Which three statements are true about the process of au…

Examine the parameters for your database instance:
NAMETYPEVALUE
—————————————————————————————————–
optimizer_adaptive_reporting_onlybooleanFALSE
optimizer_capture_sql_plan_baselinesbooleanFALSE
optimizer_dynamic_samplinginteger2
optimizer_features_enablestring12.1.0.1
Which three statements are true about the process of automatic optimization by using statistics feedback?

A.
The optimizer automatically changes a plan during subsequent execution of a SQL statement if there is ahuge difference in optimizer estimates and execution statistics.

B.
The optimizer can re optimize a query only once using cardinality feedback.

C.
The optimizer enables monitoring for cardinality feedback after the first execution of a query.

D.
The optimizer does not monitor cardinality feedback if dynamic sampling and multicolumn statistics are
enabled.

E.
After the optimizer identifies a query as a re-optimization candidate, statistics collected by the collectors are
submitted to the optimizer.

Explanation:
C: During the first execution of a SQL statement, an execution plan is generated as usual.
D: if multi-column statistics are not present for the relevant combination of columns, the optimizer can fall back
on cardinality feedback.
(not B)* Cardinality feedback. This feature, enabled by default in 11.2, is intended to improve plans for repeated
executions.
optimizer_dynamic_sampling
optimizer_features_enable
Dynamic sampling or multi-column statistics allow the optimizer to more accurately estimate selectivity of
conjunctive predicates.
Note:
* OPTIMIZER_DYNAMIC_SAMPLING controls the level of dynamic sampling performed by the optimizer.
Range of values. 0 to 10
Cardinality feedback was introduced in Oracle Database 11gR2. The purpose of this feature is to automatically
improve plans for queries that are executed repeatedly, for which the optimizer does not estimate cardinalities
in the plan properly. The optimizer may misestimate cardinalities for a variety of reasons, such as missing or
inaccurate statistics, or complex predicates. Whatever the reason for the misestimate, cardinality feedback may
be able to help.