Data import mutations - Arize AX Docs

Control file and table import jobs, integration keys and BYOB connectors. For task-oriented walkthroughs of these operations, see the Data import guide. Every mutation below is sent as a POST to https://app.arize.com/graphql with an x-api-key header; see Forming calls.

Mutations in this page

createFileImportJob: Create a job that will import model inferences from a blob store
updateFileImportJob: Update an existing job that has been imported from a blob store
startFileImportJob: Start an existing job that has been imported from a blob store
pauseFileImportJob: Pause an existing job that has been imported from a blob store
deleteFileImportJob: Delete an existing job that has been imported from a blob store
resetFileStatus: Reset the status of a file
createTableImportJob: Create a job that will import model inferences from a table
updateTableImportJob: Update an existing job that has been imported from a table
updateTableIngestionParameters: Update an existing job that has been imported from a table
startTableImportJob: Start an existing job that has been imported from a table
pauseTableImportJob: Pause an existing job that has been imported from a table
deleteTableImportJob: Delete an existing job that has been imported from a table
createTriggeredOngoingTableImportJob: Create a job that will import model inferences from a table
createTriggeredOngoingTableRun: Schedule a job run that will import model inferences from a table
createIntegrationKey: Create integration key.
patchIntegrationKey: Patch integration key.
testIntegrationKey: Test integration key.
deleteIntegrationKey: Delete integration key.
validateByobConnector: Validate a byob connector
createByobConnector: Create a byob connector
updateByobConnector: Update a byob connector
deleteByobConnector: Delete a byob connector
updateByobSyncedDatasource: Update a byob synced datasource
deleteByobDatasource: Delete a byob datasource

Reference

createFileImportJob

Create a job that will import model inferences from a blob store createFileImportJob(input: CreateFileImportJobInput!): CreateFileImportJobPayload

Arguments

CreateFileImportJobInput!

required

Show CreateFileImportJobInput fields

ID!

required

The space id for the space under which the model should be ingested

AzureStorageIdentifier

Additional information required to locate an Azure container. Required when running with an Azure service principal or managed identity.

Show AzureStorageIdentifier fields

String!

required

The Azure Active Directory Tenant ID associated with the Storage Account.

String!

required

The Azure Storage Account name.

String!

required

The model identifier or name under which the model will be stored.

ModelType!

required

The type of model. This determines how the model will be analyzed One of: numeric, score_categorical, ranking, object_detection, generative_llm, multi_class.

ModelEnvironmentName!

required

The environment for which the inferences are being ingested One of: production, validation, training, tracing.

String

A name for the ingestion batch. Only required if the environment is validation

String

The model version. This will tag all the inferences as being for a specific version string.

BlobStoreType!

required

The cloud storage solution where the files reside One of: S3, GCS, Azure.

String!

required

The bucket where the files are stored. Arize must have access to this bucket

String!

required

The path to the files. Ex. cc_model

FileImportSchemaInputType!

required

The schema for the CSV or Parquet files. The schema describes a mapping from your column names to model dimensions

Show FileImportSchemaInputType fields

String

The name of the predictionId column in the file

String

The name of the predictionGroupId column in the file. Required if the model is type ranking

String

A prefix capture group used to match feature columns

[String!]

A list of column names specifying features

String

The name of the timestamp column in the file

String

The name of the prediction label column in the file. Supported on model of type score_categorical

String

The name of the prediction score column in the file. Supported on models of type numeric and score_categorical

String

The name of the prediction scores column in the file. Supported on multi_class models

String

The name of the actual label column in the file. Supported on model of type score_categorical

String

The name of the actual score column in the file. Supported on models of type numeric and score_categorical

String

The name of the actual scores column in the file. Supported on multi_class models

String

The name of the threshold scores column in the file. Supported on multi_class models

String

The name of the relevance label column in the file. Required if the model is type ranking

String

The name of the relevance score column in the file. Required if the model is type ranking

String

The name of the model version column in the file

String

The name of the validation batch id. Required if the model is type validation

String

A prefix capture group used to match tag column

[String!]

A list of column names specifying tags

String

A regex like capture group that should be used to match shap column

String

The name of the rank column in the file. Required if the model is type ranking

[String!]

The names of fields to be excluded from data ingestion

[FileImportEmbeddingInputType!]

The embedding fields that will be ingested

Show FileImportEmbeddingInputType fields

String!

required

The embedding feature name

String!

required

The name of the vector column

String

The name of the raw data column

String

The name of the link to data column

FileImportPromptResponseInputType

The columns which contain the prompt used in a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptResponseInputType

The columns which contain the response from a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptTemplateInputType

The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative_llm

Show FileImportPromptTemplateInputType fields

String

The name of the column which contains the prompt template

String

The name of the column which contains the prompt template version

FileImportLlmConfigInputType

The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative_llm

Show FileImportLlmConfigInputType fields

String

The name of the column which contains the llm name

String

The name of the column which contains a map of llm params to values

FileImportRunMetadataInputType

The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative_llm

Show FileImportRunMetadataInputType fields

String

The name of the column which contains the total number of tokens used in the llm call

String

The name of the column which contains the number of prompt tokens in the llm call

String

The name of the column which contains the number of response tokens in the llm call

String

The name of the column which contains the response latency in ms of the llm call

FileImportObjectDetectionLabelInputType

The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

FileImportObjectDetectionLabelInputType

The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

String

The name of the file to perform a dry run on (ex. test-file.avro). If a file name is not selected, the dry run will be performed on the first file

