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1z1-084์ ์ค์จ๋์๋คํ & 1z1-084์ต์ ์ ๋ฐ์ดํธ๋คํ์๋ฃ
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์ต์ Oracle Database 19c 1z1-084 ๋ฌด๋ฃ์ํ๋ฌธ์ (Q41-Q46):
์ง๋ฌธ # 41
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 value of DBWRITERPROCESSES to 64,
- B. increasing the value of DB_FILE_MULTIBLOCK_READ_COUNT to 128
- C. Increasing the size of MEMORYTARGET
- D. setting dbwr_io_slaves to 64
- E. reducing the values of DB_FILE_MULTILOCK_READ_COUNT to 64
์ ๋ต๏ผA,D
์ค๋ช
๏ผ
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
ย
์ง๋ฌธ # 42
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?
- A. Create the KEEP cache and cache tables accessed by the SQL statements.
- B. Set OPTIMIZER_CAPTURE_SQL_PLAN_BASELINES to TRUE.
- C. Set the CURSOR_SHARING parameter to FORCE.
- D. Increase the size of the library cache.
- E. Create the RECYCLE cache and cache tables accessed by the SQL statements.
์ ๋ต๏ผC,D
์ค๋ช
๏ผ
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
ย
์ง๋ฌธ # 43
Database performance has degraded recently.
index range scan operations on index ix_sales_time_id are slower due to an increase in buffer gets on sales table blocks.
Examine these attributes displayed by querying DBA_TABLES:
Now, examine these attributes displayed by querying DBA_INDEXES:
Which action will reduce the excessive buffer gets?
- A. Re-create the SALES table sorted in order of index IX_SALES_TIME_ID.
- B. Re-create index IX_SALES_TIME_ID using ADVANCED COMPRESSION.
- C. Re-create the SALES table using the columns in IX_SALES_TIME_ID as the hash partitioning key.
- D. Partition index IX_SALES_TIME_ID using hash partitioning.
์ ๋ต๏ผB
์ค๋ช
๏ผ
Given that index range scan operations onIX_SALES_TIME_IDare slower due to an increase in buffer gets, the aim is to improve the efficiency of the index access. In this scenario:
* B (Correct):Re-creating the index usingADVANCED COMPRESSIONcan reduce the size of the index, which can lead to fewer physical reads (reduced I/O) and buffer gets when the index is accessed, as more of the index can fit into memory.
The other options would not be appropriate because:
* A (Incorrect):Re-creating theSALEStable sorted in order of the index might not address the issue of excessive buffer gets. Sorting the table would not improve the efficiency of the index itself.
* C (Incorrect):Using the columns inIX_SALES_TIME_IDas a hash partitioning key for theSALES table is more relevant to data distribution and does not necessarily improve index scan performance.
* D (Incorrect):Hash partitioning the index is generally used to improve the scan performance in a parallel query environment, but it may not reduce the number of buffer gets in a single-threaded query environment.
References:
* Oracle Database SQL Tuning Guide:Managing Indexes
* Oracle Database SQL Tuning Guide:Index Compression
ย
์ง๋ฌธ # 44
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 improves performance for queries joining several tables using bloom filter joins.
- C. It does not improve performance for queries using user-defined virtual column results.
- D. It does not improve performance for queries using cached results of function evaluations on columns from the same table.
- E. It does not require all database data to fit in memory to improve query performance.
- F. It can improve OLTP workload performance by avoiding the use of indexes.
์ ๋ต๏ผB,E,F
์ค๋ช
๏ผ
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
ย
์ง๋ฌธ # 45
Examine these commands, which execute successfully:
Which statement is true?
- A. ADDM, AWR, and ASH reports can be purged automatically.
- B. AWR snapshots can be purged manually in pluggable databases.
- C. AD DM is enabled for all pluggable databases.
- D. AWR- snapshots in all pluggable databases will be purgedautomatically after every 60 mins.
์ ๋ต๏ผB
์ค๋ช
๏ผ
TheDBMS_WORKLOAD_REPOSITORY.MODIFY_SNAPSHOT_SETTINGSprocedure allows setting attributes related to AWR snapshots. While the interval setting controls the frequency of snapshot generation, purging them is a separate process that can be managed either automatically (with retention settings) or manually.References:
* Oracle Database PL/SQL Packages and Types Reference, 19c
* Oracle Multitenant Administrator's Guide, 19c
ย
์ง๋ฌธ # 46
......
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