Understanding the Scenario:The database administrator wants to improve the performance of a nightly data load process, which involves truncating and appending a large table with geometry and several attributes. The current Append operation takes 120 minutes, and indexes are re-created after the data is loaded.
Identifying the Bottleneck:
* Spatial indexes speed up query performance but can significantly slow down data loading operations like Append.
* When loading large datasets, maintaining the spatial index during the operation forces constant updates, leading to performance degradation.
Recommended Optimization:
* Removing the Spatial Index:
* Before the Append operation, drop the spatial index to eliminate overhead during data insertion.
* After the Append operation completes, recreate the spatial index to restore query performance.
* This approach ensures that the Append process only focuses on inserting records without additional computational load from maintaining the spatial index.
Steps to Implement the Recommendation:
* Drop the spatial index using the appropriate database management command or tool.
* Execute the Append process.
* Rebuild the spatial index once the Append process is complete.
References:
* Esri Documentation: Best practices for large data loads: Managing Indexes.
* Spatial Index Concepts: Understanding how spatial indexes impact data loading operations.
Why the Correct Answer is B:Removing the spatial index before appending large datasets can significantly reduce the time required for data insertion. Options A (removing the objectid index) and C (adding a unique key index) are irrelevant because the objectid index is system-managed and the unique key index creation would not improve the performance of the Append operation.