spec get_sparql_stream(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, get_sparql_stream_output(), tuple()} | {error, any()} | {error, get_sparql_stream_errors(), tuple()}. get_sparql_stream(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/sparql/stream"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers0 = [ {<<"Accept-Encoding">>, maps:get(<<"Accept-Encoding">>, HeadersMap, undefined)} ], Headers = [H || {_, V} = H <- Headers0, V =/= undefined], Query0_ = [ {<<"commitNum">>, maps:get(<<"commitNum">>, QueryMap, undefined)}, {<<"iteratorType">>, maps:get(<<"iteratorType">>, QueryMap, undefined)}, {<<"limit">>, maps:get(<<"limit">>, QueryMap, undefined)}, {<<"opNum">>, maps:get(<<"opNum">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Lists active Gremlin queries. %% %% See Gremlin query status API: %% https://docs.aws.amazon.com/neptune/latest/userguide/gremlin-api-status.html %% for details about the output. %% %% 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:GetQueryStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getquerystatus %% IAM action in that cluster. %% %% Note that the neptune-db:QueryLanguage:Gremlin: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% 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: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec list_gremlin_queries(aws_client:aws_client()) -> {ok, list_gremlin_queries_output(), tuple()} | {error, any()} | {error, list_gremlin_queries_errors(), tuple()}. list_gremlin_queries(Client) when is_map(Client) -> list_gremlin_queries(Client, #{}, #{}). -spec list_gremlin_queries(aws_client:aws_client(), map(), map()) -> {ok, list_gremlin_queries_output(), tuple()} | {error, any()} | {error, list_gremlin_queries_errors(), tuple()}. list_gremlin_queries(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> list_gremlin_queries(Client, QueryMap, HeadersMap, []). -spec list_gremlin_queries(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, list_gremlin_queries_output(), tuple()} | {error, any()} | {error, list_gremlin_queries_errors(), tuple()}. list_gremlin_queries(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/gremlin/status"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"includeWaiting">>, maps:get(<<"includeWaiting">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Retrieves a list of the `loadIds' for all active loader jobs. %% %% 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:ListLoaderJobs: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#listloaderjobs %% IAM action in that cluster.. -spec list_loader_jobs(aws_client:aws_client()) -> {ok, list_loader_jobs_output(), tuple()} | {error, any()} | {error, list_loader_jobs_errors(), tuple()}. list_loader_jobs(Client) when is_map(Client) -> list_loader_jobs(Client, #{}, #{}). -spec list_loader_jobs(aws_client:aws_client(), map(), map()) -> {ok, list_loader_jobs_output(), tuple()} | {error, any()} | {error, list_loader_jobs_errors(), tuple()}. list_loader_jobs(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> list_loader_jobs(Client, QueryMap, HeadersMap, []). -spec list_loader_jobs(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, list_loader_jobs_output(), tuple()} | {error, any()} | {error, list_loader_jobs_errors(), tuple()}. list_loader_jobs(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/loader"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"includeQueuedLoads">>, maps:get(<<"includeQueuedLoads">>, QueryMap, undefined)}, {<<"limit">>, maps:get(<<"limit">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Returns a list of Neptune ML data processing jobs. %% %% See Listing active data-processing jobs using the Neptune ML %% dataprocessing command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-dataprocessing.html#machine-learning-api-dataprocessing-list-jobs. %% %% 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:ListMLDataProcessingJobs: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#listmldataprocessingjobs %% IAM action in that cluster. -spec list_ml_data_processing_jobs(aws_client:aws_client()) -> {ok, list_ml_data_processing_jobs_output(), tuple()} | {error, any()} | {error, list_ml_data_processing_jobs_errors(), tuple()}. list_ml_data_processing_jobs(Client) when is_map(Client) -> list_ml_data_processing_jobs(Client, #{}, #{}). -spec list_ml_data_processing_jobs(aws_client:aws_client(), map(), map()) -> {ok, list_ml_data_processing_jobs_output(), tuple()} | {error, any()} | {error, list_ml_data_processing_jobs_errors(), tuple()}. list_ml_data_processing_jobs(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> list_ml_data_processing_jobs(Client, QueryMap, HeadersMap, []). -spec