Boolean

If true, the import job will be attempted but no changes will be written. The fileResult field may be requested to check the validation status. Default is false

String

Returns

Space

Show Space fields

Scalar fields: id, name, description, uuid, createdAt, liveEnabled, isLLMOnlySpace, playgroundTracingModelId, evalTracingModelId, sandboxTracingModelId, mlModelsEnabled, private, gradientStartColor, gradientEndColor, hasDashboardsCreated.Object fields (select subfields): organization, models, monitors, dashboards, spaceUsers, byobConnectors, importJobs, tableJobs, sandboxJobs, signalInsightSummary, signalEnabledProjectSummary, signalIssues, agentIssues, automations, datasets, experiments, customMetrics, onlineTasks, prompts, tags, evaluators, annotationQueues, playgroundViews, annotationConfigs, traceFilters, llmIntegrations, defaultLlmIntegration, defaultAgentRuntime, gates, _access.

JobValidationResult

Show JobValidationResult fields

Scalar fields: filePath, validationStatus.Object fields (select subfields): error.

FilePreviewResult

Show FilePreviewResult fields

Scalar fields: filePath.Object fields (select subfields): columnMetadata, rows, errorCode.

FileImportJob

Show FileImportJob fields

Scalar fields: id, jobId, bucketName, createdAt, modelName, modelId, jobUuid, modelType, modelVersion, modelEnvironmentName, batchId, blobStore, prefix, totalFilesSuccessCount, totalFilesFailedCount, totalFilesPendingCount, jobStatus.Object fields (select subfields): schema, files.

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation CreateFileImportJob($input: CreateFileImportJobInput!) {
  createFileImportJob(input: $input) {
    space { id name }
    validationResult { filePath }
    filePreview { filePath }
  }
}

{
  "input": {
    "spaceId": "<ID>",
    "modelName": "<string>",
    "modelType": "numeric",
    "modelEnvironmentName": "production",
    "blobStore": "S3",
    "bucketName": "<string>",
    "prefix": "<string>",
    "schema": {}
  }
}

updateFileImportJob

Update an existing job that has been imported from a blob store updateFileImportJob(input: UpdateFileImportJobInput!): UpdateFileImportJobPayload

Arguments

UpdateFileImportJobInput!

required

Show UpdateFileImportJobInput fields

ID!

required

The ID of an import job to delete

JobStatus

The status of the imported job One of: ONGOING_INACTIVE, ONGOING_DELETED.

FileImportSchemaInputType!

required

The schema for the CSV or Parquet files. The schema describes a mapping from your column names to model dimensions

Show FileImportSchemaInputType fields

String

The name of the predictionId column in the file

String

The name of the predictionGroupId column in the file. Required if the model is type ranking

String

A prefix capture group used to match feature columns

[String!]

A list of column names specifying features

String

The name of the timestamp column in the file

String

The name of the prediction label column in the file. Supported on model of type score_categorical

String

The name of the prediction score column in the file. Supported on models of type numeric and score_categorical

String

The name of the prediction scores column in the file. Supported on multi_class models

String

The name of the actual label column in the file. Supported on model of type score_categorical

String

The name of the actual score column in the file. Supported on models of type numeric and score_categorical

String

The name of the actual scores column in the file. Supported on multi_class models

String

The name of the threshold scores column in the file. Supported on multi_class models

String

The name of the relevance label column in the file. Required if the model is type ranking

String

The name of the relevance score column in the file. Required if the model is type ranking

String

The name of the model version column in the file

String

The name of the validation batch id. Required if the model is type validation

String

A prefix capture group used to match tag column

[String!]

A list of column names specifying tags

String

A regex like capture group that should be used to match shap column

String

The name of the rank column in the file. Required if the model is type ranking

[String!]

The names of fields to be excluded from data ingestion

[FileImportEmbeddingInputType!]

The embedding fields that will be ingested

Show FileImportEmbeddingInputType fields

String!

required

The embedding feature name

String!

required

The name of the vector column

String

The name of the raw data column

String

The name of the link to data column

FileImportPromptResponseInputType

The columns which contain the prompt used in a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptResponseInputType

The columns which contain the response from a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptTemplateInputType

The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative_llm

Show FileImportPromptTemplateInputType fields

String

The name of the column which contains the prompt template

String

The name of the column which contains the prompt template version

FileImportLlmConfigInputType

The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative_llm

Show FileImportLlmConfigInputType fields

String

The name of the column which contains the llm name

String

The name of the column which contains a map of llm params to values

FileImportRunMetadataInputType

The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative_llm

Show FileImportRunMetadataInputType fields

String

The name of the column which contains the total number of tokens used in the llm call

String

The name of the column which contains the number of prompt tokens in the llm call

String

The name of the column which contains the number of response tokens in the llm call

String

The name of the column which contains the response latency in ms of the llm call

FileImportObjectDetectionLabelInputType

The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

FileImportObjectDetectionLabelInputType

The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

String

Returns

FileImportJob!

The updated import job

Show FileImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation UpdateFileImportJob($input: UpdateFileImportJobInput!) {
  updateFileImportJob(input: $input) {
    fileImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>",
    "schema": {}
  }
}

startFileImportJob

Start an existing job that has been imported from a blob store startFileImportJob(input: StartFileImportJobInput!): StartFileImportJobPayload

Arguments

StartFileImportJobInput!

required

Show StartFileImportJobInput fields

ID!

required

The ID of an import job to start

String

Returns

FileImportJob!

