Skip to main content

Mlflow plugin to use ElasticSearch as backend for MLflow tracking service

Project description

mlflow-elasticsearchstore

Mlflow plugin to use ElasticSearch as backend for MLflow tracking service. To use this plugin you need a running instance of Elasticsearch 6.X.

Run 'pip install mlflow-elasticsearchstore' to register the plugin as an entrypoint with Elasticsearch backend.

$ pip install mlflow-elasticsearchstore

Development

In a python environment (you can use the one where mlflow is already installed):

$ git clone git clone https://github.com/criteo/mlflow-elasticsearchstore.git
$ cd mlflow-elasticsearch
$ pip install .

How To

mlflow-elasticsearchstore can now be used with the "elasticsearch" scheme, in the same python environment :

$ mlflow server --host $MLFLOW_HOST --backend-store-uri elasticsearch://$USER:$PASSWORD@$ELASTICSEARCH_HOST:$ELASTICSEARCH_PORT --port $MLFLOW_PORT --default-artifact-root $ARTIFACT_LOCATION

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for mlflow-elasticsearchstore, version 0.1.2
Filename, size File type Python version Upload date Hashes
Filename, size mlflow_elasticsearchstore-0.1.2-py3-none-any.whl (13.3 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size mlflow-elasticsearchstore-0.1.2.tar.gz (28.6 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page