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Oracle 1Z0-084 Exam is a certification that portrays a professional's skills and knowledge in performance tuning and management of the Oracle Database 19c. A candidature that passes the exam validates their proficiency in managing and tuning the Oracle Database to maximize its efficiency and performance. Oracle Database 19c Performance and Tuning Management certification also enhances the candidate's credibility and job prospects in a highly competitive job market. Oracle Database 19c Performance and Tuning Management certification exam is ideal for professionals seeking to advance their career to higher levels of responsibility in database administration, development, and management roles in enterprises worldwide.

Oracle Database 19c Performance and Tuning Management Sample Questions (Q36-Q41):

NEW QUESTION # 36
Which two types of performance problems are reported by ADDM for PDBS?

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

Answer: B,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 # 37
You must write a statement that returns the ten most recent sales. Examine this statement:

Users complain that the query executes too slowly. Examine the statement's current execution plan:

What must you do to reduce the execution time and why?

  • A. Create an index on SALES.TIME_ID to force the return of rows in the order specified by the ORDER BY clause.
  • B. Enable Adaptive Plans so that Oracle can change the Join method as well as the Join order for this query.
  • C. Create an index on SALES.CUST_ID to force an INDEX RANGE SCAN on this index followed by a NESTED LOOP join between CUSTOMERS and SALES.
  • D. Replace the FETCH FIRST clause with ROWNUM to enable the use of an index on SALES.
  • E. Collect a new set of statistics on PRODUCT, CUSTOMERS, and SALES because the current stats are inaccurate.

Answer: A

Explanation:
The execution plan shows a full table access for the SALES table. To reduce the execution time, creating an index on SALES.TIME_ID would be beneficial as it would allow the database to quickly sort and retrieve the most recent sales without the need to perform a full table scan, which is I/O intensive and slower. By indexing TIME_ID, which is used in the ORDER BY clause, the optimizer can take advantage of the index to efficiently sort and limit the result set to the ten most recent sales.
* B (Incorrect): Replacing FETCH FIRST with ROWNUM would not necessarily improve the performance unless there is an appropriate index that the optimizer can use to avoid sorting the entire result set.
* C (Incorrect): There is no indication that the current statistics are inaccurate; hence, collecting new statistics may not lead to performance improvement.
* D (Incorrect): While adaptive plans can provide performance benefits by allowing the optimizer to adapt the execution strategy, the main issue here is the lack of an index on the ORDER BY column.
* E (Incorrect): Creating an index on SALES.CUST_ID could improve join performance but would not address the performance issue caused by the lack of an index on the ORDER BY column.
References:
* Oracle Database SQL Tuning Guide: Managing Indexes
* Oracle Database SQL Tuning Guide: Using Indexes and Clusters


NEW QUESTION # 38
You must configure and enable Database Smart Flash Cache for a database.
You configure these flash devices:

Examine these parameter settings:

What must be configured so that the database uses these devices for the Database Smart Flash Cache?

  • A. Set DB_FLASH_CACHE_SIZE to 192G and MEMORY_TARGET to 256G.
  • B. Set DB_FLASH_CACHE_SIZE parameter to 128G, 64G.
  • C. Disable Automatic Memory Management and set SGA_TARGET to 256G.
  • D. Set DB_FLASH_CACHE_SIZE to 256G and change device /dev/sdk to 128G.
  • E. Set DB_FLASH_CACHE_SIZE parameter to 192G.

