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Oracle Database 19c Performance and Tuning Management Sample Questions (Q53-Q58):

NEW QUESTION # 53
Which three statements are true about using the in Memory (IM) column store?

A. It does not require all database data to fit in memory to improve query performance.
B. It improves performance for queries joining several tables using bloom filter joins.
C. It does not improve performance for queries using user-defined virtual column results.
D. It does not improve performance for queries using cached results of function evaluations on columns from the same table.
E. It can improve OLTP workload performance by avoiding the use of indexes.
F. It does not improve performance for queries that use join groups on columns from different tables.

Answer: A,B,E

Explanation:
The Oracle In-Memory (IM) column store feature enhances the performance of databases by providing a fast columnar storage format for analytical workloads while also potentially benefiting OLTP workloads.
* C (True):It can improve OLTP workload performance by providing a faster access path for full table scans and reducing the need for indexes in certain scenarios, as the In-Memory store allows for efficient in-memory scans.
* E (True):The In-Memory column store does not require all database data to fit in memory. It can be used selectively for performance-critical tables or partitions, and Oracle Database will manage the population and eviction of data as needed.
* F (True):In-Memory column store can significantly improve performance for queries joining several tables, especially when bloom filters are used, as they are highly efficient with the columnar format for large scans and join processing.
The other options provided are not correct in the context of the In-Memory column store:
* A (False):While In-Memory column store is designed for analytical queries rather than caching results of function evaluations, it does not specifically avoid improving performance for queries using cached results of function evaluations.
* B (False):In-Memory column store can improve the performance of queries that use join groups, which can be used to optimize joins on columns from different tables.
* D (False):In-Memory column store can improve the performance of queries using expressions, including user-defined virtual columns, because it supports expression statistics which help in
* optimizing such queries.
References:
* Oracle Database In-Memory Guide:In-Memory Column Store in Oracle Database
* Oracle Database In-Memory Guide:In-Memory Joins
* Oracle Database In-Memory Guide:In-Memory Aggregation

NEW QUESTION # 54
Which two Oracle Database features use database services?

A. Oracle SQL Tuning Advisor
B. Oracle SQL Performance Management
C. Oracle Scheduler
D. Database Resource Manager
E. Oracle Automatic Reoptimization

Answer: C,D

Explanation:
Database services in Oracle are used to manage how resources are allocated and how workloads are managed within the database. The features that use database services are:
* B (Correct):Database Resource Manager (DBRM) uses services to control resource allocation to different workloads. It ensures that resources are assigned to the most critical tasks first, based on the service associated with the workload.
* E (Correct):Oracle Scheduler can also utilize database services. Jobs in Oracle Scheduler can be assigned to different services to control resource allocation and prioritization.
The other features mentioned are related to SQL performance but do not directly utilize database services in the way Resource Manager and Scheduler do:
* A:Oracle Automatic Reoptimization is a feature that allows the database to automatically improve the execution plan of a SQL statement after it is executed, based on the actual performance metrics, but it does not directly use database services.
* C:Oracle SQL Performance Management involves various components of SQL tuning and monitoring, but it does not use database services to operate.
* D:Oracle SQL Tuning Advisor provides advice on how to tune SQL queries for better performance.
While it can be used in conjunction with services for managing and analyzing workloads, it doesn't use services in its core functionality.
References:
* Oracle Database Administrator's Guide:Administering Services
* Oracle Database Administrator's Guide:Managing Resources with Oracle Database Resource Manager
* Oracle Database Scheduler Developer's Guide:Using the Scheduler

NEW QUESTION # 55
Which two types of performance problems are reported by ADDM for PDBS?

