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Oracle Database 19c Performance and Tuning Management Sample Questions (Q29-Q34):

NEW QUESTION # 29
Examine this output of a query of VSPGA_TAPGET_ADVICE:

Which statements is true'

A. With a target of 700 MB or more, all multipass executions work areas would be eliminated.
B. With a target of 800 MB or more, all one-pass execution work areas would be eliminated.
C. GGREGATE_TARGET should be set to at least 700 MB.
D. PGAA_AGGREGATE should be set to at least 800 MB.

Answer: B

Explanation:
The query output from V$PGA_TARGET_ADVICE provides tuning information for the PGA (Program Global Area). Let's break it down step by step:
Key Columns in the Output:
* TARGET_MB:
* Represents the hypothetical PGA_AGGREGATE_TARGET values (in megabytes) evaluated by Oracle.
* CACHE_HIT_PERC:
* The percentage of work areas that could execute in-memory (optimal execution) without requiring temporary disk writes.
* Higher percentages indicate fewer work areas requiring disk I/O.
* ESTD_OVERALLOC_COUNT:
* The estimated number of work areas that need to go to disk (multipass operations or overallocations).
Observations from the Data:
* At TARGET_MB = 700 MB:
* The CACHE_HIT_PERC is 68%.
* The ESTD_OVERALLOC_COUNT is 30. This indicates that some multipass work areas still exist.
* At TARGET_MB = 800 MB:
* The CACHE_HIT_PERC rises to 74%.
* The ESTD_OVERALLOC_COUNT drops to 0. This indicates that no work areas require multipass execution.
* At TARGET_MB = 900 MB and above:
* The CACHE_HIT_PERC increases slightly to 82%-84%.
* The ESTD_OVERALLOC_COUNT remains 0, meaning that all work areas are now either optimal or one-pass.
Why D is Correct:
* At 800 MB or more, the ESTD_OVERALLOC_COUNT is 0, indicating that all one-pass execution work areas are eliminated.
* A one-pass execution requires temporary disk I/O for intermediate results, but with sufficient PGA, these are no longer necessary.
Why Other Options Are Incorrect:
* Option A:
* It mentions all multipass executions work areas would be eliminated at 700 MB. This is incorrect because, at 700 MB, the ESTD_OVERALLOC_COUNT is still 30, indicating some multipass work areas still exist.
* Option B:
* Suggests setting the PGA_AGGREGATE_TARGET to at least 800 MB, which is partially correct but does not address the elimination of one-pass execution.
* Option C:
* Suggests setting the PGA_AGGREGATE_TARGET to at least 700 MB, which is not sufficient to eliminate all one-pass executions, as shown by the ESTD_OVERALLOC_COUNT of 30.

NEW QUESTION # 30
Which statement is true about DB time in V$$YS_TIME_MODEL?

A. DB time includes the time spent executing the RMAN backup and restore command.
B. DB time is organized as a simple list of statistics and any time period is attributable to only one statistic.
C. DB tine excludes the time spent waiting for a CPU in the operating system run queue.
D. DB time can be many times greater than the elapsed time since the database instance started.

Answer: D

Explanation:
DB time includes the time spent on user and background processes. It can be greater than the elapsed time because it accumulates the active time of all the processes. For example, if two sessions are each active for 2 seconds at the same time, DB time would accumulate 4 seconds, while the elapsed time would be only 2 seconds.References:
* Oracle Database Performance Tuning Guide, 19c
* Oracle Database Reference, 19c

NEW QUESTION # 31
The CURS0R_SHARING and OPTIMIZER_CAPTURE_SQL_PLAN_BASELINES parameters are set to default. The top five wait events in an awr report are due to a large number of hard parses because of several almost identical SQL statements.
Which two actions could reduce the number of hard parses?

A. Increase the size of the library cache.
B. Set the CURSOR_SHARING parameter to FORCE.
C. Create the RECYCLE cache and cache tables accessed by the SQL statements.
D. Set OPTIMIZER_CAPTURE_SQL_PLAN_BASELINES to TRUE.
E. Create the KEEP cache and cache tables accessed by the SQL statements.

Answer: A,B

Explanation:
To reduce the number of hard parses due to several almost identical SQL statements, you can take the following actions:
* C (Correct): Increasing the size of the library cache can help reduce hard parses by providing more memory to store more execution plans. This allows SQL statements to be shared more effectively.
* E (Correct): Setting the CURSOR_SHARING parameter to FORCE will cause Oracle to replace literals in SQL statements with bind variables, which can significantly reduce the number of hard parses by making it more likely that similar SQL statements will share the same execution plan.
The other options do not directly impact the number of hard parses:
* A (Incorrect): Creating the KEEP cache and caching tables accessed by the SQL statements can improve performance for those tables, but it does not directly reduce the number of hard parses.
* B (Incorrect): Creating the RECYCLE cache and caching tables accessed by the SQL statements can make it more likely that objects will be removed from the cache quickly, which does not help with hard parse issues.
* D (Incorrect): Setting OPTIMIZER_CAPTURE_SQL_PLAN_BASELINES to TRUE can help stabilize SQL execution plans but will not reduce the number of hard parses. This parameter is used to automatically capture SQL plan baselines for repeatable SQL statements, which can prevent performance regressions due to plan changes.
References:
* Oracle Database Performance Tuning Guide: Minimizing Hard Parses
* Oracle Database SQL Tuning Guide: CURSOR_SHARING

NEW QUESTION # 32
Database performance has degraded recently.
index range scan operations on index ix_sales_time_id are slower due to an increase in buffer gets on sales table blocks.
Examine these attributes displayed by querying DBA_TABLES:

Now, examine these attributes displayed by querying DBA_INDEXES:

Which action will reduce the excessive buffer gets?

A. Re-create index IX_SALES_TIME_ID using ADVANCED COMPRESSION.
B. Partition index IX_SALES_TIME_ID using hash partitioning.
C. Re-create the SALES table sorted in order of index IX_SALES_TIME_ID.
D. Re-create the SALES table using the columns in IX_SALES_TIME_ID as the hash partitioning key.

Answer: A

Explanation:
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

NEW QUESTION # 33
For which two actions can SQL Performance Analyzer be used to assess the impact of changes to SQL performance?

A. database consolidation for pluggable databases (PDBs)
B. changes to database initialization parameters
C. storage, network, and interconnect changes
D. operating system and hardware migrations
E. operating system upgrades

Answer: A,B

Explanation:
SQL Performance Analyzer (SPA) can be used to assess the impact of different types of changes on SQL performance. These changes can include database initialization parameters, which can significantly affect how SQL statements are executed and therefore their performance. SPA allows you to capture a workload before and after the change and compare the performance of each SQL statement.
Database consolidation, including moving to pluggable databases (PDBs), can also affect SQL performance.
SPA can analyze the SQL workload to see how consolidation impacts performance, by comparing metrics such as elapsed time and CPU time before and after the consolidation.
References:
* Oracle Database SQL Tuning Guide, 19c
* Oracle Database Performance Tuning Guide, 19c

NEW QUESTION # 34
......

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