Ingestion Customization

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Ingestion Customization: Enhancing Asset Auto-Tagging in OMD

As a user of the Open Metadata (OMD) system, you're likely aware of its capabilities in ingesting tables and views from various data sources, including AWS Athena. One of the key features of OMD is its ability to build lineage, which helps understand internal dependencies between assets. However, as your data management needs evolve, you may encounter requirements that go beyond the standard features of OMD. In this article, we'll explore the concept of ingestion customization, specifically focusing on asset auto-tagging, and how it can be achieved using hooks and custom connectors.

Ingestion customization refers to the ability to modify or extend the behavior of OMD's ingestion process to accommodate specific requirements. In your case, you're looking to tag assets based on specific values of the "Parameters" field in Glue metadata, rather than relying on LF-tags. This is a common scenario where the standard features of OMD may not be sufficient, and a more tailored approach is needed.

When attempting to customize the ingestion process, you may encounter internal dependencies and configurations that make it difficult to achieve your goals. In your case, you tried inheriting from the AthenaConnector class and using it as a Custom Ingestion class, but this approach didn't work due to the complexities of internal dependencies and configurations.

So, what are your alternatives? One option is to copy the existing Connector with all its functions, such as lineage, and then use it as a modified copy. This approach would allow you to leverage the existing functionality while still making the necessary modifications to accommodate your specific requirements.

Hooks are a powerful tool for customizing the ingestion process in OMD. By using hooks, you can execute custom code at specific points during the ingestion process, such as after table creation or database creation. This allows you to perform tasks like asset auto-tagging without having to write a fully custom Athena connector.

Using hooks offers several benefits, including:

  • Flexibility: Hooks enable you to customize the ingestion process without modifying the underlying code.
  • Reusability: Hooks can be reused across different data sources and ingestion processes.
  • Scalability: Hooks can be easily added or removed as needed, making it easy to adapt to changing requirements.

To implement hooks in OMD, you'll need to create a custom connector that includes the necessary hook functions. These functions will be executed at specific points during the ingestion process, allowing you to perform custom tasks like asset auto-tagging.

Let's consider an example use case where you want to tag assets based on specific values of the "Parameters" field in Glue metadata. Using hooks, you can create a custom connector that includes a hook function that executes after table creation. This function can then check the "Parameters" field and apply the necessary tags to the asset.

** Example: Custom Connector with Hook Function**

import logging

from omd.connector import AthenaConnector
from omd.hooks import Hook

class CustomAthenaConnector(AthenaConnector):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.hooks = Hook()

    def after_table_creation(self, table):
        # Check the "Parameters" field and apply tags as needed
        if table.get('Parameters') == 'specific_value':
            self.hooks.apply_tag(table, 'custom_tag')

Ingestion customization is a powerful feature that allows you to tailor the behavior of OMD's ingestion process to meet specific requirements. By using hooks, you can execute custom code at specific points during the ingestion process, making it easy to perform tasks like asset auto-tagging. In this article, we explored the concept of ingestion customization, including the challenges and alternatives, and provided a code example of how to implement hooks in OMD. Whether you're looking to enhance asset auto-tagging or perform other custom tasks, hooks offer a flexible and scalable solution for ingestion customization.
Ingestion Customization: Q&A

In our previous article, we explored the concept of ingestion customization in Open Metadata (OMD), specifically focusing on asset auto-tagging. We discussed the need for customization, the challenges of implementing it, and the benefits of using hooks. In this article, we'll answer some frequently asked questions (FAQs) about ingestion customization to help you better understand this powerful feature.

A: Ingestion customization refers to the ability to modify or extend the behavior of OMD's ingestion process to accommodate specific requirements. You may need ingestion customization if you want to perform tasks like asset auto-tagging, data quality checks, or data transformation, which are not supported by the standard features of OMD.

A: Hooks are a type of custom code that can be executed at specific points during the ingestion process. They allow you to perform tasks like asset auto-tagging, data quality checks, or data transformation without having to write a fully custom connector. Hooks are executed by the OMD engine, which provides a flexible and scalable way to customize the ingestion process.

A: To implement hooks in OMD, you'll need to create a custom connector that includes the necessary hook functions. These functions will be executed at specific points during the ingestion process, allowing you to perform custom tasks. You can use the OMD API to create custom connectors and hook functions.

A: Using hooks offers several benefits, including:

  • Flexibility: Hooks enable you to customize the ingestion process without modifying the underlying code.
  • Reusability: Hooks can be reused across different data sources and ingestion processes.
  • Scalability: Hooks can be easily added or removed as needed, making it easy to adapt to changing requirements.

A: Yes, you can use hooks with existing connectors. In fact, hooks are designed to work seamlessly with existing connectors, allowing you to customize the ingestion process without having to rewrite the entire connector.

A: Debugging hooks can be challenging, but OMD provides several tools to help you debug your custom code. You can use the OMD API to log messages, set breakpoints, and inspect variables to troubleshoot issues with your hooks.

A: Yes, you can use hooks with multiple data sources. Hooks are designed to be reusable across different data sources and ingestion processes, making it easy to customize the ingestion process for multiple data sources.

A: When the OMD engine changes, you may need to update your hooks to ensure compatibility. OMD provides several tools to help you update your hooks, including API documentation, release notes, and community support.

Ingestion customization is a powerful feature that allows you to the behavior of OMD's ingestion process to meet specific requirements. By using hooks, you can execute custom code at specific points during the ingestion process, making it easy to perform tasks like asset auto-tagging. In this article, we answered some frequently asked questions about ingestion customization to help you better understand this feature. Whether you're looking to enhance asset auto-tagging or perform other custom tasks, hooks offer a flexible and scalable solution for ingestion customization.