steampipe plugin install awssteampipe plugin install aws
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Table: aws_sagemaker_training_job

A training job helps to train a model in Amazon SageMaker.

Examples

Basic info

select
name,
arn,
training_job_status,
creation_time,
last_modified_time
from
aws_sagemaker_training_job;

Get details of associated ML compute instances and storage volumes for each training job

select
name,
arn,
resource_config ->> 'InstanceType' as instance_type,
resource_config ->> 'InstanceCount' as instance_count,
resource_config ->> 'VolumeKmsKeyId' as volume_kms_id,
resource_config ->> 'VolumeSizeInGB' as volume_size
from
aws_sagemaker_training_job;

List failed training jobs

select
name,
arn,
training_job_status,
failure_reason
from
aws_sagemaker_training_job
where
training_job_status = 'Failed';

.inspect aws_sagemaker_training_job

AWS SageMaker Training Job

NameTypeDescription
account_idtextThe AWS Account ID in which the resource is located.
akasjsonbArray of globally unique identifier strings (also known as) for the resource.
algorithm_specificationjsonbInformation about the algorithm used for training, and algorithm metadata.
arntextThe Amazon Resource Name (ARN) of the training job.
auto_ml_job_arntextThe Amazon Resource Name (ARN) of an AutoML job.
billable_time_in_secondsbigintThe billable time in seconds. Billable time refers to the absolute wall-clock time.
checkpoint_configjsonbContains information about the output location for managed spot training checkpoint data.
creation_timetimestamp without time zoneA timestamp that shows when the training job was created.
debug_hook_configjsonbConfiguration information for the Debugger hook parameters, metric and tensor collections, and storage paths.
debug_rule_configurationsjsonbConfiguration information for Debugger rules for debugging output tensors.
debug_rule_evaluation_statusesjsonbEvaluation status of Debugger rules for debugging on a training job.
enable_inter_container_traffic_encryptionbooleanTo encrypt all communications between ML compute instances in distributed training, choose True.
enable_managed_spot_trainingbooleanA Boolean indicating whether managed spot training is enabled or not.
enable_network_isolationbooleanSpecifies enable network isolation for training jobs.
environmentjsonbThe environment variables to set in the Docker container.
experiment_configjsonbAssociates a SageMaker job as a trial component with an experiment and trial.
failure_reasontextIf the training job failed, the reason it failed.
final_metric_data_listjsonbA collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
hyper_parametersjsonbAlgorithm-specific parameters.
input_data_configjsonbAn array of Channel objects that describes each data input channel.
labeling_job_arntextThe Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
last_modified_timetimestamp without time zoneTimestamp when the training job was last modified.
model_artifactsjsonbInformation about the Amazon S3 location that is configured for storing model artifacts.
nametextThe name of the training job.
output_data_configjsonbThe S3 path where model artifacts that you configured when creating the job are stored.
partitiontextThe AWS partition in which the resource is located (aws, aws-cn, or aws-us-gov).
profiler_configjsonbConfiguration information for Debugger system monitoring,framework profiling and storage paths.
profiler_rule_configurationsjsonbConfiguration information for Debugger rules for profiling system and framework metrics.
profiler_rule_evaluation_statusesjsonbEvaluation status of Debugger rules for profiling on a training job.
profiling_statustextProfiling status of a training job.
regiontextThe AWS Region in which the resource is located.
resource_configjsonbResources, including ML compute instances and ML storage volumes, that are configured for model training.
role_arntextThe AWS Identity and Access Management (IAM) role configured for the training job.
secondary_statustextProvides detailed information about the state of the training job.
secondary_status_transitionsjsonbA history of all of the secondary statuses that the training job has transitioned through.
stopping_conditionjsonbSpecifies a limit to how long a model training job can run.
tagsjsonbA map of tags for the resource.
tags_srcjsonbA list of tags assigned to the training job.
tensor_board_output_configjsonbConfiguration of storage locations for the Debugger TensorBoard output data.
titletextTitle of the resource.
training_end_timetimestamp without time zoneA timestamp that shows when the training job ended.
training_job_statustextThe status of the training job.
training_start_timetimestamp without time zoneIndicates the time when the training job starts on training instances.
training_time_in_secondsbigintThe training time in seconds.
tuning_job_arntextThe Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
vpc_configjsonbA VpcConfig object that specifies the VPC that this training job has access to.