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NEW QUESTION # 13
The CURS0R_SHARING and OPTIMIZER_CAPTURE_SQL_PLAN_BASELINES parameters are set to default. The top five wait events in an awr report are due to a large number of hard parses because of several almost identical SQL statements.
Which two actions could reduce the number of hard parses?
Answer: A,E
Explanation:
To reduce the number of hard parses due to several almost identical SQL statements, you can take the following actions:
* C (Correct): Increasing the size of the library cache can help reduce hard parses by providing more memory to store more execution plans. This allows SQL statements to be shared more effectively.
* E (Correct): Setting the CURSOR_SHARING parameter to FORCE will cause Oracle to replace literals in SQL statements with bind variables, which can significantly reduce the number of hard parses by making it more likely that similar SQL statements will share the same execution plan.
The other options do not directly impact the number of hard parses:
* A (Incorrect): Creating the KEEP cache and caching tables accessed by the SQL statements can improve performance for those tables, but it does not directly reduce the number of hard parses.
* B (Incorrect): Creating the RECYCLE cache and caching tables accessed by the SQL statements can make it more likely that objects will be removed from the cache quickly, which does not help with hard parse issues.
* D (Incorrect): Setting OPTIMIZER_CAPTURE_SQL_PLAN_BASELINES to TRUE can help stabilize SQL execution plans but will not reduce the number of hard parses. This parameter is used to automatically capture SQL plan baselines for repeatable SQL statements, which can prevent performance regressions due to plan changes.
References:
* Oracle Database Performance Tuning Guide: Minimizing Hard Parses
* Oracle Database SQL Tuning Guide: CURSOR_SHARING
NEW QUESTION # 14
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?
Answer: B
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 # 15
Examine this statement and output:
Which two situations can trigger this error?
Answer: B,C
Explanation:
The ORA-15505 error indicates that the instance encountered errors while trying to access the specified directory. This could be due to:
A: Insufficient privileges: The user attempting to start the workload capture might not have the required permissions to execute the DBMS_WORKLOAD_CAPTURE package or to read/write to the directory specified.
E: Accessibility: The database instance may not be able to access the directory due to issues such as incorrect directory path, directory does not exist, permission issues at the OS level, or the directory being on a file system that's not accessible to the database instance.
References:
* Oracle Database Error Messages, 19c
* Oracle Database Administrator's Guide, 19c
NEW QUESTION # 16
Which two types of performance problems are reported by ADDM for PDBS?
Answer: A,C
Explanation:
The Automatic Database Diagnostic Monitor (ADDM) analyzes and reports on various types of performance problems. For Pluggable Databases (PDBs), it can identify issues such as I/O capacity limits which may hinder the overall performance by causing bottlenecks. Additionally, ADDM can report on user I/O waits, which can indicate performance issues related to the time it takes for user queries to read data from the disk.
References:
* Oracle Multitenant Administrator's Guide, 19c
* Oracle Database Performance Tuning Guide, 19c
NEW QUESTION # 17
Which Optimizer component helps decide whether to use a nested loop join or a hash join in an adaptive execution plan?
Answer: E
Explanation:
In an adaptive execution plan, the Optimizer makes runtime decisions between nested loop and hash joins using a statistics collector. The collector is a row source that collects statistics about the rows it processes and can adapt the plan based on the number of rows processed.
References:
* Oracle Database SQL Tuning Guide, 19c
NEW QUESTION # 18
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