The import job which has been started

Show FileImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation StartFileImportJob($input: StartFileImportJobInput!) {
  startFileImportJob(input: $input) {
    fileImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>"
  }
}

pauseFileImportJob

Pause an existing job that has been imported from a blob store pauseFileImportJob(input: PauseFileImportJobInput!): PauseFileImportJobPayload

Arguments

PauseFileImportJobInput!

required

Show PauseFileImportJobInput fields

ID!

required

The ID of an import job to pause

String

Returns

FileImportJob!

The paused import job

Show FileImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation PauseFileImportJob($input: PauseFileImportJobInput!) {
  pauseFileImportJob(input: $input) {
    fileImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>"
  }
}

deleteFileImportJob

Delete an existing job that has been imported from a blob store deleteFileImportJob(input: DeleteFileImportJobInput!): DeleteFileImportJobPayload

Arguments

DeleteFileImportJobInput!

required

Show DeleteFileImportJobInput fields

ID!

required

The ID of an import job to delete

String

Returns

FileImportJob!

The deleted import job

Show FileImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation DeleteFileImportJob($input: DeleteFileImportJobInput!) {
  deleteFileImportJob(input: $input) {
    fileImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>"
  }
}

resetFileStatus

Reset the status of a file resetFileStatus(input: ResetFileStatusInput!): ResetFileStatusPayload

Arguments

ResetFileStatusInput!

required

Show ResetFileStatusInput fields

ID!

required

The id of the job to reset the status of

ID!

required

The id of the file to reset the status of

String

Returns

FileImportJob!

The updated import job

Show FileImportJob fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation ResetFileStatus($input: ResetFileStatusInput!) {
  resetFileStatus(input: $input) {
    job { id }
  }
}

{
  "input": {
    "jobId": "<ID>",
    "fileId": "<ID>"
  }
}

createTableImportJob

Create a job that will import model inferences from a table createTableImportJob(input: CreateTableImportJobInput!): CreateTableImportJobPayload

Arguments

CreateTableImportJobInput!

required

Show CreateTableImportJobInput fields

ID!

required

The space id for the space under which the model should be ingested

String!

required

The model identifier or name under which the model will be stored.

ModelType!

required

The type of model. This determines how the model will be analyzed One of: numeric, score_categorical, ranking, object_detection, generative_llm, multi_class.

ModelEnvironmentName!

required

The environment for which the inferences are being ingested One of: production, validation, training, tracing.

String

A name for the ingestion batch. Only required if the environment is validation

String

The model version. This will tag all the inferences as being for a specific version string.

TableIntegrationType!

required

The table solution where the inferences reside One of: BigQuery, Snowflake, Databricks.

BigQueryTableConfig

Show BigQueryTableConfig fields

String!

required

The unique string used to differentiate a Google Cloud project

String!

required

The dataset where the tables are stored. Arize must have access to this dataset

String!

required

The path to the table

SnowflakeTableConfig

Show SnowflakeTableConfig fields

String!

required

The account identifier assigned to the Snowflake account.

String!

required

The schema which the target Table belongs to. Together, a database and schema comprise a namespace in Snowflake.

String!

required

The database which the schema of the target Table belongs to.

String!

required

The table which to import data from.

DatabricksTableConfig

Show DatabricksTableConfig fields

String!

required

The base URL of the workspace ex. databricks-hostname-example.databricks.com

String!

required

The URL fragment that corresponds to the resource, either a Compute Cluster or SQL Warehouse ex. /sql/1.0/warehouses/example

String!

required

The port of the resource ex. 443

String

Personal access token (for a service principal) ex. dapi12392103129093021. Required if ‘azureResourceId’ is needed & not provided.

String

The Azure Resource Manager ID for the Azure Databricks workspace. Required only if not doing token-based authentication.

String!

required

If using Unity Catalog, this is the catalog name. If not, this will be hive_metastore

String!

required

A logical collection of tables

String!

required

The name of the table or view

TableImportSchemaInputType!

required

The schema for the CSV or Parquet files. The schema describes a mapping from your column names to model dimensions

Show TableImportSchemaInputType fields

String!

required

The name of the predictionId column in the file

String

The name of the predictionGroupId column in the file. Required if the model is type ranking

String

A prefix capture group used to match feature columns

[String!]

A list of column names specifying features

String

The name of the timestamp column in the file

String

The name of the prediction label column in the file. Supported on model of type score_categorical

String

The name of the prediction score column in the file. Supported on models of type numeric and score_categorical

String

The name of the prediction scores column in the file. Supported on multi_class models

String

The name of the actual label column in the file. Supported on model of type score_categorical

String

The name of the actual score column in the file. Supported on models of type numeric and score_categorical

String

The name of the actual scores column in the file. Supported on multi_class models

String

The name of the threshold scores column in the file. Supported on multi_class models

String

The name of the relevance label column in the file. Required if the model is type ranking

String

The name of the relevance score column in the file. Required if the model is type ranking

String

The name of the model version column in the file

String

The name of the validation batch id. Required if the model is type validation

String

A prefix capture group used to match tag column

[String!]

A list of column names specifying tags

String

A regex like capture group that should be used to match shap column

String

The name of the rank column in the file. Required if the model is type ranking

[String!]

The names of fields to be excluded from data ingestion

[FileImportEmbeddingInputType!]

