bqup-spartez 0.0.7

BigQuery backup scripts - Spartez fork

bqup

bqup is a backup tool for BigQuery projects. It can export a BigQuery project's structure and source code while mimicking the hierarchy of datasets and tables.

For the full story of why we made bqup, check out our blog post!

Installation

bqup can be installed using pip.

$ pip install bqup

Alternatively, you can also clone the repository then run install.

$ git clone https://github.com/thinkingmachines/bqup.git
$ cd bqup
$ python3 setup.py install

Usage

Command line options

You can list down the options by running bqup --help.

bqup [-p PROJECT_ID] [-d TARGET_DIR] [-fvx]

Options:
  -p PROJECT_ID, --project PROJECT_ID  Project ID to load. If unspecified,
                                       defaults to current project in
                                       configuration.
  -d TARGET_DIR, --dir TARGET_DIR      The target directory where the project
                                       will be written. Defaults to current
                                       timestamp.
  -f --force                           Overwrite target directory if it exists.
  -v --verbose                         Print a summary of the loaded project.
  -x --schema                          Export table schemata as json.

Development

1. Set up gcloud to run with your personal account (aka run with scissors).

2. Set up application-default.

   $ gcloud auth application-default login
   

3. Install wheel.

   $ pip3 install wheel
   

4. Install bqup.

   pip3 install -e .
   

   Alternatively, you can also install it using:

   python3 setup.py develop
   

5. Run bqup (see Usage).

Production

Note: When deploying for a new GCP project, consider using Cloud Scheduler

1. Turn off your host Google Instance.
2. Enable BigQuery on the instance's Cloud API Access Scopes
3. Start the instance.
4. ssh into the Google Instance you want to run bqup from.
5. Authorize your Compute Instance Account to read from the target BigQuery project.
6. Install bqup via pip install bqup, optionally inside a virtual environment.
7. Run bqup
   • If it still doesn't work, check in IAM that the service account you are using has BigQuery read access.

Setting up regular backups

1. On the machine that will run your backups, set up your git config (username, email, the usual).

2. Make a directory to use as the Git repository. For this example, let's use repo:

   $ mkdir repo cd repo git init
   

3. Add the remote to the git repository (ideally a GCP repository). For this example, let's use google:

   $ git remote add google <url-to-remote-repository>
   

4. Create a script called bqup.sh that follows the following template. For our example, our repository is dedicated to backups, so we just assume that our HEAD is the latest and just push gently to master.

   #!/bin/bash
   <absolute-path-to-bqup> -p <project-id> -d <absolute-path-to-repo>/projects -fv >> <absolute-path-to-log-file>
   cd <absolute-path-to-repo>
   date > last-updated.log
   git add .
   git commit -m "Automated bqup"
   git push <remote> <branch>
   

5. Add this script to your crontab to run as frequently as your heart desires.

Distribution

Run make test to try a test upload.

Run make dist to upload a distribution.

Both of these will call make build, which rebuilds the package locally.

Contributing

If you wish to contribute, check out our contributing guide!

A list is maintained for all external contributors who have submitted pull requests that were subsequently approved. Users are allowed and encouraged to fork the project and submit pull requests and issues. We only request that contributions adhere to these guidelines:

• Commit messages
• Github flow

The official maintainers in charge of responding to issues and merging pull requests are:

• Pepe Bawagan
• Mark Steve Samson
• Carlson Cheng

Contributors

Thanks to all these wonderful people who've helped out with bqup:

Jess

Ram

Pepe Berba

Tim Pron

Enzo

Ardie

Disclaimers

bqup is maintained on a best effort basis:

• No amount of official time is currently being dedicated to the regular maintenance of this project.
• Thinking Machines does not make any guarantees about the quality of the software.

Thinking Machines reserves the rights to:

• refuse to resolve issues
• close issues without resolution
• request changes to pull requests
• reject pull requests outright