Question 5
Domain 1: Developing Code for Data Processing using Python and SQLA source database emits out-of-order inserts, updates, and deletes with a monotonically increasing sequence column. Which ingestion pattern best builds a current-state silver table?
Correct answer: C
Explanation
A Lakeflow Declarative Pipelines AUTO CDC flow is designed for change data capture and can apply inserts, updates, and deletes in sequence. Keying by the business key and sequencing by the monotonically increasing source column ensures the latest event wins, which builds a current-state silver table from out-of-order changes.
Why each option is right or wrong
A. Append every event forever and let analysts resolve current state in queries
Appending forever keeps raw history, but does not materialize a maintained current-state table.
B. Reload the full source every minute
Frequent full reloads are brute-force replication, not efficient ordered CDC handling.
C. Use a Lakeflow Declarative Pipelines AUTO CDC flow keyed by the business key and sequenced by the source column
Lakeflow Declarative Pipelines AUTO CDC is the CDC-specific ingestion primitive for applying inserts, updates, and deletes into a target table while preserving the latest row per entity; it uses the declared key to identify the business record and the sequence column to order late or out-of-order events. In this scenario, the monotonically increasing source sequence column is the required ordering field, so the pipeline can deterministically resolve multiple events for the same key and materialize the current-state silver table rather than an append-only history.
D. Use `COPY INTO` with `mergeSchema` and no delete handling
COPY INTO loads files, but without delete logic it cannot maintain true current state.