The embedding fields that will be ingested

Show FileImportEmbeddingInputType fields

String!

required

The embedding feature name

String!

required

The name of the vector column

String

The name of the raw data column

String

The name of the link to data column

FileImportPromptResponseInputType

The columns which contain the prompt used in a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptResponseInputType

The columns which contain the response from a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptTemplateInputType

The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative_llm

Show FileImportPromptTemplateInputType fields

String

The name of the column which contains the prompt template

String

The name of the column which contains the prompt template version

FileImportLlmConfigInputType

The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative_llm

Show FileImportLlmConfigInputType fields

String

The name of the column which contains the llm name

String

The name of the column which contains a map of llm params to values

FileImportRunMetadataInputType

The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative_llm

Show FileImportRunMetadataInputType fields

String

The name of the column which contains the total number of tokens used in the llm call

String

The name of the column which contains the number of prompt tokens in the llm call

String

The name of the column which contains the number of response tokens in the llm call

String

The name of the column which contains the response latency in ms of the llm call

FileImportObjectDetectionLabelInputType

The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

FileImportObjectDetectionLabelInputType

The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

String

The name of the change timestamp column in the file.

Boolean

If true, the import job will be attempted but no changes will be written. The fileResult field may be requested to check the validation status. Default is false

String

Returns

Space

Show Space fields

TableJobValidationResult

Show TableJobValidationResult fields

Scalar fields: jobId, tableQueryId, queryId, validationStatus.Object fields (select subfields): error.

TableImportJob

Show TableImportJob fields

Scalar fields: id, jobId, jobStatus, tableStore, projectId, dataset, createdAt, modelName, modelId, modelType, modelVersion, modelEnvironmentName, batchId, table, totalQueriesSuccessCount, totalQueriesFailedCount, totalQueriesPendingCount.Object fields (select subfields): schema, tableIngestionParameters, queries.

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation CreateTableImportJob($input: CreateTableImportJobInput!) {
  createTableImportJob(input: $input) {
    space { id name }
    validationResult { jobId }
    tableImportJob { id }
  }
}

{
  "input": {
    "spaceId": "<ID>",
    "modelName": "<string>",
    "modelType": "numeric",
    "modelEnvironmentName": "production",
    "tableStore": "BigQuery",
    "schema": {
      "predictionId": "<string>"
    }
  }
}

updateTableImportJob

Update an existing job that has been imported from a table updateTableImportJob(input: UpdateTableImportJobInput!): UpdateTableImportJobPayload

Arguments

UpdateTableImportJobInput!

required

Show UpdateTableImportJobInput fields

ID!

required

The ID of an import job to delete

JobStatus

The status of the imported job One of: ONGOING_INACTIVE, ONGOING_DELETED.

String

The model version set as a constant

TableImportSchemaInputType!

required

The schema describes a mapping from your column names to model dimensions

Show TableImportSchemaInputType fields

String!

required

The name of the predictionId column in the file

String

The name of the predictionGroupId column in the file. Required if the model is type ranking

String

A prefix capture group used to match feature columns

[String!]

A list of column names specifying features

String

The name of the timestamp column in the file

String

The name of the prediction label column in the file. Supported on model of type score_categorical

String

The name of the prediction score column in the file. Supported on models of type numeric and score_categorical

String

The name of the prediction scores column in the file. Supported on multi_class models

String

The name of the actual label column in the file. Supported on model of type score_categorical

String

The name of the actual score column in the file. Supported on models of type numeric and score_categorical

String

The name of the actual scores column in the file. Supported on multi_class models

String

The name of the threshold scores column in the file. Supported on multi_class models

String

The name of the relevance label column in the file. Required if the model is type ranking

String

The name of the relevance score column in the file. Required if the model is type ranking

String

The name of the model version column in the file

String

The name of the validation batch id. Required if the model is type validation

String

A prefix capture group used to match tag column

[String!]

A list of column names specifying tags

String

A regex like capture group that should be used to match shap column

String

The name of the rank column in the file. Required if the model is type ranking

[String!]

The names of fields to be excluded from data ingestion

[FileImportEmbeddingInputType!]

The embedding fields that will be ingested

Show FileImportEmbeddingInputType fields

String!

required

The embedding feature name

String!

required

The name of the vector column

String

The name of the raw data column

String

The name of the link to data column

FileImportPromptResponseInputType

The columns which contain the prompt used in a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptResponseInputType

The columns which contain the response from a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptTemplateInputType

The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative_llm

Show FileImportPromptTemplateInputType fields

String

The name of the column which contains the prompt template

String

The name of the column which contains the prompt template version

FileImportLlmConfigInputType

The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative_llm

Show FileImportLlmConfigInputType fields

String

The name of the column which contains the llm name

String

The name of the column which contains a map of llm params to values

FileImportRunMetadataInputType

The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative_llm

Show FileImportRunMetadataInputType fields

String

The name of the column which contains the total number of tokens used in the llm call

String

The name of the column which contains the number of prompt tokens in the llm call

String

The name of the column which contains the number of response tokens in the llm call

String

The name of the column which contains the response latency in ms of the llm call

FileImportObjectDetectionLabelInputType

The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

FileImportObjectDetectionLabelInputType

The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

String

The name of the change timestamp column in the file.

TableIngestionParametersInputType!

required

Table ingestion parameters

Show TableIngestionParametersInputType fields

Int

How often a user wants to query data in minutes

Int

How large of a query window to use in hours

String

Returns

TableImportJob!

