1Z1-084 TEST BOOK | 1Z1-084 DOWNLOAD FREE DUMPS

1z1-084 Test Book | 1z1-084 Download Free Dumps

1z1-084 Test Book | 1z1-084 Download Free Dumps

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2025 1z1-084 Test Book : Oracle Database 19c Performance and Tuning Management Realistic 1z1-084 100% Pass

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Oracle is a globally recognized corporation that is responsible for several innovative IT solutions. Its flagship product, the Oracle database, has revolutionized the way organizations store, manage and retrieve data since its inception. With the latest release of Oracle Database 19c, it is now possible to optimize, manage and enhance the performance of databases with greater ease and effectiveness. One of the emerging areas of knowledge and expertise related to Oracle databases is performance and tuning management, which is now covered by the 1Z0-084 Oracle exam.

Oracle Database 19c Performance and Tuning Management Sample Questions (Q18-Q23):

NEW QUESTION # 18
Multiple sessions are inserting data concurrently into a table that has an LOB column.
At some point in time, one of the sessions cannot find available space in the LOB segment and needs to allocate a new extent.
Which wait event will be raised in the other sessions that need space in the LOB column?

  • A. enq: HW - contention
  • B. enq: TX - allocate ITL entry
  • C. enq: TM - contention
  • D. enq: SQ - contention

Answer: A

Explanation:
When sessions concurrently insert data into a table with an LOB column and one session needs to allocate a new extent because it cannot find available space, the wait event associated with this contention is "enq: HW - contention". The HW stands for High Water Mark which is related to space allocation in the database segment.
When asession needs to allocate a new extent, it may raise this wait event in other sessions that are also attempting to allocate space in the same LOB segment.
References
* Oracle Database 19c Reference Guide - enq: HW - contention


NEW QUESTION # 19
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 size of MEMORYTARGET
  • B. increasing the value of DB_FILE_MULTIBLOCK_READ_COUNT to 128
  • C. increasing the value of DBWRITERPROCESSES to 64,
  • D. reducing the values of DB_FILE_MULTILOCK_READ_COUNT to 64
  • E. setting dbwr_io_slaves to 64

Answer: C,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 # 20
Which two options are part of a Soft Parse operation?

  • A. SQL Row Source Generation
  • B. SQL Optimization
  • C. Syntax Check
  • D. Shared Pool Memory Allocation
  • E. Semantic Check

Answer: C,E

Explanation:
What is a Soft Parse?
A Soft Parse occurs when a SQL statement is already present in the shared SQL area (Shared Pool) of the database. Instead of recreating the execution plan, Oracle reuses the existing plan, making the process much faster and more efficient. This is an essential optimization step in Oracle Database to reduce overhead and improve performance.
Steps Involved in a Soft Parse
* Syntax Check (Step A)
* This is the first step of the parsing process.
* Purpose: Ensures the SQL statement conforms to proper syntax rules defined by the SQL language.
* Example:
SELECT FROM employees;
This query will fail at the Syntax Check step because it doesn't specify any columns to retrieve. Oracle ensures that such malformed queries are identified early.
* Semantic Check (Step E)
* The Semantic Check happens after the Syntax Check if the statement passes the syntax validation.
* Purpose:
* Verify Object Existence: Check if all referenced tables, columns, and other database objects exist. Example:
SELECT salary FROM non_existent_table;
This query will fail because the table non_existent_table does not exist.
* User Privileges: Ensure the user has sufficient permissions to access the objects. Example:
SELECT * FROM employees;
If the user doesn't have SELECT privileges on the employees table, the query will fail.
* Validate Data Types: Ensure that columns used in expressions or comparisons are compatible in terms of data types. Example:
SELECT * FROM employees WHERE hire_date = '01-01-2023';
If hire_date is stored as a DATE type, and the literal is not implicitly convertible, this will fail.
Steps Skipped in a Soft Parse
SQL Row Source Generation (Option B):
This step involves breaking the query into operations (row sources) to fetch data. It is part of execution plan generation, which happens only during a Hard Parse.
SQL Optimization (Option C):
The SQL Optimizer calculates the most efficient execution plan during a hard parse. In a soft parse, the existing plan is reused, so this step is skipped.
Shared Pool Memory Allocation (Option D):
A Hard Parse allocates memory in the shared pool for a new SQL statement. In a soft parse, Oracle reuses the existing shared memory, avoiding additional allocation.
Why Are Syntax Check and Semantic Check the Correct Steps?
These steps are mandatory validations for all SQL statements, even during a soft parse. Without them, Oracle would risk executing invalid or unauthorized SQL statements.
By reusing the execution plan but performing these lightweight checks, Oracle ensures both efficiency and correctness.
References to Oracle Database 19c: Performance Management and Tuning
Oracle Documentation:
Oracle Database 19c Concepts: SQL Parsing and Execution
Oracle Database Performance Tuning Guide: Understanding Hard Parses and Soft Parses Key Features Discussed in the Guide:
Shared Pool and Library Cache: The role of the shared SQL area in reducing parsing overhead.
SQL Execution Workflow: Detailed explanation of syntax and semantic checks.
SQL Optimizer: The differences between hard and soft parsing in relation to the optimizer.
Tools for Analysis:
AWR Reports: Monitor the number of hard vs. soft parses for query performance.
V$SQL: View cached SQL statements and their parsing statistics.


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 expdp from Statspack and import it by using $ORACLE_HOME/rdbms/admin
    /awrload into the AWR repository.
  • B. Export the data by using expdp from the ftatspack repository and import it by using impdp into the AWR repository.
  • C. 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.
  • D. 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.

Answer: D

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

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

Answer: C,D,E

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 # 23
......

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