ADA-C01 Question 542
Single answerIceberg tablesA data platform team stores curated Parquet data in an external volume backed by cloud object storage and wants Snowflake to manage it as an Apache Iceberg table so other engines can also read the data. After several merge and delete operations from Snowflake, analysts notice query performance degrading because many small data files and outdated metadata files have accumulated in storage. The team wants Snowflake to automatically maintain the table and reduce manual operational work. Which action should the administrator take?
- A
Enable automatic refresh on the Iceberg table so Snowflake compacts small files and removes obsolete snapshots during metadata refresh
- B
Configure a search optimization service on the Iceberg table because it automatically rewrites Iceberg data files and cleans up stale manifests
- C
Enable automatic maintenance for the Snowflake-managed Iceberg table so Snowflake can perform background optimization and metadata cleanup
- D
Convert the Iceberg table to a transient table so Snowflake can skip fail-safe and reclaim old Iceberg metadata files immediately
Show answer and explanation
Correct answer: C
Explanation
The scenario points to a Snowflake-managed Iceberg table, where Snowflake manages the table metadata and can perform background maintenance. In practice, repeated MERGE, UPDATE, and DELETE activity can create many small files and obsolete metadata/snapshot artifacts, which can degrade performance and increase storage clutter. The appropriate administrative response is to enable automatic maintenance so Snowflake handles optimization and cleanup tasks with less manual effort. By contrast, automatic refresh is about synchronizing metadata visibility, not physical maintenance; Search Optimization Service is a query acceleration feature, not an Iceberg compaction service; and transient table settings do not control Iceberg file maintenance. This aligns with Snowflake guidance for Snowflake-managed Iceberg tables, where Snowflake manages metadata lifecycle and maintenance operations to improve operational simplicity.
- A. Incorrect.
Incorrect. Automatic refresh is associated with keeping table metadata in sync for externally managed metadata scenarios, but it is not the feature used to compact small files or clean up outdated Iceberg snapshots and metadata files for a Snowflake-managed Iceberg table. A common misconception is to equate metadata refresh with physical optimization and maintenance.
- B. Incorrect.
Incorrect. Search Optimization Service can improve selective query performance for supported access patterns, but it does not perform Iceberg file compaction or snapshot/manifest cleanup. This distractor is plausible because both affect performance, but they address different layers: indexing/access-path optimization versus table maintenance.
- C. Correct.
Correct. For Snowflake-managed Iceberg tables, Snowflake can perform automatic maintenance tasks in the background, including optimization-related work and cleanup of obsolete metadata associated with Iceberg table operations. This is the administrative action that best addresses file proliferation and stale metadata while minimizing manual intervention.
- D. Incorrect.
Incorrect. Transient versus permanent affects data protection behavior such as fail-safe, not Iceberg maintenance semantics. Changing the table type does not enable compaction or metadata cleanup for Iceberg tables. This option reflects the misconception that storage-retention settings solve file-layout and metadata-management issues.