Lakeflow Spark Declarative Pipelines (SDP) Why & When Should I Use Them? скачать в хорошем качестве

Lakeflow Spark Declarative Pipelines (SDP) Why & When Should I Use Them?

Spark Declarative Pipelines: The Best Use Case for Streaming Tables in Data Ingestion In this video, I break down what I believe is the single best use case for Spark Declarative Pipelines (formerly Delta Live Table Pipelines or DLT Pipelines): creating and refreshing streaming tables as part of your data ingestion flow. Streaming tables let you process each input row exactly once, handle massive volumes of append-only data, and incrementally refresh — no full recomputation needed. Combine that with the declarative model of SDP, where you define what your data should look like rather than how to build it, and you get an ingestion layer that practically runs itself. #databricks #apachespark #python #polars #pipelines #automation #data #dataengineering #bigdata #gcp