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NEW QUESTION: 1
Examine the parameters for your database instance:

Which three statements are true about the process of automatic optimization by using cardinality feedback?
A. The optimizer automatically changes a plan during subsequent execution of a SQL statement if there is a huge 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. After the optimizer identifies a query as a re-optimization candidate, statistics collected by the collectors are submitted to the optimizer.
E. The optimizer does not monitor cardinality feedback if dynamic sampling and multicolumn statistics are enabled.
Answer: A,C,E
Explanation:
Explanation/Reference:
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.

NEW QUESTION: 2
A network administrator is tasked with blocking unwanted spam is being relayed by an internal email server. Which of the following is the FIRST step in preventing spam that is originating from bots on the network?
A. Turning off the IMAP service on the email server
B. Closing off port 25 on the firewall
C. Turning off the SMTP service on the email server
D. Closing off port 53 on the firewall
Answer: B

NEW QUESTION: 3
ラベルを使用してデータ転送に関する決定を下すWANテクノロジはどれですか。
A. メトロイーサネット
B. ISDN
C. VSAT
D. フレームリレー
E. MPLS
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NEW QUESTION: 1
Examine the parameters for your database instance:

Which three statements are true about the process of automatic optimization by using cardinality feedback?
A. The optimizer automatically changes a plan during subsequent execution of a SQL statement if there is a huge 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. After the optimizer identifies a query as a re-optimization candidate, statistics collected by the collectors are submitted to the optimizer.
E. The optimizer does not monitor cardinality feedback if dynamic sampling and multicolumn statistics are enabled.
Answer: A,C,E
Explanation:
Explanation/Reference:
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.