NEW 1Z1-084 PREPARATION | VALID 1Z1-084: ORACLE DATABASE 19C PERFORMANCE AND TUNING MANAGEMENT 100% PASS

New 1z1-084 Preparation | Valid 1z1-084: Oracle Database 19c Performance and Tuning Management 100% Pass

New 1z1-084 Preparation | Valid 1z1-084: Oracle Database 19c Performance and Tuning Management 100% Pass

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Oracle Database 19c Performance and Tuning Management Sample Questions (Q10-Q15):

NEW QUESTION # 10
Which application lifecycle phase could be managed reactively?

  • A. Deployment
  • B. Design and development
  • C. Production
  • D. Testing
  • E. Upgrade or migration

Answer: C

Explanation:
The production phase of the application lifecycle is often managed reactively. While proactive measures and performance tuning are essential, unforeseen issues can arise in production that require immediate attention and resolution. Reactive management involves monitoring performance and responding to issues as they occur, ensuring the application maintains acceptable performance levels for end-users.
References
* Oracle Database 19c Performance Tuning Guide - Reactive Tuning


NEW QUESTION # 11
You manage a 19c database with default optimizer settings.
This statement is used extensively as subquery in the application queries:
SELECT city_id FROM sh2.sales WHERE city_id=:Bl
You notice the performance of these queries is often poor and, therefore, execute:
SELECT city_id,COUNT(*) FROM sh2.sales GROUP BY city_id;
Examine the results:

There is no index on the CITY_ID column.
Which two options improve the performance?

  • A. Generate frequency histograms on the CITY__ID column.
  • B. Force the subquery to use dynamic sampling.
  • C. Create an index on the CITY IP column.
  • D. Activate the adaptive plans.
  • E. Use a SQL Profile to enforce the appropriate plan.

Answer: A,C

Explanation:
In this scenario, creating an index and generating frequency histograms are two methods that can potentially improve performance:
* A (Correct):Generating frequency histograms on theCITY_IDcolumn 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 theCITY_IDcolumn 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


NEW QUESTION # 12
Which three statements are true about using the in Memory (IM) column store?

  • A. It does not improve performance for queries using cached results of function evaluations on columns from the same table.
  • B. It does not improve performance for queries that use join groups on columns from different tables.
  • C. It does not require all database data to fit in memory to improve query performance.
  • D. It improves performance for queries joining several tables using bloom filter joins.
  • E. It does not improve performance for queries using user-defined virtual column results.
  • F. It can improve OLTP workload performance by avoiding the use of indexes.

Answer: C,D,F

Explanation:
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


NEW QUESTION # 13
Examine this statement and its corresponding execution plan:

Which phase introduces the CONCATENATION step?

  • A. SQL Transformation
  • B. SQL Execution
  • C. SQL Row Source Generation
  • D. SQL Semantic Check
  • E. SQL Adaptive Execution

Answer: A

Explanation:
The CONCATENATION step in an execution plan is introduced during the SQL Transformation phase. This phase is part of the optimizer's query transformations which can include various techniques to rewrite the query for more efficient execution. The CONCATENATION operation is used to combine the results of two separate SQL operations, typically when there is an OR condition in the WHERE clause, as seen in the provided query.
References:
* Oracle Database SQL Tuning Guide, 19c
* Oracle Database Concepts, 19c


NEW QUESTION # 14
Which two statements are true about the use and monitoring of Buffer Cache Hit ratios and their value in tuning Database I/O performance?

  • A. The performance of workloads that primarily generate full table scans and fast full index scans are always affected by the cache hit ratio.
  • B. A 60% cache hit ratio can be observed for database instances which have very good I/O performance.
  • C. A 99% cache hit ratio can be observed for database instances which have very poor I/O performance.
  • D. The buffer cache advisory view v$db_cache_advice provides advice on cache hit ratios appropriate for the instance workload.
  • E. Both the RECYCLE and KEEP buffer caches should always have a very high cache hit ratio.

Answer: C,D

Explanation:
A high buffer cache hit ratio typically indicates that the database is effectively using the buffer cache and does not often need to read data from disk. However, this metric alone is not a reliable indicator of the I/O performance of the database for several reasons:
* Full table scans and fast full index scans (A) can bypass the buffer cache by design if the blocks are not deemed reusable shortly, which can impact the cache hit ratio.
* A high cache hit ratio (B) can be misleading if the database performance is poor due to other factors, such as inefficient queries or contention issues.
* The buffer cache advisory (C) is a more valuable tool for understanding the potential impact of different cache sizes on the database's I/O performance. It simulates scenarios with different cache sizes and provides a more targeted recommendation.
* The RECYCLE and KEEP buffer caches (D) are specialized caches designed for certain scenarios.
While high hit ratios can be beneficial, they are not universally required; some workloads might not be significantly impacted by lower hit ratios in these caches.
* A lower cache hit ratio (E) does not necessarily mean poor I/O performance. In some cases, a system with a well-designed storage subsystem and efficient queries might perform well even with a lower cache hit ratio.
References
* Oracle Database 19c Performance Tuning Guide - Buffer Cache Hit Ratio
* Oracle Database 19c Performance Tuning Guide - v$db_cache_advice


NEW QUESTION # 15
......

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