The updated table import job

Show TableImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation UpdateTableImportJob($input: UpdateTableImportJobInput!) {
  updateTableImportJob(input: $input) {
    tableImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>",
    "schema": {
      "predictionId": "<string>"
    },
    "tableIngestionParameters": {}
  }
}

updateTableIngestionParameters

Update an existing job that has been imported from a table updateTableIngestionParameters(input: UpdateTableIngestionParametersInput!): UpdateTableIngestionParametersPayload

Arguments

UpdateTableIngestionParametersInput!

required

Show UpdateTableIngestionParametersInput fields

ID!

required

The import job id

TableIngestionParametersInputType!

required

Table ingestion parameters

Show TableIngestionParametersInputType fields

Int

How often a user wants to query data in minutes

Int

How large of a query window to use in hours

String

Returns

TableImportJob!

The updated table import job

Show TableImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation UpdateTableIngestionParameters($input: UpdateTableIngestionParametersInput!) {
  updateTableIngestionParameters(input: $input) {
    tableImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>",
    "tableIngestionParameters": {}
  }
}

startTableImportJob

Start an existing job that has been imported from a table startTableImportJob(input: StartTableImportJobInput!): StartTableImportJobPayload

Arguments

StartTableImportJobInput!

required

Show StartTableImportJobInput fields

ID!

required

The ID of an import job to start

String

Returns

FileImportJob!

The import job which has been started

Show FileImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation StartTableImportJob($input: StartTableImportJobInput!) {
  startTableImportJob(input: $input) {
    tableImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>"
  }
}

pauseTableImportJob

Pause an existing job that has been imported from a table pauseTableImportJob(input: PauseTableImportJobInput!): PauseTableImportJobPayload

Arguments

PauseTableImportJobInput!

required

Show PauseTableImportJobInput fields

ID!

required

The ID of an import job to pause

String

Returns

TableImportJob!

The paused import job

Show TableImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation PauseTableImportJob($input: PauseTableImportJobInput!) {
  pauseTableImportJob(input: $input) {
    tableImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>"
  }
}

deleteTableImportJob

Delete an existing job that has been imported from a table deleteTableImportJob(input: DeleteTableImportJobInput!): DeleteTableImportJobPayload

Arguments

DeleteTableImportJobInput!

required

Show DeleteTableImportJobInput fields

ID!

required

The ID of a table import job to delete

String

Returns

TableImportJob!

The deleted table import job

Show TableImportJob fields

Space!

Show Space fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation DeleteTableImportJob($input: DeleteTableImportJobInput!) {
  deleteTableImportJob(input: $input) {
    tableImportJob { id }
    space { id name }
  }
}

{
  "input": {
    "jobId": "<ID>"
  }
}

createTriggeredOngoingTableImportJob

Create a job that will import model inferences from a table

createTriggeredOngoingTableImportJob(input: CreateTriggeredOngoingTableImportJobInput!): CreateTriggeredOngoingTableImportJobPayload

Arguments

CreateTriggeredOngoingTableImportJobInput!

required

Show CreateTriggeredOngoingTableImportJobInput fields

ID!

required

The space id for the space under which the model should be ingested

String!

required

The model identifier or name under which the model will be stored.

ModelType!

required

The type of model. This determines how the model will be analyzed One of: numeric, score_categorical, ranking, object_detection, generative_llm, multi_class.

ModelEnvironmentName!

required

The environment for which the inferences are being ingested One of: production, validation, training, tracing.

String

A name for the ingestion batch. Only required if the environment is validation

String

The model version. This will tag all the inferences as being for a specific version string.

TableIntegrationType!

required

The table solution where the inferences reside One of: BigQuery, Snowflake, Databricks.

BigQueryTableConfig

Show BigQueryTableConfig fields

String!

required

The unique string used to differentiate a Google Cloud project

String!

required

The dataset where the tables are stored. Arize must have access to this dataset

String!

required

The path to the table

SnowflakeTableConfig

Show SnowflakeTableConfig fields

String!

required

The account identifier assigned to the Snowflake account.

String!

required

The schema which the target Table belongs to. Together, a database and schema comprise a namespace in Snowflake.

String!

required

The database which the schema of the target Table belongs to.

String!

required

The table which to import data from.

DatabricksTableConfig

Show DatabricksTableConfig fields

String!

required

The base URL of the workspace ex. databricks-hostname-example.databricks.com

String!

required

The URL fragment that corresponds to the resource, either a Compute Cluster or SQL Warehouse ex. /sql/1.0/warehouses/example

String!

required

The port of the resource ex. 443

String

Personal access token (for a service principal) ex. dapi12392103129093021. Required if ‘azureResourceId’ is needed & not provided.

String

The Azure Resource Manager ID for the Azure Databricks workspace. Required only if not doing token-based authentication.

String!

required

If using Unity Catalog, this is the catalog name. If not, this will be hive_metastore

String!

required

A logical collection of tables

String!

required

The name of the table or view

TableImportSchemaInputType!

required

The schema for the CSV or Parquet files. The schema describes a mapping from your column names to model dimensions

Show TableImportSchemaInputType fields

String!

required

The name of the predictionId column in the file

String

The name of the predictionGroupId column in the file. Required if the model is type ranking

String

A prefix capture group used to match feature columns

[String!]