A. SGA sizing issues
B. Excessive checkpoint writes
C. I/O capacity limits
D. User I/O waits
E. Top SQL statements

Answer: C,E

Explanation:
ADDM (Automatic Database Diagnostic Monitor) is a key Oracle diagnostic tool that analyzes performance data captured by AWR (Automatic Workload Repository) and provides insights into performance issues. In a PDB (Pluggable Database), ADDM can provide recommendations for various types of performance issues.
Why A. I/O capacity limits is correct:
* ADDM evaluates the performance of a database and identifies I/O bottlenecks that could be impacting query performance.
* I/O capacity limits occur when the database cannot handle the I/O workload effectively, which could be due to disk contention, inadequate I/O throughput, or hardware limitations.
* ADDM reports such issues and suggests remedies like tuning SQL queries, redistributing I/O workloads, or upgrading storage systems.
Why D. Top SQL statements is correct:
* One of the critical capabilities of ADDM is identifying high-resource-consuming SQL statements (Top SQL) that are impacting database performance.
* For PDBs, ADDM provides specific recommendations to optimize these SQL statements, such as improving execution plans, adding indexes, or rewriting queries.
Why Other Options Are Incorrect:
* B. Excessive checkpoint writes:
* While excessive checkpoint writes can occur, ADDM typically focuses on higher-level performance problems like I/O issues or top SQL rather than specific low-level operational events like checkpointing. Excessive checkpoint writes are not commonly reported directly for PDBs by ADDM.
* C. SGA sizing issues:
* ADDM does not directly analyze or provide recommendations for SGA (System Global Area) sizing issues at the PDB level because SGA is managed at the CDB (Container Database) level.
PDBs share the SGA of the CDB.
* E. User I/O waits:
* While user I/O waits are captured in performance metrics, ADDM typically groups them under broader issues like I/O capacity limits. It does not specifically report on "user I/O waits" as a standalone problem.
Key Features of ADDM for PDBs:
* Identifying Top SQL Statements impacting performance.
* Reporting I/O issues, including capacity limits and contention.
* Highlighting inter-PDB resource contention within the same CDB.
References to Oracle Documentation:
* Oracle Database 19c Performance Tuning Guide:
* Section: Using ADDM for Pluggable Databases.
* Details the types of performance issues ADDM reports for PDBs.
* Automatic Database Diagnostic Monitor (ADDM) Concepts:
* Highlights ADDM's ability to analyze I/O, SQL performance, and resource utilization.

NEW QUESTION # 56
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. GGREGATE_TARGET should be set to at least 700 MB.
C. PGAA_AGGREGATE should be set to at least 800 MB.
D. With a target of 800 MB or more, all one-pass execution work areas would be eliminated.

Answer: D

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 # 57
A database instance is suffering poor I/O performance on two frequently accessed large tables.
No Big Table caching occurs in the database.
Examine these parameter settings:

Which are two actions either one of which will allow Big Table caching to occur?

A. Increasing DB_CACHESIZE to 1 G
B. Setting DB_KEEP_CACHE_SIZE to at least 50M
C. Increasing DB_BIG_TABLE_CACHE_PERCENT_TARGET to at least 25
D. Setting PARALLEL_DEGREE_POLICYAUTO
E. Increasing DB_BIG_TABLE_CACHE_PERCENT_TARGET to at least 50
F. Setting PARALLEL_DEGREE_POLICYADAPTIVE

Answer: A,C

Explanation:
Big Table caching is a feature that allows frequently accessed large tables to be cached in memory to improve I/O performance. From the parameter settings provided, Big Table caching is not occurring because DB_BIG_TABLE_CACHE_PERCENT_TARGET is set to 10, which is the minimum threshold for enabling the feature, but the size of the cache is too small for the big tables to be effectively cached.
To enable Big Table caching, one of the following actions could be taken:
* C (Correct): Increasing DB_BIG_TABLE_CACHE_PERCENT_TARGET to at least 25. This action would allocate a larger percentage of the buffer cache for storing big tables, which could allow for caching large tables and thus improve I/O performance.
* D (Correct): Increasing DB_CACHE_SIZE to 1G. Since the size of the buffer cache is a determining factor for how much data can be cached, increasing this parameter would provide more memory space for big tables to be cached.
Options A, B, E, and F will not enable Big Table caching because:
* A: Increasing DB_BIG_TABLE_CACHE_PERCENT_TARGET to 50 without adjusting the overall size of the cache might still not be sufficient if the DB_CACHE_SIZE is not large enough to hold the big tables.
* B: Setting DB_KEEP_CACHE_SIZE to at least 50M only specifies a separate buffer pool for objects with the KEEP cache attribute and does not affect Big Table caching.
* E: and F: Changing the PARALLEL_DEGREE_POLICY to ADAPTIVE or AUTO influences the behavior of parallel execution but does not directly enable or influence Big Table caching.
References:
* Oracle Database Performance Tuning Guide: Big Table Caching
* Oracle Database Reference: DB_BIG_TABLE_CACHE_PERCENT_TARGET
* Oracle Database Reference: DB_CACHE_SIZE

NEW QUESTION # 58
......

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