Skip to main content

Library for ingesting Redshift metadata into Google Cloud Data Catalog

Project description

google-datacatalog-redshift-connector

Library for ingesting Greenplum metadata into Google Cloud Data Catalog.

Python package PyPi License Issues

Disclaimer: This is not an officially supported Google product.

Table of Contents


1. Installation

Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python environments. The basic problem it addresses is one of dependencies and versions, and indirectly permissions.

With virtualenv, it's possible to install this library without needing system install permissions, and without clashing with the installed system dependencies. Make sure you use Python 3.6+.

1.1. Mac/Linux

pip3 install virtualenv
virtualenv --python python3.6 <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install google-datacatalog-redshift-connector

1.2. Windows

pip3 install virtualenv
virtualenv --python python3.6 <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install google-datacatalog-redshift-connector

1.3. Install from source

1.3.1. Get the code

git clone https://github.com/GoogleCloudPlatform/datacatalog-connectors-rdbms/
cd datacatalog-connectors-rdbms/google-datacatalog-redshift-connector

1.3.2. Create and activate a virtualenv

pip3 install virtualenv
virtualenv --python python3.6 <your-env>
source <your-env>/bin/activate

1.3.3. Install the library

pip install .

2. Environment setup

2.1. Auth credentials

2.1.1. Create a service account and grant it below roles

  • Data Catalog Admin

2.1.2. Download a JSON key and save it as

  • <YOUR-CREDENTIALS_FILES_FOLDER>/redshift2dc-credentials.json

Please notice this folder and file will be required in next steps.

2.2. Set environment variables

Replace below values according to your environment:

export GOOGLE_APPLICATION_CREDENTIALS=data_catalog_credentials_file

export REDSHIFT2DC_DATACATALOG_PROJECT_ID=google_cloud_project_id
export REDSHIFT2DC_DATACATALOG_LOCATION_ID=google_cloud_location_id
export REDSHIFT2DC_SERVER=redshift_server
export REDSHIFT2DC_USERNAME=redshift_username
export REDSHIFT2DC_PASSWORD=redshift_password
export REDSHIFT2DC_DATABASE=redshift_database
export REDSHIFT2DC_RAW_METADATA_CSV=redshift_raw_csv (If supplied ignores the REDSHIFT server credentials)

3. Run entry point

3.1. Run Python entry point

  • Virtualenv
google-datacatalog-redshift-connector \
--datacatalog-project-id=$REDSHIFT2DC_DATACATALOG_PROJECT_ID \
--datacatalog-location-id=$REDSHIFT2DC_DATACATALOG_LOCATION_ID \
--redshift-host=$REDSHIFT2DC_SERVER \
--redshift-user=$REDSHIFT2DC_USERNAME \
--redshift-pass=$REDSHIFT2DC_PASSWORD \
--redshift-database=$REDSHIFT2DC_DATABASE  \
--raw-metadata-csv=$REDSHIFT2DC_RAW_METADATA_CSV      

3.2. Run Docker entry point

docker build -t redshift2datacatalog .
docker run --rm --tty -v YOUR-CREDENTIALS_FILES_FOLDER:/data redshift2datacatalog \
--datacatalog-project-id=$REDSHIFT2DC_DATACATALOG_PROJECT_ID \
--datacatalog-location-id=$REDSHIFT2DC_DATACATALOG_LOCATION_ID \
--redshift-host=$REDSHIFT2DC_SERVER \
--redshift-user=$REDSHIFT2DC_USERNAME \
--redshift-pass=$REDSHIFT2DC_PASSWORD \
--redshift-database=$REDSHIFT2DC_DATABASE  \
--raw-metadata-csv=$REDSHIFT2DC_RAW_METADATA_CSV       

4 Scripts inside tools

4.1. Run clean up

# List of projects split by comma. Can be a single value without comma
export REDSHIFT2DC_PROJECT_IDS=my-project-1,my-project-2
# Run the clean up
python tools/cleanup_datacatalog.py --datacatalog-project-ids=$REDSHIFT2DC_PROJECT_IDS

5. Developer environment

5.1. Install and run Yapf formatter

pip install --upgrade yapf

# Auto update files
yapf --in-place --recursive src tests

# Show diff
yapf --diff --recursive src tests

# Set up pre-commit hook
# From the root of your git project.
curl -o pre-commit.sh https://raw.githubusercontent.com/google/yapf/master/plugins/pre-commit.sh
chmod a+x pre-commit.sh
mv pre-commit.sh .git/hooks/pre-commit

5.2. Install and run Flake8 linter

pip install --upgrade flake8
flake8 src tests

5.3. Run Tests

python setup.py test

6. Troubleshooting

In the case a connector execution hits Data Catalog quota limit, an error will be raised and logged with the following detailement, depending on the performed operation READ/WRITE/SEARCH:

status = StatusCode.RESOURCE_EXHAUSTED
details = "Quota exceeded for quota metric 'Read requests' and limit 'Read requests per minute' of service 'datacatalog.googleapis.com' for consumer 'project_number:1111111111111'."
debug_error_string = 
"{"created":"@1587396969.506556000", "description":"Error received from peer ipv4:172.217.29.42:443","file":"src/core/lib/surface/call.cc","file_line":1056,"grpc_message":"Quota exceeded for quota metric 'Read requests' and limit 'Read requests per minute' of service 'datacatalog.googleapis.com' for consumer 'project_number:1111111111111'.","grpc_status":8}"

For more info about Data Catalog quota, go to: Data Catalog quota docs.

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 google-datacatalog-redshift-connector, version 0.7.0
Filename, size File type Python version Upload date Hashes
Filename, size google_datacatalog_redshift_connector-0.7.0-py2.py3-none-any.whl (8.5 kB) File type Wheel Python version py2.py3 Upload date Hashes View
Filename, size google-datacatalog-redshift-connector-0.7.0.tar.gz (7.8 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