Stream Processing with SQLite - Stateful Transformation Tutorial
Syncing real-time Wikipedia analysis to a spreadsheet with SQL and Estuary Flow
0:00 Intro
0:22 Scenario
2:17 Tutorial Begins
2:43 GitPod
3:15 Set up flow.yaml
5:24 Migration
6:27 Lambda
10:26 Preview
12:29 Schema Inference
13:22 Publish
13:52 Create Materialization
14:45 Validation
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At times, the collections generated by a capture may not be suitable for your needs. For instance, you might want to filter certain documents or add calculations to them. Perhaps you need to unpack an array nested inside or aggregate data from many documents. Alternatively, you might need to merge across several collections using a common key, or employ business logic to arrive at a real-time decision. With Flow derivations, you can perform a wide range of transformations, from a simple remapping to complicated, self-referential, and stateful transaction processing.
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