Docker image for the mongo-connector.
For more information about this image and its history, please see the relevant manifest file in the gorillastack/docker-mongo-connector
GitHub repo.
Docker image with mongo-connector installed. The image is built based on Python 3.4.3.
The docker image is auto built at https://registry.hub.docker.com/u/gorillastack/mongo-connector/.
FROM gorillastack/mongo-connector:latest
By default, it will connect mongo node ($MONGO
or the mongo host, on port $MONGOPORT
or 27017) and elasticsearch node ($ELASTICSEARCH
or the elasticsearch host, on port $ELASTICPORT or 9200).
You can use the $NS_SET
environment variable to set the namespace-set (-n) option for mongo-connector. This allows you to specify the namespaces mongo-connector should write to elasticsearch from mongodb. E.g. -e NS_SET="app.tags"
will read from a db named 'app', from collection named 'tags', and write to an elasticsearch index named 'app' with a type of 'tags'.
Boot two containers with name mongo (config to cluster) and elasticsearch.
$ docker run -d --link=mongo:mongo --link=elasticsearch:elasticsearch gorillastack/mongo-connector
It will connect the two containers together to sync data between each other.
The image is based on official python:3.4.3
.
The repository is an original fork of 'yeasy/mongo-connector'.
Install the mongo-connector:2.4.
This image is officially supported on Docker version 1.7.1.
Support for older versions (down to 1.0) is provided on a best-effort basis.
Be sure to familiarize yourself with the repository's README.md
file before attempting a pull request.
If you have any problems with or questions about this image, please contact us through a GitHub issue.
You can also reach many of the official image maintainers via the email.
You are invited to contribute new features, fixes, or updates, large or small; we are always thrilled to receive pull requests, and do our best to process them as fast as we can.
Before you start to code, we recommend discussing your plans through a GitHub issue, especially for more ambitious contributions. This gives other contributors a chance to point you in the right direction, give you feedback on your design, and help you find out if someone else is working on the same thing.