list_ml_data_processing_jobs(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, list_ml_data_processing_jobs_output(), tuple()} | {error, any()} | {error, list_ml_data_processing_jobs_errors(), tuple()}. list_ml_data_processing_jobs(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/ml/dataprocessing"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"maxItems">>, maps:get(<<"maxItems">>, QueryMap, undefined)}, {<<"neptuneIamRoleArn">>, maps:get(<<"neptuneIamRoleArn">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Lists existing inference endpoints. %% %% See Managing inference endpoints using the endpoints command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-endpoints.html. %% %% 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:ListMLEndpoints: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#listmlendpoints %% IAM action in that cluster. -spec list_ml_endpoints(aws_client:aws_client()) -> {ok, list_ml_endpoints_output(), tuple()} | {error, any()} | {error, list_ml_endpoints_errors(), tuple()}. list_ml_endpoints(Client) when is_map(Client) -> list_ml_endpoints(Client, #{}, #{}). -spec list_ml_endpoints(aws_client:aws_client(), map(), map()) -> {ok, list_ml_endpoints_output(), tuple()} | {error, any()} | {error, list_ml_endpoints_errors(), tuple()}. list_ml_endpoints(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> list_ml_endpoints(Client, QueryMap, HeadersMap, []). -spec list_ml_endpoints(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, list_ml_endpoints_output(), tuple()} | {error, any()} | {error, list_ml_endpoints_errors(), tuple()}. list_ml_endpoints(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/ml/endpoints"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"maxItems">>, maps:get(<<"maxItems">>, QueryMap, undefined)}, {<<"neptuneIamRoleArn">>, maps:get(<<"neptuneIamRoleArn">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Lists Neptune ML model-training jobs. %% %% See Model training using the `modeltraining' command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-modeltraining.html. %% %% 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:neptune-db:ListMLModelTrainingJobs: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#neptune-db:listmlmodeltrainingjobs %% IAM action in that cluster. -spec list_ml_model_training_jobs(aws_client:aws_client()) -> {ok, list_ml_model_training_jobs_output(), tuple()} | {error, any()} | {error, list_ml_model_training_jobs_errors(), tuple()}. list_ml_model_training_jobs(Client) when is_map(Client) -> list_ml_model_training_jobs(Client, #{}, #{}). -spec list_ml_model_training_jobs(aws_client:aws_client(), map(), map()) -> {ok, list_ml_model_training_jobs_output(), tuple()} | {error, any()} | {error, list_ml_model_training_jobs_errors(), tuple()}. list_ml_model_training_jobs(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> list_ml_model_training_jobs(Client, QueryMap, HeadersMap, []). -spec list_ml_model_training_jobs(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, list_ml_model_training_jobs_output(), tuple()} | {error, any()} | {error, list_ml_model_training_jobs_errors(), tuple()}. list_ml_model_training_jobs(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/ml/modeltraining"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"maxItems">>, maps:get(<<"maxItems">>, QueryMap, undefined)}, {<<"neptuneIamRoleArn">>, maps:get(<<"neptuneIamRoleArn">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Returns a list of model transform job IDs. %% %% See Use a trained model to generate new model artifacts: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-model-transform.html. %% %% 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:ListMLModelTransformJobs: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#listmlmodeltransformjobs %% IAM action in that cluster. -spec list_ml_model_transform_jobs(aws_client:aws_client()) -> {ok, list_ml_model_transform_jobs_output(), tuple()} | {error, any()} | {error, list_ml_model_transform_jobs_errors(), tuple()}. list_ml_model_transform_jobs(Client) when is_map(Client) -> list_ml_model_transform_jobs(Client, #{}, #{}). -spec list_ml_model_transform_jobs(aws_client:aws_client(), map(), map()) -> {ok, list_ml_model_transform_jobs_output(), tuple()} | {error, any()} | {error, list_ml_model_transform_jobs_errors(), tuple()}. list_ml_model_transform_jobs(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> list_ml_model_transform_jobs(Client, QueryMap, HeadersMap, []). -spec