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Answer: Table partitioning allows delete operations to utilize partition boundaries for efficiency.
✅ **B. Table partitioning allows delete operations to utilize partition boundaries for efficiency.** - Partitioning by topic and month enables targeted deletion of 'user_activity' data older than two months, improving performance by scanning only relevant partitions. ❌ **A. Table partitioning enables the immediate deletion of files without the need for the VACUUM command.** - While partitioning isolates data for deletion, the VACUUM command is still required to physically remove files and reclaim storage space. ❌ **C. Table partitioning decreases query latency during the deletion of large data files.** - Partitioning reduces scan time by skipping irrelevant partitions but doesn't inherently speed up the rewriting of data within targeted partitions. ❌ **D. Table partitioning prevents time travel access to PII data post-deletion.** - Delta Lake's time travel feature allows querying previous table versions unless explicitly removed with VACUUM, regardless of partitioning. ❌ **E. None of the above. Table partitioning does not support the specified requirement.** - As detailed in option B, partitioning is effective for meeting the deletion requirement by enabling targeted operations on specific partitions.
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A data engineering team uses a pipeline to ingest Kafka source data into a Multiplex bronze table, partitioned by topic and month. A new engineer notices the 'user_activity' topic contains Personal Identifiable Information (PII) that must be deleted every two months per the company’s SLA. How can table partitioning assist in meeting this requirement?
A
Table partitioning enables the immediate deletion of files without the need for the VACUUM command.
B
Table partitioning allows delete operations to utilize partition boundaries for efficiency.
C
Table partitioning decreases query latency during the deletion of large data files.
D
Table partitioning prevents time travel access to PII data post-deletion.
E
None of the above. Table partitioning does not support the specified requirement.