From the course: Advanced Snowflake: Deep Dive Cloud Data Warehousing and Analytics
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Continuous data pipelines: Tasks and streams - Snowflake Tutorial
From the course: Advanced Snowflake: Deep Dive Cloud Data Warehousing and Analytics
Continuous data pipelines: Tasks and streams
For completeness, let's do a quick overview of Imperative Pipelines using Tasks and Streams. With Imperative Pipelines, you define the exact sequence of events that you want to transform your data. You'll tell the system precisely how to move data, when to transform it, where to store it, rather than letting Snowflake decide the best path. path. In imperative pipelines, you write each step, ingest, transform, merge, load, and control the order of execution using tasks and scripting. This mirrors traditional procedural logic where the process is spelled out. In this model, you use tasks and streams. Snowflakes tasks serve as the orchestrators. You schedule or trigger each step. Streams capture changes and you write SQL or Python that applies logic to those changes. The pipeline runs a defined sequence of actions, not just a final desired outcome. Here in an imperative pipeline, you control dependencies and timing. For example, run transformation B only after transformation A completes.…
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