Docker

Metarank official image is published in docker hub as metarank/metarank.
We publish the :latest tag, although it's not always recommended to have any production deployments without pinning a specific version.
Official docker images are multi-arch, and cross-built for the following platforms:
linux/amd64: a regular docker image
linux/arm64/v8: docker image which will work natively (so without emulation) on platforms like Mac M1/M2.
Running the docker image
All metarank sub-commands are wrapped into a single command-line API. To see the CLI, run the docker container:
$ docker run metarank/metarank:0.6.4 --help
​
+ exec /opt/java/openjdk/bin/java -jar /app/metarank.jar --help
​
                __                              __    
  _____   _____/  |______ ____________    ____ |  | __
 /     \_/ __ \   __\__  \\_  __ \__  \  /    \|  |/ /
|  Y Y  \  ___/|  |  / __ \|  | \// __ \|   |  \    < 
|__|_|  /\___  >__| (____  /__|  (____  /___|  /__|_ \
      \/     \/          \/           \/     \/     \/ ver:0.6.4
Usage: metarank <subcommand> <options>
Resources
Metarank image exposes a /data volume to handle all the local IO. For example, you can pass the input training dataset from your local host using the docker's -v switch:
docker run -v /home/user/input:/data metarank/metarank:latest train <opts>
Memory
Metarank docker container uses 1Gb of JVM heap by default. In practice the actual RSS memory usage is a bit higher than the heap size due to JVM's extra overhead.
This can be configured with the JVM_OPTS environment variable:
docker run -e JVM_OPTS="-Xmx5g" metarank/metarank:latest train <opts>
Ports
The image exposes the following ports:
8080 for API access for the inference and ingestion APIs
To map these ports to your host, use the -p flag:
docker run -p 8080:8080 metarank/metarank:latest serve <opts>
Standalone
Kubernetes
Last modified 15d ago