A list of column names specifying features

String

The name of the timestamp column in the file

String

The name of the prediction label column in the file. Supported on model of type score_categorical

String

The name of the prediction score column in the file. Supported on models of type numeric and score_categorical

String

The name of the prediction scores column in the file. Supported on multi_class models

String

The name of the actual label column in the file. Supported on model of type score_categorical

String

The name of the actual score column in the file. Supported on models of type numeric and score_categorical

String

The name of the actual scores column in the file. Supported on multi_class models

String

The name of the threshold scores column in the file. Supported on multi_class models

String

The name of the relevance label column in the file. Required if the model is type ranking

String

The name of the relevance score column in the file. Required if the model is type ranking

String

The name of the model version column in the file

String

The name of the validation batch id. Required if the model is type validation

String

A prefix capture group used to match tag column

[String!]

A list of column names specifying tags

String

A regex like capture group that should be used to match shap column

String

The name of the rank column in the file. Required if the model is type ranking

[String!]

The names of fields to be excluded from data ingestion

[FileImportEmbeddingInputType!]

The embedding fields that will be ingested

Show FileImportEmbeddingInputType fields

String!

required

The embedding feature name

String!

required

The name of the vector column

String

The name of the raw data column

String

The name of the link to data column

FileImportPromptResponseInputType

The columns which contain the prompt used in a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptResponseInputType

The columns which contain the response from a generative LLM. Relevant if the model is generative_llm

Show FileImportPromptResponseInputType fields

String

The name of the vector column

String!

required

The name of the raw data column. Required if the prompt or response is specified

FileImportPromptTemplateInputType

The columns which contain the prompt template fields, such as the template and template version. Relevant if the model is generative_llm

Show FileImportPromptTemplateInputType fields

String

The name of the column which contains the prompt template

String

The name of the column which contains the prompt template version

FileImportLlmConfigInputType

The columns which contain the llm config fields, such as the llm name and params. Relevant if the model is generative_llm

Show FileImportLlmConfigInputType fields

String

The name of the column which contains the llm name

String

The name of the column which contains a map of llm params to values

FileImportRunMetadataInputType

The columns which contain the metadata relevant to the llm call that was used to generate the response using the prompt. Relevant if the model is generative_llm

Show FileImportRunMetadataInputType fields

String

The name of the column which contains the total number of tokens used in the llm call

String

The name of the column which contains the number of prompt tokens in the llm call

String

The name of the column which contains the number of response tokens in the llm call

String

The name of the column which contains the response latency in ms of the llm call

FileImportObjectDetectionLabelInputType

The columns which contain the object detection prediction fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

FileImportObjectDetectionLabelInputType

The columns which contain the object detection actual fields, such as the bounding box coordinates, categories, and scores. Relevant if the model is object_detection

Show FileImportObjectDetectionLabelInputType fields

String!

required

The name of the column which contains the bounding box coordinates

String!

required

The name of the column which contains a map of bounding box categories

String

The name of the column which contains a map of bounding box scores

String

The name of the change timestamp column in the file.

String

Returns

Space

Show Space fields

TableJobValidationResult

Show TableJobValidationResult fields

Scalar fields: jobId, tableQueryId, queryId, validationStatus.Object fields (select subfields): error.

TableImportJob

Show TableImportJob fields

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation CreateTriggeredOngoingTableImportJob($input: CreateTriggeredOngoingTableImportJobInput!) {
  createTriggeredOngoingTableImportJob(input: $input) {
    space { id name }
    validationResult { jobId }
    tableImportJob { id }
  }
}

{
  "input": {
    "spaceId": "<ID>",
    "modelName": "<string>",
    "modelType": "numeric",
    "modelEnvironmentName": "production",
    "tableStore": "BigQuery",
    "schema": {
      "predictionId": "<string>"
    }
  }
}

createTriggeredOngoingTableRun

Schedule a job run that will import model inferences from a table createTriggeredOngoingTableRun(input: CreateTriggeredOngoingTableRunInput!): CreateTriggeredOngoingTableRunPayload

Arguments

CreateTriggeredOngoingTableRunInput!

required

Show CreateTriggeredOngoingTableRunInput fields

ID!

required

The job id to schedule a table ingestion run for

DateTime!

required

The start time for the query

DateTime!

required

The end time for the query

String

Returns

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation CreateTriggeredOngoingTableRun($input: CreateTriggeredOngoingTableRunInput!) {
  createTriggeredOngoingTableRun(input: $input) {
    clientMutationId
  }
}

{
  "input": {
    "jobId": "<ID>",
    "queryStart": "2026-01-01T00:00:00Z",
    "queryEnd": "2026-01-01T00:00:00Z"
  }
}

createIntegrationKey

createIntegrationKey(input: CreateIntegrationKeyInput!): CreateIntegrationKeyPayload

Arguments

CreateIntegrationKeyInput!

required

Show CreateIntegrationKeyInput fields

ID!

required

The global relay id of the organization to create the integration key in.

IntegrationProvider!

required

The name of an integration provider e.g. opsgeneie, pagerduty, slack One of: opsgenie, pagerduty, slack.

String!

required

The name of the integration, used to denote a target service or team e.x. ML Team Opsgenie.

String!

required

The integration’s api key

IntegrationAlertSeverity

The priority/severity level when sending alerts to the given integration provider. One of: opsgenieP1, opsgenieP2, opsgenieP3, opsgenieP4, opsgenieP5, pagerdutycritical, pagerdutyerror, pagerdutywarning, pagerdutyinfo.

String

Returns

IntegrationKey!

The created integration key.

