Best Practices Near Real-time Processing

[Gilg]

HI All,

We are ingesting 1000 files in json format and different sizes per minute. DLT is in continuous mode. Unity Catalog is enabled workspace.  We are using the default setting of Autoloader (Directory Listing) and Silver has CDC as well.

We aim to have a near real-time processing. What are the best practices to do this? 

Cheers,

[Kaniz]

Hi @Gilg, Achieving near real-time processing for your data ingestion and processing pipeline is crucial.

Here are some best practices to consider:

• Plan your data isolation model: When using a data platform like Azure Databricks, consider setting up data isolation boundaries between different environments (e.g., development and production) or organizational units. Unity Catalog can help manage these boundaries effectively¹.
• Configure a Unity Catalog metastore: Unity Catalog’s metastore serves as the top-level container for objects. Properly organizing your data within the metastore ensures efficient governance and access control.

• Delta Live Tables (DLT) and Unity Catalog Integration:

  • DLT as a Process in a Larger Pipeline: Treat DLT as a process or task within a larger pipeline. Decouple it from your main workflow to allow asynchronous operation. DLT essentially combines materializations of your data into logical segments².
  • Unity Catalog and DLT Working Together: By integrating Unity Catalog and DLT, you can fully leverage....
• Streaming and Incremental Processing:
  • Use Databricks for Near Real-Time Processing: Databricks provide optimizations for streaming and incremental data processing. For most streaming or incremental ETL tasks, consider using Delta Live Tables.
• Remember that these practices are guidelines, and you may need to tailor them to your specific use case. Regularly monitor and fine-tune your pipeline to ensure optimal performance and reliability.
• Cheers to achieving near real-time processing!