Feast
Important Capabilities
Capability | Status | Notes |
---|---|---|
Table-Level Lineage | ✅ | Enabled by default |
This plugin extracts:
- Entities as
MLPrimaryKey
- Fields as
MLFeature
- Feature views and on-demand feature views as
MLFeatureTable
- Batch and stream source details as
Dataset
- Column types associated with each entity and feature
CLI based Ingestion
Install the Plugin
pip install 'acryl-datahub[feast]'
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: feast
config:
# Coordinates
path: "/path/to/repository/"
# Options
environment: "PROD"
sink:
# sink configs
Config Details
- Options
- Schema
Note that a .
is used to denote nested fields in the YAML recipe.
Field | Description |
---|---|
path ✅ string | Path to Feast repository |
environment string | Environment to use when constructing URNs Default: PROD |
fs_yaml_file string | Path to the feature_store.yaml file used to configure the feature store |
The JSONSchema for this configuration is inlined below.
{
"title": "FeastRepositorySourceConfig",
"type": "object",
"properties": {
"path": {
"title": "Path",
"description": "Path to Feast repository",
"type": "string"
},
"fs_yaml_file": {
"title": "Fs Yaml File",
"description": "Path to the `feature_store.yaml` file used to configure the feature store",
"type": "string"
},
"environment": {
"title": "Environment",
"description": "Environment to use when constructing URNs",
"default": "PROD",
"type": "string"
}
},
"required": [
"path"
],
"additionalProperties": false
}
Code Coordinates
- Class Name:
datahub.ingestion.source.feast.FeastRepositorySource
- Browse on GitHub
Questions
If you've got any questions on configuring ingestion for Feast, feel free to ping us on our Slack.