Show IntegrationKey fields

Scalar fields: id, name, providerName, createdAt, alertSeverity, channelName.Object fields (select subfields): creator.

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation CreateIntegrationKey($input: CreateIntegrationKeyInput!) {
  createIntegrationKey(input: $input) {
    integrationKey { id name }
  }
}

{
  "input": {
    "accountOrganizationId": "<ID>",
    "providerName": "opsgenie",
    "serviceName": "<string>",
    "apiKey": "<string>"
  }
}

patchIntegrationKey

patchIntegrationKey(input: PatchIntegrationKeyInput!): PatchIntegrationKeyPayload

Arguments

PatchIntegrationKeyInput!

required

Show PatchIntegrationKeyInput fields

ID!

required

The ID of the integration to patch

IntegrationKeyPatchInput!

required

Patch of the integration

Show IntegrationKeyPatchInput fields

String

The name of the integration, used to denote a target service or team e.x. ML Team Opsgenie.

String

The integration’s api key

IntegrationAlertSeverity

String

Returns

IntegrationKey!

The updated integration.

Show IntegrationKey fields

Scalar fields: id, name, providerName, createdAt, alertSeverity, channelName.Object fields (select subfields): creator.

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation PatchIntegrationKey($input: PatchIntegrationKeyInput!) {
  patchIntegrationKey(input: $input) {
    integrationKey { id name }
  }
}

{
  "input": {
    "integrationKeyId": "<ID>",
    "set": {}
  }
}

testIntegrationKey

testIntegrationKey(input: TestIntegrationKeyInput!): TestIntegrationKeyPayload

Arguments

TestIntegrationKeyInput!

required

Show TestIntegrationKeyInput fields

ID!

required

The global relay id for the integration key to update

String

Returns

Int!

The http status code of the test integration endpoint response e.g. 201, 401, etc

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation TestIntegrationKey($input: TestIntegrationKeyInput!) {
  testIntegrationKey(input: $input) {
    statusCode
  }
}

{
  "input": {
    "integrationKeyId": "<ID>"
  }
}

deleteIntegrationKey

deleteIntegrationKey(input: DeleteIntegrationKeyInput!): DeleteIntegrationKeyPayload

Arguments

DeleteIntegrationKeyInput!

required

Show DeleteIntegrationKeyInput fields

ID!

required

The global relay id for the integration key to delete

String

Returns

IntegrationKey!

The soft deleted integration key.

Show IntegrationKey fields

Scalar fields: id, name, providerName, createdAt, alertSeverity, channelName.Object fields (select subfields): creator.

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation DeleteIntegrationKey($input: DeleteIntegrationKeyInput!) {
  deleteIntegrationKey(input: $input) {
    integrationKey { id name }
  }
}

{
  "input": {
    "integrationKeyId": "<ID>"
  }
}

validateByobConnector

Validate a byob connector validateByobConnector(input: ValidateByobConnectorInput!): ValidateByobConnectorPayload

Arguments

ValidateByobConnectorInput!

required

Show ValidateByobConnectorInput fields

ID!

required

The id of the space that the byob connector belongs to

ByobConnectorIdentifier!

required

The object that identifies the byob connector

Show ByobConnectorIdentifier fields

ID!

required

The id of the space that the byob connector belongs to

CloudStorageProvider!

required

The cloud storage provider that the byob connector belongs to One of: GCS, S3, AZURE.

String!

required

The full path of the bucket that the byob connector belongs to

String

The Azure tenant ID for Azure Blob Storage connectors

String

Returns

Boolean!

Whether the byob connector is valid

ValidationReason

The reason why the byob connector is valid One of: UNKNOWN_INVALID_REASON, FAILED_BUCKET_OWNERSHIP_CHECK, FAILED_BUCKET_ACCESS.

String

The message that explains why the byob connector is valid

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation ValidateByobConnector($input: ValidateByobConnectorInput!) {
  validateByobConnector(input: $input) {
    isValid
    validationReason
    validationMessage
  }
}

{
  "input": {
    "spaceId": "<ID>",
    "connectorIdentifier": {
      "spaceId": "<ID>",
      "cloudStorageProvider": "GCS",
      "bucketAndPath": "<string>"
    }
  }
}

createByobConnector

Create a byob connector createByobConnector(input: CreateByobConnectorInput!): CreateByobConnectorPayload

Arguments

CreateByobConnectorInput!

required

Show CreateByobConnectorInput fields

ID!

required

The id of the space that the byob connector belongs to

ByobConnectorIdentifier!

required

The identifier of the byob connector

Show ByobConnectorIdentifier fields

ID!

required

The id of the space that the byob connector belongs to

CloudStorageProvider!

required

The cloud storage provider that the byob connector belongs to One of: GCS, S3, AZURE.

String!

required

The full path of the bucket that the byob connector belongs to

String!

required

The name of the byob connector

[String]!

required

The external model ids of the byob connector

ByobTableFormat

The table format for the connector (defaults to ICEBERG) One of: ICEBERG, DELTA.

String

The Azure tenant ID for Azure Blob Storage connectors

String

Returns

ID!

