The right time to stop tuning an Oracle database is often determined by the point of diminishing returns - when the cost of further tuning (in terms of time, resources, or money) exceeds the performance benefits gained.
This is often related to the budget allocated for performance tuning.
* A (Correct):When the allocated budget for performance tuning has been exhausted, it may be time to stop tuning unless the benefits of further tuning justify requesting additional budget.
* B (Incorrect):Eliminating all concurrency waits from the Top 10 is an unrealistic goal since some waits are inevitable and can occur due to application design, which might not be possible to eliminate completely.
* C (Incorrect):The buffer cache and library cache hit ratio being above 95% does not necessarily indicate that the database is fully optimized. Hit ratios are not reliable indicators of database performance and should not be used as sole criteria to end tuning efforts.
* D (Incorrect):Having I/O less than 10% of DB time is not a definitive indicator to stop tuning. It is essential to consider the overall performance goals and whether they have been met rather than focusing solely on I/O metrics.
References:
* Oracle Database Performance Tuning Guide:Introduction to Performance Tuning
* Oracle Database 2 Day + Performance Tuning Guide:Understanding the Tuning Process

Given that index range scan operations on IX_SALES_TIME_ID are slower due to an increase in buffer gets, the aim is to improve the efficiency of the index access. In this scenario:
* B (Correct): Re-creating the index using ADVANCED COMPRESSION can reduce the size of the index, which can lead to fewer physical reads (reduced I/O) and buffer gets when the index is accessed, as more of the index can fit into memory.
The other options would not be appropriate because:
* A (Incorrect): Re-creating the SALES table sorted in order of the index might not address the issue of excessive buffer gets. Sorting the table would not improve the efficiency of the index itself.
* C (Incorrect): Using the columns in IX_SALES_TIME_ID as a hash partitioning key for the SALES table is more relevant to data distribution and does not necessarily improve index scan performance.
* D (Incorrect): Hash partitioning the index is generally used to improve the scan performance in a parallel query environment, but it may not reduce the number of buffer gets in a single-threaded query environment.
References:
* Oracle Database SQL Tuning Guide: Managing Indexes
* Oracle Database SQL Tuning Guide: Index Compression

A high buffer cache hit ratio typically indicates that the database is effectively using the buffer cache and does not often need to read data from disk. However, this metric alone is not a reliable indicator of the I/O performance of the database for several reasons:
* Full table scans and fast full index scans (A) can bypass the buffer cache by design if the blocks are not deemed reusable shortly, which can impact the cache hit ratio.
* A high cache hit ratio (B) can be misleading if the database performance is poor due to other factors, such as inefficient queries or contention issues.
* The buffer cache advisory (C) is a more valuable tool for understanding the potential impact of different cache sizes on the database's I/O performance. It simulates scenarios with different cache sizes and provides a more targeted recommendation.
* The RECYCLE and KEEP buffer caches (D) are specialized caches designed for certain scenarios.
While high hit ratios can be beneficial, they are not universally required; some workloads might not be significantly impacted by lower hit ratios in these caches.
* A lower cache hit ratio (E) does not necessarily mean poor I/O performance. In some cases, a system with a well-designed storage subsystem and efficient queries might perform well even with a lower cache hit ratio.
References
* Oracle Database 19c Performance Tuning Guide - Buffer Cache Hit Ratio
* Oracle Database 19c Performance Tuning Guide - v$db_cache_advice

Baselines are typically taken during the production phase of the application lifecycle. They provide a snapshot of performance metrics under normal operating conditions which can be used for comparison against future performance. Baselines are essential for understanding how the system performs under its typical workload and for detecting deviations from this expected performance over time, especially after changes like migrations, upgrades, or significant changes in user activity.
References
* Oracle Database 19c Performance Tuning Guide - Managing Performance Through Baselines

The SQL Tuning Advisor provides recommendations for improving SQL query performance. This may include suggestions for creating additional indexes to speed up data retrieval and materialized views to precompute and store query results.References:
* Oracle Database SQL Tuning Guide, 19c