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NEW QUESTION: 1
Your multitenant container database (CDB) cdb1 that is running in archivelog mode contains two pluggable databases (PDBs), pdb2_1 and pdb2_2, both of which are open. RMAN is connected to the target pluggable database pdb2_1.
RMAN> BACKUP DATABASE PLUS ARCHIVELOG DELETE INPUT;
Which statement is true about the execution of this command to back up the database?
A. All data files belonging to pdb2_1 are backed up and all archive log files are deleted.
B. All data files belonging to pdb2_1 are backed up along with the archive log files.
C. This command gives an error because archive log files can be backed up only when RMAN is connected to the root database.
D. Only the data files belonging to pdb2_ are backed up.
Answer: B
NEW QUESTION: 2
Which three statements are true about adaptive SQL plan management? (Choose three.)
A. The non-accepted plans are automatically accepted and become usable by the optimizer if they perform better than the existing accepted plans.
B. The non-accepted plans in a SQL plan baseline are automatically evolved, in COMPREHENSIVE mode, during the nightly maintenance window and a persistent verification report is generated.
C. It automatically performs verification or evolves non-accepted plans, in COMPREHENSIVE mode when they perform better than existing accepted plans.
D. It adds new, bettor plans automatically as fixed plans to the baseline.
E. The optimizer always uses the fixed plan, if the fixed plan exists in the plan baseline.
Answer: A,B,C
Explanation:
Explanation
With adaptive SQL plan management, DBAs no longer have to manually run the verification or evolve process for non-accepted plans. When automatic SQL tuning is in COMPREHENSIVE mode, it runs a verification or evolve process for all SQL statements that have non-accepted plans during the nightly maintenance window. If the non-accepted plan performs better than the existing accepted plan (or plans) in the SQL plan baseline, then the plan is automatically accepted and becomes usable by the optimizer. After the verification is complete, a persistent report is generated detailing how the non-accepted plan performs compared to the accepted plan performance. Because the evolve process is now an AUTOTASK, DBAs can also schedule their own evolve job at end time.
Note:
* The optimizer is able to adapt plans on the fly by predetermining multiple subplans for portions of the plan.
* Adaptive plans, introduced in Oracle Database 12c, enable the optimizer to defer the final plan decision for a statement until execution time. The optimizer instruments its chosen plan (the default plan) with statistics collectors so that it can detect at runtime, if its cardinality estimates differ greatly from the actual number of rows seen by the operations in the plan. If there is a significant difference, then the plan or a portion of it will be automatically adapted to avoid suboptimal performance on the first execution of a SQL statement.
References:
NEW QUESTION: 3
You want to capture column group usage and gather extended statistics for better cardinality estimates for the customers table in the SH schema.
Examine the following steps:
1. Issue the SELECTDBMS_STATS. CREATE_EXTENDED_STATS ('SH', 'CUSTOMERS') from dual statement.
2. Execute the dbms_stats.seed_col_usage (null, 'SH', 500) procedure.
3. Execute the required queries on the customers table.
4. Issue the select dbms_stats.reportwcol_usage ('SH', 'customers') from dual statement.
Identify the correct sequence of steps.
A. 4, 1, 3, 2
B. 3, 2, 1, 4
C. 2, 3, 4, 1
D. 3, 2, 4, 1
Answer: C
Explanation:
Explanation
Step 1 (2). Seed column usage
Oracle must observe a representative workload, in order to determine the appropriate column groups. Using the new procedure DBMS_STATS.SEED_COL_USAGE, you tell Oracle how long it should observe the workload.
Step 2: (3) You don't need to execute all of the queries in your work during this window. You can simply run explain plan for some of your longer running queries to ensure column group information is recorded for these queries.
Step 3. (1) Create the column groups
At this point you can get Oracle to automatically create the column groups for each of the tables based on the usage information captured during the monitoring window. You simply have to call the DBMS_STATS.CREATE_EXTENDED_STATS function for each table.This function requires just two arguments, the schema name and the table name. From then on, statistics will be maintained for each column group whenever statistics are gathered on the table.
Note:
* DBMS_STATS.REPORT_COL_USAGE reports column usage information and records all the SQL operations the database has processed for a given object.
* The Oracle SQL optimizer has always been ignorant of the implied relationships between data columns within the same table. While the optimizer has traditionally analyzed the distribution of values within a column, he does not collect value-based relationships between columns.
* Creating extended statistics
Here are the steps to create extended statistics for related table columns withdbms_stats.created_extended_stats:
1 - The first step is to create column histograms for the related columns.
2 - Next, we run dbms_stats.create_extended_stats to relate the columns together.
Unlike a traditional procedure that is invoked via an execute ("exec") statement, Oracle extended statistics are created via a select statement.