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SageMaker

Module sagemaker

Certified

Important Capabilities

CapabilityStatusNotes
Table-Level LineageEnabled by default

This plugin extracts the following:

  • Feature groups
  • Models, jobs, and lineage between the two (e.g. when jobs output a model or a model is used by a job)

CLI based Ingestion

Install the Plugin

pip install 'acryl-datahub[sagemaker]'

Starter Recipe

Check out the following recipe to get started with ingestion! See below for full configuration options.

For general pointers on writing and running a recipe, see our main recipe guide.

source:
type: sagemaker
config:
# Coordinates
aws_region: "my-aws-region"

sink:
# sink configs

Config Details

Note that a . is used to denote nested fields in the YAML recipe.

View All Configuration Options
Field [Required]TypeDescriptionDefaultNotes
aws_region [✅]stringAWS region code.None
aws_access_key_idstringAWS access key ID. Can be auto-detected, see https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html for details.None
aws_endpoint_urlstringAutodetected. See https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.htmlNone
aws_profilestringNamed AWS profile to use. Only used if access key / secret are unset. If not set the default will be usedNone
aws_proxymap(str,string)None
aws_secret_access_keystringAWS secret access key. Can be auto-detected, see https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html for details.None
aws_session_tokenstringAWS session token. Can be auto-detected, see https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html for details.None
extract_feature_groupsbooleanWhether to extract feature groups.True
extract_jobsUnionType (See notes for variants)Whether to extract AutoML jobs.TrueOne of string,boolean
extract_modelsbooleanWhether to extract models.True
envstringThe environment that all assets produced by this connector belong toPROD
aws_roleUnionType (See notes for variants)AWS roles to assume. If using the string format, the role ARN can be specified directly. If using the object format, the role can be specified in the RoleArn field and additional available arguments are documented at https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sts.html?highlight=assume_role#STS.Client.assume_roleNoneOne of string,union(anyOf),string,AwsAssumeRoleConfig
aws_role.RoleArn [❓ (required if aws_role is set)]stringARN of the role to assume.None
aws_role.ExternalIdstringExternal ID to use when assuming the role.None
database_patternAllowDenyPatternregex patterns for databases to filter in ingestion.{'allow': ['.*'], 'deny': [], 'ignoreCase': True}
database_pattern.allowarray(string)None
database_pattern.denyarray(string)None
database_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True
table_patternAllowDenyPatternregex patterns for tables to filter in ingestion.{'allow': ['.*'], 'deny': [], 'ignoreCase': True}
table_pattern.allowarray(string)None
table_pattern.denyarray(string)None
table_pattern.ignoreCasebooleanWhether to ignore case sensitivity during pattern matching.True

Code Coordinates

  • Class Name: datahub.ingestion.source.aws.sagemaker.SagemakerSource
  • Browse on GitHub

Questions

If you've got any questions on configuring ingestion for SageMaker, feel free to ping us on our Slack