Most Recent Oracle 1Z0-084 Exam Dumps

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.

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.

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.

Reference

Oracle Database 19c Documentation on Database Smart Flash Cache

Oracle Support Articles and Community Discussions on DB_FLASH_CACHE_SIZE Configuration

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.

Oracle Database SQL Tuning Guide, 19c

Oracle Database Performance Tuning Guide, 19c

The optimizer_adaptive_statistics parameter, when set to TRUE, enables the optimizer to use adaptive statistics, such as SQL Plan Directives, to help improve plans by automatically adjusting them based on the actual execution statistics.

Oracle Database SQL Tuning Guide, 19c

In this scenario, creating an index and generating frequency histograms are two methods that can potentially improve performance:

A (Correct): Generating frequency histograms on the CITY_ID column can help the optimizer make better decisions regarding the execution plan, especially if the data distribution is skewed. Histograms provide the optimizer with more detailed information about the data distribution in a column, which is particularly useful for columns with non-uniform distributions.

B (Correct): Creating an index on the CITY_ID column would speed up queries that filter on this column, especially if it's used frequently in the WHERE clause as a filter. An index would allow for an index range scan instead of a full table scan, reducing the I/O and time needed to execute such queries.

C (Incorrect): While SQL profiles can be used to improve the performance of specific SQL statements, they are usually not the first choice for such a problem, and creating a profile does not replace the need for proper indexing or statistics.

D (Incorrect): Forcing the subquery to use dynamic sampling might not provide a consistent performance benefit, especially if the table statistics are not representative or are outdated. However, dynamic sampling is not as effective as having accurate statistics and a well-chosen index.

E (Incorrect): Adaptive plans can adjust the execution strategy based on the conditions at runtime. While they can be useful in certain scenarios, in this case, creating an index and ensuring accurate statistics would likely provide a more significant performance improvement.

Oracle Database SQL Tuning Guide: Managing Optimizer Statistics

Oracle Database SQL Tuning Guide: Using Indexes and Clusters