list_ml_model_transform_jobs(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, list_ml_model_transform_jobs_output(), tuple()} | {error, any()} | {error, list_ml_model_transform_jobs_errors(), tuple()}. list_ml_model_transform_jobs(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/ml/modeltransform"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"maxItems">>, maps:get(<<"maxItems">>, QueryMap, undefined)}, {<<"neptuneIamRoleArn">>, maps:get(<<"neptuneIamRoleArn">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Lists active openCypher queries. %% %% See Neptune openCypher status endpoint: %% https://docs.aws.amazon.com/neptune/latest/userguide/access-graph-opencypher-status.html %% for more information. %% %% 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:GetQueryStatus: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#getquerystatus %% IAM action in that cluster. %% %% Note that the neptune-db:QueryLanguage:OpenCypher: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html#iam-neptune-condition-keys %% IAM condition key can be used in the policy document to restrict the use %% of openCypher queries (see Condition keys available in Neptune IAM %% data-access policy statements: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-data-condition-keys.html). -spec list_open_cypher_queries(aws_client:aws_client()) -> {ok, list_open_cypher_queries_output(), tuple()} | {error, any()} | {error, list_open_cypher_queries_errors(), tuple()}. list_open_cypher_queries(Client) when is_map(Client) -> list_open_cypher_queries(Client, #{}, #{}). -spec list_open_cypher_queries(aws_client:aws_client(), map(), map()) -> {ok, list_open_cypher_queries_output(), tuple()} | {error, any()} | {error, list_open_cypher_queries_errors(), tuple()}. list_open_cypher_queries(Client, QueryMap, HeadersMap) when is_map(Client), is_map(QueryMap), is_map(HeadersMap) -> list_open_cypher_queries(Client, QueryMap, HeadersMap, []). -spec list_open_cypher_queries(aws_client:aws_client(), map(), map(), proplists:proplist()) -> {ok, list_open_cypher_queries_output(), tuple()} | {error, any()} | {error, list_open_cypher_queries_errors(), tuple()}. list_open_cypher_queries(Client, QueryMap, HeadersMap, Options0) when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) -> Path = ["/opencypher/status"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary} | Options2], Headers = [], Query0_ = [ {<<"includeWaiting">>, maps:get(<<"includeWaiting">>, QueryMap, undefined)} ], Query_ = [H || {_, V} = H <- Query0_, V =/= undefined], request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode). %% @doc Manages the generation and use of property graph statistics. %% %% 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:ManageStatistics: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#managestatistics %% IAM action in that cluster. -spec manage_propertygraph_statistics(aws_client:aws_client(), manage_propertygraph_statistics_input()) -> {ok, manage_propertygraph_statistics_output(), tuple()} | {error, any()} | {error, manage_propertygraph_statistics_errors(), tuple()}. manage_propertygraph_statistics(Client, Input) -> manage_propertygraph_statistics(Client, Input, []). -spec manage_propertygraph_statistics(aws_client:aws_client(), manage_propertygraph_statistics_input(), proplists:proplist()) -> {ok, manage_propertygraph_statistics_output(), tuple()} | {error, any()} | {error, manage_propertygraph_statistics_errors(), tuple()}. manage_propertygraph_statistics(Client, Input0, Options0) -> Method = post, Path = ["/propertygraph/statistics"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Manages the generation and use of RDF graph statistics. %% %% 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:ManageStatistics: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#managestatistics %% IAM action in that cluster. -spec manage_sparql_statistics(aws_client:aws_client(), manage_sparql_statistics_input()) -> {ok, manage_sparql_statistics_output(), tuple()} | {error, any()} | {error, manage_sparql_statistics_errors(), tuple()}. manage_sparql_statistics(Client, Input) -> manage_sparql_statistics(Client, Input, []). -spec manage_sparql_statistics(aws_client:aws_client(), manage_sparql_statistics_input(), proplists:proplist()) -> {ok, manage_sparql_statistics_output(), tuple()} | {error, any()} | {error, manage_sparql_statistics_errors(), tuple()}. manage_sparql_statistics(Client, Input0, Options0) -> Method = post, Path = ["/sparql/statistics"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Starts a Neptune