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Answer: It enables the efficient propagation of row-level deletes and updates without requiring expensive full table scans.
Change Data Feed (CDF) solves the challenge of propagating incremental updates and deletes to downstream systems. Instead of consumers having to perform costly full table scans or re-process entire datasets to identify changes, CDF exposes a stream of row-level modifications (inserts, updates, and deletes) that can be consumed incrementally.
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How does the Delta Lake Change Data Feed (CDF) feature specifically assist downstream consumers in handling data modifications?
A
It streamlines the management of complex schema evolutions across a multi-table Lakehouse architecture.
B
It improves query performance by automatically optimizing file sizes through background compaction.
C
It enables the efficient propagation of row-level deletes and updates without requiring expensive full table scans.
D
It automates the physical partitioning of the table to enhance overall storage and retrieval performance.