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Candidates who pass the Oracle 1Z0-084 Exam will earn the Oracle Certified Professional, Oracle Database 19c Performance and Tuning Management certification. Oracle Database 19c Performance and Tuning Management certification validates the candidates’ expertise in database performance management and tuning, and demonstrates their ability to optimize the performance of Oracle Database 19c. Oracle Database 19c Performance and Tuning Management certification is recognized globally, and can improve the candidate’s career prospects by demonstrating their proficiency in performance tuning and management.

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Oracle Database 19c Performance and Tuning Management Sample Questions (Q17-Q22):

NEW QUESTION # 17
A database supporting a mixed workload is hosted on a server with 64 CPUs.
A large number of free buffer waits and buffer busy waits occur affecting performance.
The buffer cache size was then increased but after a few hours, the same wait events occur more often than before the change.
Examine these parameter settings:

Which two actions can help reduce the number of these waits7

  • A. increasing the value of DBWRITERPROCESSES to 64,
  • B. Increasing the size of MEMORYTARGET
  • C. reducing the values of DB_FILE_MULTILOCK_READ_COUNT to 64
  • D. increasing the value of DB_FILE_MULTIBLOCK_READ_COUNT to 128
  • E. setting dbwr_io_slaves to 64

Answer: A,E

Explanation:
Given a server with 64 CPUs, if the buffer cache size increase did not alleviate free buffer waits and buffer busy waits, one can look into optimizing I/O and the efficiency of the DB writer processes.
C: Setting theDBWR_IO_SLAVESparameter to a non-zero value, such as the number of CPUs, would initiate I/O slave processes to assist the DB writer process. This can help reduce I/O contention when writing from the buffer cache to disk, particularly for systems without asynchronous I/O capabilities.
D: Increasing the value ofDBWRITERPROCESSESenables multiple DB writer processes to be active simultaneously. In a system with many CPUs, such as 64, increasing this value can improve the write throughput to disk and potentially reduce buffer busy waits.
References:
* Oracle Database Reference, 19c
* Oracle Database Performance Tuning Guide, 19c


NEW QUESTION # 18
You want to reduce the amount of db file scattered read that is generated in the database. You execute the SQL Tuning Advisor against the relevant workload. Which two can be part of the expected result?

  • A. recommendations regarding the creation of SQL Patches
  • B. recommendations regarding the creation of additional indexes
  • C. recommendations regarding rewriting the SQL statements
  • D. recommendations regarding the creation of materialized views
  • E. recommendations regarding partitioning the tables

Answer: B,C

Explanation:
https://docs.oracle.com/en/database/oracle/oracle-database/21/tgsql/sql-tuning-advisor.html#GUID-
8E1A39CB-A491-4254-8B31-9B1DF7B52AA1
The goal is to reduce the db file scattered read waits, which are associated with full table scans. These are I
/O operations where Oracle retrieves data blocks scattered across the disk, typically when large amounts of data are read inefficiently. Running the SQL Tuning Advisor analyzes the workload and provides tuning recommendations. Let's evaluate the options.
Why A. Recommendations regarding the creation of additional indexes is correct:
* Full table scans (which cause db file scattered read) often occur because suitable indexes are missing.
* The SQL Tuning Advisor can identify queries that would benefit from indexes and recommend creating them. Indexes allow the database to access data more efficiently using row lookups, reducing the need for full table scans.
Why B. Recommendations regarding rewriting the SQL statements is correct:
* Sometimes, poorly written SQL statements cause inefficient execution plans that lead to db file scattered read.
* SQL Tuning Advisor can recommend SQL rewrites to make better use of indexes, avoid full table scans, or optimize joins. For example:
* Rewriting predicates to use indexed columns.
* Using hints to guide the optimizer.
Why Other Options Are Incorrect:
* C. Recommendations regarding the creation of materialized views:
* Materialized views are typically recommended to optimize complex queries involving aggregations or joins, not to address db file scattered read directly. They are less relevant for solving I/O issues caused by full table scans in this context.
* D. Recommendations regarding the creation of SQL Patches:
* SQL Patches are used to influence the execution plan for specific SQL statements. While SQL Patches can potentially fix performance issues, the SQL Tuning Advisor focuses on improving SQL and database design rather than patching queries.
* E. Recommendations regarding partitioning the tables:
* Partitioning tables can improve query performance, especially for very large datasets. However, this is a database design-level recommendation and is not typically provided by SQL Tuning Advisor. Partitioning would not directly target db file scattered read.
How SQL Tuning Advisor Helps:
The SQL Tuning Advisor provides actionable recommendations, such as:
* Creating indexes to reduce full table scans.
* Rewriting SQL to optimize the execution plan.
* Improving statistics to help the optimizer make better decisions.
References to Oracle Documentation:
* Oracle Database 19c Performance Tuning Guide:
* Section: Using SQL Tuning Advisor to Optimize Workloads.
* Explains recommendations for indexes and SQL rewrites to reduce I/O.
* Understanding Wait Events:
* Details about db file scattered read and how to address it.


