Pass the Oracle Oracle Database 19c 1z0-084 Questions and answers with CertsForce

Regarding space usage in temporary tablespaces, the following statements are true:

A (Correct): When a global temporary table or a sort operation exceeds the available memory, Oracle Database allocates space in a temporary tablespace to store the temporary data or intermediate results.

E (Correct): Using temporary tablespace groups can prevent insufficient temporary tablespace for sort operations by providing a collective pool of space from multiple temporary tablespaces, which can be used for user sorting operations.

The other options provided have inaccuracies:

B (Incorrect): Oracle does not provide a mechanism for setting quotas on temporary tablespaces. Quotas can be set for permanent tablespaces but not for temporary ones.

C (Incorrect): A sort operation may fail due to insufficient space, but Oracle will attempt to allocate space in the temporary tablespace dynamically. If no space can be allocated, an error is returned rather than a sort failure.

D (Incorrect): If a session consumes all available temporary tablespace storage, Oracle will not hang the session; it will return an error to the session indicating that it has run out of temporary space.

References:

Oracle Database Administrator's Guide: Managing Space for Schema Objects

Oracle Database Concepts: Temporary Tablespaces

To investigate the cause of the ORA-04036 error, which indicates that PGA memory usage exceeds the PGA_AGGREGATE_LIMIT, the appropriate views to consult are DBA_HIST_ACTIVE_SESS_HISTORY and DBA_HIST_PROCESS_MEM_SUMMARY.

DBA_HIST_ACTIVE_SESS_HISTORY: This view provides historical information about active sessions in the database. It includes details about the SQL executed, the execution context, and the resources consumed by each session. By examining this view, you can identify the specific sessions and SQL queries that were active and potentially consuming excessive PGA memory around the time the ORA-04036 error occurred.

DBA_HIST_PROCESS_MEM_SUMMARY: This view contains historical summaries of memory usage by processes. It can help in identifying the processes that were consuming a significant amount of PGA memory, leading to the ORA-04036 error. This view provides aggregated memory usage information over time, making it easier to pinpoint the processes responsible for high PGA memory consumption.

Together, these views offer a comprehensive overview of the memory usage patterns and specific queries or processes that might have contributed to exceeding the PGA_AGGREGATE_LIMIT, resulting in the ORA-04036 error.

References:

Oracle Database Reference: DBA_HIST_ACTIVE_SESS_HISTORY

Oracle Database Reference: DBA_HIST_PROCESS_MEM_SUMMARY

Oracle Database Performance Tuning Guide: Managing Memory

The cursor: pin S wait on X wait event suggests contention for a cursor pin, which is associated with mutexes (a type of locking mechanism) that protect the library cache to prevent concurrent modifications. This issue can often be alleviated by deferring the invalidation of cursors until the end of the call to reduce contention. The correct command to use would be:

C (Correct): ALTER SYSTEM SET CURSOR_INVALIDATION=DEFERRED; This setting defers the invalidation of dependent cursors until the end of the PL/SQL call, which can reduce the cursor: pin S wait on X wait events.

The other options are incorrect in addressing this issue:

A (Incorrect): Setting CURSOR_SHARING to FORCE makes the optimizer replace literal values with bind variables. It doesn't address the contention for cursor pins directly.

B (Incorrect): CURSOR_SPACE_FOR_TIME=TRUE aims to reduce the parsing effort by keeping cursors for prepared statements open. It may increase memory usage but does not directly resolve cursor: pin S wait on X waits.

D (Incorrect): Increasing SESSION_CACHED_CURSORS caches more session cursors but doesn't necessarily prevent the contention indicated by the cursor: pin S wait on X wait events.

References:

Oracle Database Reference: CURSOR_INVALIDATION

Oracle Database Performance Tuning Guide: Reducing Cursor Invalidation

For a Standard Edition production database, the Statspack tool is available to diagnose performance problems. The Automatic Workload Repository (AWR) and its related tools like AWR Compare Periods report and SQL Performance Analyzer are features of the Oracle Database Enterprise Edition and are not available in Standard Edition. Database Replay is also a feature of the Enterprise Edition. Statspack is a performance diagnostic tool provided for earlier versions and Standard Editions of the Oracle Database to collect, store, and analyze performance data.

References

Oracle Database 19c Administrator’s Guide - Using Statspack to Diagnose Database Performance Issues

Statspack is a performance diagnostic tool provided by Oracle prior to the introduction of the Automatic Workload Repository (AWR). At snap level 6, Statspack captures the following types of statistics:

A (Correct): Parent and child latches are captured. Latch statistics provide information about contention for latches, which are low-level serialization mechanisms used by Oracle.

E (Correct): Enqueue statistics, which provide information on the waits for locks that manage the concurrency between users.

F (Correct): Segment-level statistics, which provide detailed information on database segments such as tables, indexes, etc., to identify I/O and contention issues.

C (Incorrect): While optimizer execution plans are an essential aspect of performance tuning, detailed execution plan capture is not part of the Statspack report at level 6.

D (Incorrect): Plan usage data refers to how frequently a plan is being used, which is more associated with AWR and not typically captured in Statspack reports.

References:

Oracle Database Performance Tuning Guide: Using Statspack

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.

References:

Oracle Database SQL Tuning Guide: Managing Optimizer Statistics

Oracle Database SQL Tuning Guide: Using Indexes and Clusters

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

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 the DBWR_IO_SLAVES parameter 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 of DBWRITERPROCESSES enables 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

The Oracle Optimizer statistics advisor, which is part of the automated tasks framework, can be disabled using the DBMS_AUTO_TASK_ADMIN package. This will prevent it from running and thus reduce space usage in the SYSAUX tablespace.References:

Oracle Database PL/SQL Packages and Types Reference, 19c

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