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NEW QUESTION: 1
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. After the optimizer identifies a query as a re-optimization candidate, statistics collected by the collectors are submitted to the optimizer.
B. The optimizer can re optimize a query only once using cardinality feedback.
C. 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.
D. The optimizer enables monitoring for cardinality feedback after the first execution of a query.
E. The optimizer doesnot monitor cardinality feedback if dynamic sampling and multicolumn statistics are enabled.
Answer: C,D,E
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 toautomatically 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
Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?
A. The with Allowed Lateness method
B. A processing time trigger
C. An hourly watermark
D. An event time trigger
Answer: B
Explanation:
When collecting and grouping data into windows, Beam uses triggers to determine when to emit the aggregated results of each window.
Processing time triggers. These triggers operate on the processing time ?the time when the data element is processed at any given stage in the pipeline. Event time triggers. These triggers operate on the event time, as indicated by the timestamp on each data element. Beam's default trigger is event time-based.
Reference: https://beam.apache.org/documentation/programming-guide/#triggers

NEW QUESTION: 3

StringBuffer b = new StringBuffer("3"); System.out.print(5+4+b+2+1);

A. Option A
B. Option B
C. Option F
D. Option D
E. Option C
F. Option E
Answer: C
Explanation:
The code will not compile.
The print function cannot handle the mixture of integers and strings.
Exception in thread "main" java.lang.RuntimeException: Uncompilable source code -
Erroneous tree type

NEW QUESTION: 4
Which of the following is not true about Project Plan Development?
A. It is used to document project planning assumptions
B. It involves making trade offs between competing objectives and alternatives
C. Wait until all the other planning outputs are complete, then compile them into one final
project plan
D. It is an iterative process
Answer: C