turbo-transforms

To write SQL transforms for EVM logs, use Goldsky SQL functions to decode raw Ethereum logs, extract event parameters like sender and receiver, and filter specific events for pipeline processing.

Yes, you can combine multiple events into a single data stream by using the UNION ALL operator within your SQL transform to merge decoded Transfer and Approval event data for unified analysis.

The best way to debug data transformation logic is to break down complex SQL queries into chained transforms, verifying data type casting and event filtering steps individually before combining outputs.

You can chain multiple SQL transforms together by structuring your data pipeline logic sequentially, allowing the output of one data manipulation step to serve as the input for the next filtering or casting operation.

Yes, this approach supports advanced data processing logic by allowing you to combine standard SQL functions with specialized Goldsky SQL functions to manipulate and cast types within Turbo data pipelines.

You need to cast data types when decoding raw Ethereum logs to ensure extracted EVM event parameters, such as amounts and addresses, are properly formatted for downstream data transformation and analysis.