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In this section, we provide guides and references to use the BigTable connector. Configure and schedule BigTable metadata and profiler workflows from the OpenMetadata UI:

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How to Run the Connector Externally

To run the Ingestion via the UI you’ll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment. If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.

External Schedulers

Get more information about running the Ingestion Framework Externally

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Requirements

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Python Requirements

We have support for Python versions 3.9-3.11
To run the BigTable ingestion, you will need to install: 
pip3 install "openmetadata-ingestion[bigtable]"

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GCP Permissions

To execute metadata extraction and usage workflow successfully the user or the service account should have enough access to fetch required data. Following table describes the minimum required permissions
#GCP PermissionRequired For
1bigtable.instances.getMetadata Ingestion
2bigtable.instances.listMetadata Ingestion
3bigtable.tables.getMetadata Ingestion
4bigtable.tables.listMetadata Ingestion
5bigtable.tables.readRowsMetadata Ingestion

Create Custom GCP Role

Checkout this documentation on how to create a custom role and assign it to the service account.

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Metadata Ingestion

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1. Define the YAML Config

This is a sample config for BigTable:

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2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run: 
metadata ingest -c <path-to-yaml>
Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration, you will be able to extract metadata from different sources.