bulk loader job to load data from an Amazon S3 %% bucket into a Neptune DB instance. %% %% See Using the Amazon Neptune Bulk Loader to Ingest Data: %% https://docs.aws.amazon.com/neptune/latest/userguide/bulk-load.html. %% %% 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:StartLoaderJob: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#startloaderjob %% IAM action in that cluster. -spec start_loader_job(aws_client:aws_client(), start_loader_job_input()) -> {ok, start_loader_job_output(), tuple()} | {error, any()} | {error, start_loader_job_errors(), tuple()}. start_loader_job(Client, Input) -> start_loader_job(Client, Input, []). -spec start_loader_job(aws_client:aws_client(), start_loader_job_input(), proplists:proplist()) -> {ok, start_loader_job_output(), tuple()} | {error, any()} | {error, start_loader_job_errors(), tuple()}. start_loader_job(Client, Input0, Options0) -> Method = post, Path = ["/loader"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Creates a new Neptune ML data processing job for processing the graph %% data exported from Neptune for training. %% %% See The `dataprocessing' command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-dataprocessing.html. %% %% 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:StartMLModelDataProcessingJob: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#startmlmodeldataprocessingjob %% IAM action in that cluster. -spec start_ml_data_processing_job(aws_client:aws_client(), start_ml_data_processing_job_input()) -> {ok, start_ml_data_processing_job_output(), tuple()} | {error, any()} | {error, start_ml_data_processing_job_errors(), tuple()}. start_ml_data_processing_job(Client, Input) -> start_ml_data_processing_job(Client, Input, []). -spec start_ml_data_processing_job(aws_client:aws_client(), start_ml_data_processing_job_input(), proplists:proplist()) -> {ok, start_ml_data_processing_job_output(), tuple()} | {error, any()} | {error, start_ml_data_processing_job_errors(), tuple()}. start_ml_data_processing_job(Client, Input0, Options0) -> Method = post, Path = ["/ml/dataprocessing"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Creates a new Neptune ML model training job. %% %% See Model training using the `modeltraining' command: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-api-modeltraining.html. %% %% 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:StartMLModelTrainingJob: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#startmlmodeltrainingjob %% IAM action in that cluster. -spec start_ml_model_training_job(aws_client:aws_client(), start_ml_model_training_job_input()) -> {ok, start_ml_model_training_job_output(), tuple()} | {error, any()} | {error, start_ml_model_training_job_errors(), tuple()}. start_ml_model_training_job(Client, Input) -> start_ml_model_training_job(Client, Input, []). -spec start_ml_model_training_job(aws_client:aws_client(), start_ml_model_training_job_input(), proplists:proplist()) -> {ok, start_ml_model_training_job_output(), tuple()} | {error, any()} | {error, start_ml_model_training_job_errors(), tuple()}. start_ml_model_training_job(Client, Input0, Options0) -> Method = post, Path = ["/ml/modeltraining"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %% @doc Creates a new model transform job. %% %% See Use a trained model to generate new model artifacts: %% https://docs.aws.amazon.com/neptune/latest/userguide/machine-learning-model-transform.html. %% %% 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:StartMLModelTransformJob: %% https://docs.aws.amazon.com/neptune/latest/userguide/iam-dp-actions.html#startmlmodeltransformjob %% IAM action in that cluster. -spec start_ml_model_transform_job(aws_client:aws_client(), start_ml_model_transform_job_input()) -> {ok, start_ml_model_transform_job_output(), tuple()} | {error, any()} | {error, start_ml_model_transform_job_errors(), tuple()}. start_ml_model_transform_job(Client, Input) -> start_ml_model_transform_job(Client, Input, []). -spec start_ml_model_transform_job(aws_client:aws_client(), start_ml_model_transform_job_input(), proplists:proplist()) -> {ok, start_ml_model_transform_job_output(), tuple()} | {error, any()} | {error, start_ml_model_transform_job_errors(), tuple()}. start_ml_model_transform_job(Client, Input0, Options0) -> Method = post, Path = ["/ml/modeltransform"], SuccessStatusCode = 200, {SendBodyAsBinary, Options1} = proplists_take(send_body_as_binary, Options0, false), {ReceiveBodyAsBinary, Options2} = proplists_take(receive_body_as_binary, Options1, false), Options = [{send_body_as_binary, SendBodyAsBinary}, {receive_body_as_binary, ReceiveBodyAsBinary}, {append_sha256_content_hash, false} | Options2], Headers = [], Input1 = Input0, CustomHeaders = [], Input2 = Input1, Query_ = [], Input = Input2, request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode). %%==================================================================== %% Internal functions %%==================================================================== -spec proplists_take(any(), proplists:proplist(), any()) -> {any(), proplists:proplist()}. proplists_take(Key, Proplist, Default) -> Value = proplists:get_value(Key, Proplist, Default), {Value, proplists:delete(Key, Proplist)}. -spec request(aws_client:aws_client(), atom(), iolist(), list(), list(), map() | undefined, list(), pos_integer() | undefined) -> {ok, {integer(), list()}} | {ok, Result, {integer(), list(), hackney:client()}} | {error, Error, {integer(), list(), hackney:client()}} | {error, term()} when Result :: map(), Error :: map(). request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) -> RequestFun = fun() -> do_request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) end, aws_request:request(RequestFun, Options). do_request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) -> Client1 = Client#{service => <<"neptune-db">>}, Host = build_host(<<"neptune-db">>, Client1), URL0 = build_url(Host, Path, Client1), URL = aws_request:add_query(URL0, Query), AdditionalHeaders1 = [ {<<"Host">>, Host} , {<<"Content-Type">>, <<"application/x-amz-json-1.1">>} ], Payload = case proplists:get_value(send_body_as_binary, Options) of true -> maps:get(<<"Body">>, Input, <<"">>); false -> encode_payload(Input) end, AdditionalHeaders = case proplists:get_value(append_sha256_content_hash, Options, false) of true -> add_checksum_hash_header(AdditionalHeaders1, Payload); false -> AdditionalHeaders1 end, Headers1 = aws_request:add_headers(AdditionalHeaders, Headers0), MethodBin = aws_request:method_to_binary(Method), SignedHeaders = aws_request:sign_request(Client1, MethodBin, URL, Headers1, Payload), Response = hackney:request(Method, URL, SignedHeaders, Payload, Options), DecodeBody = not proplists:get_value(receive_body_as_binary, Options), handle_response(Response, SuccessStatusCode, DecodeBody). add_checksum_hash_header(Headers, Body) -> [ {<<"X-Amz-CheckSum-SHA256">>, base64:encode(crypto:hash(sha256, Body))} | Headers ]. handle_response({ok, StatusCode, ResponseHeaders}, SuccessStatusCode, _DecodeBody) when StatusCode =:= 200; StatusCode =:= 202; StatusCode =:= 204; StatusCode =:= 206; StatusCode =:= SuccessStatusCode -> {ok, {StatusCode, ResponseHeaders}}; handle_response({ok, StatusCode, ResponseHeaders}, _, _DecodeBody) -> {error, {StatusCode, ResponseHeaders}}; handle_response({ok, StatusCode, ResponseHeaders, Client}, SuccessStatusCode, DecodeBody) when StatusCode =:= 200; StatusCode =:= 202; StatusCode =:= 204; StatusCode =:= 206; StatusCode =:= SuccessStatusCode -> case hackney:body(Client) of {ok, <<>>} when StatusCode =:= 200; StatusCode =:= SuccessStatusCode -> {ok, #{}, {StatusCode, ResponseHeaders, Client}}; {ok, Body} -> Result = case DecodeBody of true -> try jsx:decode(Body) catch Error:Reason:Stack -> erlang:raise(error, {body_decode_failed, Error, Reason, StatusCode, Body}, Stack) end; false -> #{<<"Body">> => Body} end, {ok, Result, {StatusCode, ResponseHeaders, Client}} end; handle_response({ok, StatusCode, _ResponseHeaders, _Client}, _, _DecodeBody) when StatusCode =:= 503 -> %% Retriable error if retries are enabled {error, service_unavailable}; handle_response({ok, StatusCode, ResponseHeaders, Client}, _, _DecodeBody) -> {ok, Body} = hackney:body(Client), try DecodedError = jsx:decode(Body), {error, DecodedError, {StatusCode, ResponseHeaders, Client}} catch Error:Reason:Stack -> erlang:raise(error, {body_decode_failed, Error, Reason, StatusCode, Body}, Stack) end; handle_response({error, Reason}, _, _DecodeBody) -> {error, Reason}. build_host(_EndpointPrefix, #{region := <<"local">>, endpoint := Endpoint}) -> Endpoint; build_host(_EndpointPrefix, #{region := <<"local">>}) -> <<"localhost">>; build_host(EndpointPrefix, #{region := Region, endpoint := Endpoint}) -> aws_util:binary_join([EndpointPrefix, Region, Endpoint], <<".">>). build_url(Host, Path0, Client) -> Proto = aws_client:proto(Client), Path = erlang:iolist_to_binary(Path0), Port = aws_client:port(Client), aws_util:binary_join([Proto, <<"://">>, Host, <<":">>, Port, Path], <<"">>). -spec encode_payload(undefined | map()) -> binary(). encode_payload(undefined) -> <<>>; encode_payload(Input) -> jsx:encode(Input).