While the simple pipelines let you get real-time data from one of our data sets into your own destination, most teams also do enrichment and filtering using transforms. With transforms, you can decode check external API is call contracts storage and more. You can even call your own APIs in order to tie the pipeline into your existing system seamlessly.

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SQL Transforms

SQL transforms allow you to write SQL queries to modify and shape data from multiple sources within the pipeline. This is ideal for operations that need to be performed within the data pipeline itself, such as filtering, aggregating, or joining datasets. Depending on how you choose to source your data, you might find that you run into 1 of 2 challenges:
  1. You only care about a few contracts Rather than fill up your database with a ton of extra data, you’d rather filter down your data to a smaller set.
  2. The data is still a bit raw Maybe you’d rather track gwei rounded to the nearest whole number instead of wei. You’re looking to map data to a different format so you don’t have to run this calculation over and over again.

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External Handler Transforms

With external handler transforms, you can send data from your Mirror pipeline to an external service via HTTP and return the processed results back into the pipeline. This opens up a world of possibilities by allowing you to bring your own custom logic, programming languages, and external services into the transformation process. Key Features of External Handler Transforms:
  • Send data to external services via HTTP.
  • Supports a wide variety of programming languages and external libraries.
  • Handle complex processing outside the pipeline and return results in real time.
  • Guaranteed at least once delivery and back-pressure control to ensure data integrity.

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How External Handlers work

  1. The pipeline sends a POST request to the external handler with a mini-batch of JSON rows.
  2. The external handler processes the data and returns the transformed rows in the same format and order as received