NEW QUESTION # 19
Accessing the SALES tables causes excessive db file sequential read wait events.
Examine this AWR except:

Now, examine these attributes displayed by querying dba_tables:

Finally, examine these parameter settings:

Which two must both be used to reduce these excessive waits?

  • A. Increase PCTFREE for the SALES table.
  • B. Compress the SALES table.
  • C. Coalesce all sales table indexes.
  • D. Re-create the SALES table.
  • E. Partition the SALES table.

Answer: B,E

Explanation:
The AWR excerpt points to excessive physical reads on the SALES table and index, suggesting the need for optimizing table storage and access.
Partitioning the SALES table (A) can reduce 'db file sequential read' waits by breaking down the large SALES table into smaller, more manageable pieces. This can localize the data and reduce the I/O necessary for query operations.
Compressing the SALES table (D) can also help reduce I/O by minimizing the amount of data that needs to be read from disk. This can also improve cache utilization and reduce the 'db file sequential read' waits.
References:
* Oracle Database VLDB and Partitioning Guide, 19c
* Oracle Database Administrator's Guide, 19c
These changes are recommended based on Oracle's best practices for managing large tables and reducing I/O waits, ensuring better performance and efficiency.


NEW QUESTION # 20
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_BIG_TABLE_CACHE_PERCENT_TARGET to at least 25
  • B. Setting DB_KEEP_CACHE_SIZE to at least 50M
  • C. Setting PARALLEL_DEGREE_POLICYADAPTIVE
  • D. Increasing DB_BIG_TABLE_CACHE_PERCENT_TARGET to at least 50
  • E. Increasing DB_CACHESIZE to 1 G
  • F. Setting PARALLEL_DEGREE_POLICYAUTO

Answer: A,E

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 # 21
You need to transport performance data from a Standard Edition to an Enterprise Edition database. What is the recommended method to do this?

  • A. Export the data by using the exp utility and parameter file spuexp.par from the Statspack repository and import it by using imp into a dedicated Statspack schema on the destination.
  • B. Export the data by using the expdp utility and parameter file spuexp.par from the Statspack repository and import it by using impdp into Export the data by using expdp from the Statspack repository and import it by using impdp into the AWR repository.
  • C. Export the data by using expdp from Statspack and import it by using $ORACLE_HOME/rdbms/admin
    /awrload into the AWR repository.
  • D. Export the data by using expdp from the ftatspack repository and import it by using impdp into the AWR repository.

Answer: A

Explanation:
To transport performance data from an Oracle Database Standard Edition, which uses Statspack, to an Enterprise Edition database, which uses AWR, you must consider the compatibility of data structures and repository schemas between these tools. The recommended method is:
* D (Correct): Export the data using the exp utility with a parameter file appropriate for Statspack (like spuexp.par) from the Statspack repository and import it into a dedicated Statspack schema on the destination. Since Statspack and AWR use different schemas, it's not recommended to import Statspack data directly into the AWR repository.
The other options are incorrect because:
* A (Incorrect): expdp is not designed to export from Statspack, and awrload is intended for loading from an AWR export file, not a Statspack export.
* B (Incorrect): Although expdp and impdp are used for exporting and importing data, the AWR repository schema is different from the Statspack schema, so importing Statspack data directly into the AWR repository is not recommended.
* C (Incorrect): Using expdp to export from Statspack and then importing directly into the AWR repository is not the correct approach due to the schema differences between Statspack and AWR.
References:
* Oracle Database Performance Tuning Guide: Migrating from Statspack to AWR


NEW QUESTION # 22
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