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README.md

Mongo Connector

Docker images for the mongo-connector.

Supported tags and respective Dockerfile links

For more information about this image and its history, please see the relevant manifest file in the yeasy/docker-mongo-connector GitHub repo.

What is docker-mongo-connector?

Docker image with mongo-connector installed. The image is built based on Python 3.4.3.

How to use this image?

The docker image is auto built at https://registry.hub.docker.com/u/yeasy/mongo-connector/.

In Dockerfile

FROM yeasy/mongo-connector:latest

Local Run

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).

Boot two containers with name mongo (config to cluster) and elasticsearch.

$ docker run -d --link=mongo:mongo --link=elasticsearch:elasticsearch yeasy/mongo-connector

It will connect the two containers together to sync data between each other.

Which image is based on?

The image is based on official python:3.4.3.

What has been changed?

Config TZ

Config timezone to Asia/Shanghai.

Install mongo-connector

Install the mongo-connector:2.1.

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.

User Feedback

Documentation

Be sure to familiarize yourself with the repository's README.md file before attempting a pull request.

Issues

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.

Contributing

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.

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