Answer: B

Explanation:
To configure and enable Database Smart Flash Cache, you must set the DB_FLASH_CACHE_SIZE parameter to reflect the combined size of the flash devices you intend to use for the cache. In this scenario, two flash devices are configured: /dev/sdj with 128G and /dev/sdk with 64G.
* Determine the combined size of the flash devices intended for the Database Smart Flash Cache. In this case, it's 128G + 64G = 192G.
* However, Oracle documentation suggests setting DB_FLASH_CACHE_SIZE to the exact sizes of the individual devices, separated by a comma when multiple devices are used.
* Modify the parameter in the database initialization file (init.ora or spfile.ora) or using an ALTER SYSTEM command. Here's the command for altering the system setting:
ALTER SYSTEM SET DB_FLASH_CACHE_SIZE='128G,64G' SCOPE=SPFILE;
* Since this is a static parameter, a database restart is required for the changes to take effect.
* Upon database startup, it will allocate the Database Smart Flash Cache using the provided sizes for the specified devices.
It is important to note that MEMORY_TARGET and MEMORY_MAX_TARGET parameters should be configured independently of DB_FLASH_CACHE_SIZE. They control the Oracle memory management for the SGA and PGA, and do not directly correlate with the flash cache configuration.
References
* Oracle Database 19c Documentation on Database Smart Flash Cache
* Oracle Support Articles and Community Discussions on DB_FLASH_CACHE_SIZE Configuration


NEW QUESTION # 39
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 the SALES table using the columns in IX_SALES_TIME_ID as the hash partitioning key.
  • B. Re-create the SALES table sorted in order of index IX_SALES_TIME_ID.
  • C. Re-create index IX_SALES_TIME_ID using ADVANCED COMPRESSION.
  • D. Partition index IX_SALES_TIME_ID using hash partitioning.

Answer: C

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 # 40
Examine this AWR report excerpt:

You must reduce the impact of database I/O, without increasing buffer cache size and without modifying the SQL statements.
Which compression option satisfies this requirement?

  • A. ROW STORE COMPRESS ADVANCED
  • B. MN STORE COMPRESS FOR QUERY LOW
  • C. COLUMN STORE COMPRESS FOR QUERY HIGH
  • D. STORE COMPRESS

Answer: C

Explanation:
The question asks to reduce database I/O impact without increasing the buffer cache size or modifying SQL statements. This indicates a need to reduce the physical I/O required to access the data. Let's analyze the scenario and the options.
Analysis of the AWR Report:
* Top Wait Events:
* The top foreground wait event is db file sequential read, which accounts for 40.4% of DB time.
This indicates significant physical I/O operations, primarily single-block reads, which are typically associated with index access.
* Reducing the physical I/O associated with db file sequential read can significantly improve performance.
* SQL Ordered by Reads:
* The SQL consuming the most reads involves high physical I/O. This confirms the need to reduce I
/O overhead by compressing data efficiently to minimize physical reads.
Compression Techniques and Their Suitability:
* A. COLUMN STORE COMPRESS FOR QUERY LOW:
* This option is a columnar compression method that optimizes for query performance but provides less compression compared to the HIGH option. While effective, it is not as suitable as FOR QUERY HIGH for reducing I/O.
* B. STORE COMPRESS:
* This is the basic compression option for tables and does not offer the advanced capabilities required for reducing significant physical I/O for queries.
* C. ROW STORE COMPRESS ADVANCED:
* This is a row-level compression that is suitable for OLTP workloads. While it reduces storage, it does not reduce query-related I/O as effectively as columnar compression.
* D. COLUMN STORE COMPRESS FOR QUERY HIGH (Correct Option):
* This is the most effective option for reducing query-related I/O. It:
* Uses columnar compression to reduce the size of data stored on disk.
* Reduces the number of physical reads by compressing data highly, meaning fewer blocks need to be read.
* Optimizes query performance for analytical workloads, which aligns with the scenario described in the AWR report.
Why COLUMN STORE COMPRESS FOR QUERY HIGH Is the Best Fit:
* It is designed to improve query performance by minimizing the amount of I/O required.
* Suitable for environments with heavy read operations (as indicated by the db file sequential read waits).
* Does not require changes to SQL or buffer cache size, adhering to the constraints in the question.
Reference to Oracle Documentation:
* Oracle Database 19c Performance Tuning Guide:
* Section: Using Compression to Reduce Storage and I/O Requirements.
* Discussion of columnar compression techniques for reducing I/O in query-intensive environments.
* Oracle Advanced Compression Documentation:
* Details on COLUMN STORE COMPRESS FOR QUERY HIGH and its benefits for analytical workloads.


NEW QUESTION # 41
......

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