Model monitoring data input spec.
dataset
Union type
dataset
can be only one of the following:Columnized dataset.
Vertex AI Batch prediction Job.
Vertex AI Endpoint request & response logging.
time_spec
Union type
time_spec
can be only one of the following:The time interval (pair of startTime and endTime) for which results should be returned.
The time offset setting for which results should be returned.
JSON representation |
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{ // dataset "columnizedDataset": { object ( |
ModelMonitoringDataset
Input dataset spec.
timestampField
string
The timestamp field. Usually for serving data.
data_location
Union type
data_location
can be only one of the following:vertexDataset
string
Resource name of the Vertex AI managed dataset.
Google Cloud Storage data source.
BigQuery data source.
JSON representation |
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{ "timestampField": string, // data_location "vertexDataset": string, "gcsSource": { object ( |
ModelMonitoringGcsSource
Dataset spec for data stored in Google Cloud Storage.
gcsUri
string
Google Cloud Storage URI to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.
data format of the dataset.
JSON representation |
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{
"gcsUri": string,
"format": enum ( |
DataFormat
Supported data format.
Enums | |
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DATA_FORMAT_UNSPECIFIED |
data format unspecified, used when this field is unset. |
CSV |
CSV files. |
TF_RECORD |
TfRecord files |
JSONL |
JsonL files. |
ModelMonitoringBigQuerySource
Dataset spec for data sotred in BigQuery.
connection
Union type
connection
can be only one of the following:tableUri
string
BigQuery URI to a table, up to 2000 characters long. All the columns in the table will be selected. Accepted forms:
- BigQuery path. For example:
bq://projectId.bqDatasetId.bqTableId
.
query
string
Standard SQL to be used instead of the tableUri
.
JSON representation |
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{ // connection "tableUri": string, "query": string // Union type } |
BatchPredictionOutput
data from Vertex AI Batch prediction job output.
batchPredictionJob
string
Vertex AI Batch prediction job resource name. The job must match the model version specified in [ModelMonitor].[modelMonitoringTarget].
JSON representation |
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{ "batchPredictionJob": string } |
VertexEndpointLogs
data from Vertex AI Endpoint request response logging.
endpoints[]
string
List of endpoint resource names. The endpoints must enable the logging with the [Endpoint].[requestResponseLoggingConfig], and must contain the deployed model corresponding to the model version specified in [ModelMonitor].[modelMonitoringTarget].
JSON representation |
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{ "endpoints": [ string ] } |
TimeOffset
time offset setting.
offset
string
[offset] is the time difference from the cut-off time. For scheduled jobs, the cut-off time is the scheduled time. For non-scheduled jobs, it's the time when the job was created. Currently we support the following format: 'w|W': Week, 'd|D': Day, 'h|H': Hour E.g. '1h' stands for 1 hour, '2d' stands for 2 days.
window
string
[window] refers to the scope of data selected for analysis. It allows you to specify the quantity of data you wish to examine. Currently we support the following format: 'w|W': Week, 'd|D': Day, 'h|H': Hour E.g. '1h' stands for 1 hour, '2d' stands for 2 days.
JSON representation |
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{ "offset": string, "window": string } |