The id of the created byob connector

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation CreateByobConnector($input: CreateByobConnectorInput!) {
  createByobConnector(input: $input) {
    id
  }
}

{
  "input": {
    "spaceId": "<ID>",
    "connectorIdentifier": {
      "spaceId": "<ID>",
      "cloudStorageProvider": "GCS",
      "bucketAndPath": "<string>"
    },
    "name": "<string>",
    "externalModelIds": [
      "<string>"
    ]
  }
}

updateByobConnector

Update a byob connector updateByobConnector(input: UpdateByobConnectorInput!): UpdateByobConnectorPayload

Arguments

UpdateByobConnectorInput!

required

Show UpdateByobConnectorInput fields

ID!

required

The id of the byob connector

ID!

required

The id of the space that the byob connector belongs to

String!

required

The name of the byob connector

[String]!

required

The external model ids of the byob connector

String

Returns

Boolean

Whether the update was successful

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation UpdateByobConnector($input: UpdateByobConnectorInput!) {
  updateByobConnector(input: $input) {
    success
  }
}

{
  "input": {
    "id": "<ID>",
    "spaceId": "<ID>",
    "name": "<string>",
    "externalModelIds": [
      "<string>"
    ]
  }
}

deleteByobConnector

Delete a byob connector deleteByobConnector(input: DeleteByobConnectorInput!): DeleteByobConnectorPayload

Arguments

DeleteByobConnectorInput!

required

Show DeleteByobConnectorInput fields

ID!

required

The id of the byob connector

ID!

required

The id of the space that the byob connector belongs to

String

Returns

Boolean

Whether the delete was successful

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation DeleteByobConnector($input: DeleteByobConnectorInput!) {
  deleteByobConnector(input: $input) {
    success
  }
}

{
  "input": {
    "id": "<ID>",
    "spaceId": "<ID>"
  }
}

updateByobSyncedDatasource

Update a byob synced datasource updateByobSyncedDatasource(input: UpdateByobSyncedDatasourceInput!): UpdateByobSyncedDatasourcePayload

Arguments

UpdateByobSyncedDatasourceInput!

required

Show UpdateByobSyncedDatasourceInput fields

ID!

required

The id of the byob synced datasource

ID!

required

The id of the space

ActiveStatus

The active status of the byob synced datasource One of: active, paused.

Int

The sync frequency minutes of the byob synced datasource

String

Returns

Boolean

Whether the update was successful

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation UpdateByobSyncedDatasource($input: UpdateByobSyncedDatasourceInput!) {
  updateByobSyncedDatasource(input: $input) {
    success
  }
}

{
  "input": {
    "id": "<ID>",
    "spaceId": "<ID>"
  }
}

deleteByobDatasource

Delete a byob datasource deleteByobDatasource(input: DeleteByobDatasourceInput!): DeleteByobDatasourcePayload

Arguments

DeleteByobDatasourceInput!

required

Show DeleteByobDatasourceInput fields

ID!

required

The id of the byob datasource

ID!

required

The id of the space that the byob datasource belongs to

String

Returns

Boolean

Whether the delete was successful

Example

Only required input fields are shown. Replace <ID> and <string> placeholders with real values; the object graph page shows how to look IDs up.

mutation DeleteByobDatasource($input: DeleteByobDatasourceInput!) {
  deleteByobDatasource(input: $input) {
    success
  }
}

{
  "input": {
    "id": "<ID>",
    "spaceId": "<ID>"
  }
}

​Mutations in this page

​Reference

​createFileImportJob

​Arguments

​Returns

​Example

​updateFileImportJob

​Arguments

​Returns

​Example

​startFileImportJob

​Arguments

​Returns

​Example

​pauseFileImportJob

​Arguments

​Returns

​Example

​deleteFileImportJob

​Arguments

​Returns

​Example

​resetFileStatus

​Arguments

​Returns

​Example

​createTableImportJob

​Arguments

​Returns

​Example

​updateTableImportJob

​Arguments

​Returns

​Example

​updateTableIngestionParameters

​Arguments

​Returns

​Example

​startTableImportJob

​Arguments

​Returns

​Example

​pauseTableImportJob

​Arguments

​Returns

​Example

​deleteTableImportJob

​Arguments

​Returns

​Example

​createTriggeredOngoingTableImportJob

​Arguments

​Returns

​Example

​createTriggeredOngoingTableRun

​Arguments

​Returns

​Example

​createIntegrationKey

​Arguments

​Returns

​Example

​patchIntegrationKey

​Arguments

​Returns

​Example

​testIntegrationKey

​Arguments

​Returns

​Example

​deleteIntegrationKey

​Arguments

​Returns

​Example

​validateByobConnector

​Arguments

​Returns

​Example

​createByobConnector

​Arguments

Mutations in this page

Reference

createFileImportJob

Arguments

Returns

Example

updateFileImportJob

Arguments

Returns

Example

startFileImportJob

Arguments

Returns

Example

pauseFileImportJob

Arguments

Returns

Example

deleteFileImportJob

Arguments

Returns

Example

resetFileStatus

Arguments

Returns

Example

createTableImportJob

Arguments

Returns

Example

updateTableImportJob

Arguments

Returns

Example

updateTableIngestionParameters

Arguments

Returns

Example

startTableImportJob

Arguments

Returns

Example

pauseTableImportJob

Arguments

Returns

Example

deleteTableImportJob

Arguments

Returns

Example

createTriggeredOngoingTableImportJob

Arguments

Returns

Example

createTriggeredOngoingTableRun

Arguments

Returns

Example

createIntegrationKey

Arguments

Returns

Example

patchIntegrationKey

Arguments

Returns

Example

testIntegrationKey

Arguments

Returns

Example

deleteIntegrationKey

Arguments

Returns

Example

validateByobConnector

Arguments

Returns

Example

createByobConnector

Arguments