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NEW QUESTION: 1
Which three object types can you use in a Web Intelligence universe query?
A. Detail
B. Class
C. Dimension
D. Measure
E. User Defined
Answer: A,C,D

NEW QUESTION: 2
You have a Python data frame named salesData in the following format:
The data frame must be unpivoted to a long data format as follows:
You need to use the pandas.melt() function in Python to perform the transformation.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: dataFrame
Syntax: pandas.melt(frame, id_vars=None, value_vars=None, var_name=None, value_name='value', col_level=None)[source] Where frame is a DataFrame Box 2: shop Paramter id_vars id_vars : tuple, list, or ndarray, optional Column(s) to use as identifier variables.
Box 3: ['2017','2018']
value_vars : tuple, list, or ndarray, optional
Column(s) to unpivot. If not specified, uses all columns that are not set as id_vars.
Example:
df = pd.DataFrame({'A': {0: 'a', 1: 'b', 2: 'c'},
'B': {0: 1, 1: 3, 2: 5},
'C': {0: 2, 1: 4, 2: 6}})
pd.melt(df, id_vars=['A'], value_vars=['B', 'C'])
A variable value
0 a B 1
1 b B 3
2 c B 5
3 a C 2
4 b C 4
5 c C 6
References:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.melt.html

NEW QUESTION: 3
An airline is building a booking system for its premium and general customers. The goal is to ensure premium members are given higher access priority when user traffic is high.
What configuration will achieve this goal?
A. Configure a Work Manager for premium users with a higher fair-share-request-class.
B. Configure a Work Manager for premium users with a Minimum Thread Constraint.
C. Configure a Work Manager for premium users with a higher response-time-request-class.
D. Configure a Work Manager general users with a Maximum Thread Constraint.
E. Configure a Work Manager for premium users with a custom request-class.
Answer: A
Explanation:
Explanation/Reference:
fair-share-request-class-Specifies the average thread-use time required to process requests. The default fair share value is 50.
For example, assume that WebLogic Server is running two modules. The Work Manager for ModuleA specifies a fair-share-request-class of 80 and the Work Manager for ModuleB specifies a fair- share-request-class of 20.
During a period of sufficient demand, with a steady stream of requests for each module such that the number requests exceed the number of threads, WebLogic Server will allocate 80% and 20% of the thread-usage time to ModuleA and ModuleB, respectively.
* Example:
< work-manager>
< name>lowpriority_workmanager</name>
< fair-share-request-class>
< name>low_priority</name>
< fair-share>10</fair-share>
< /fair-share-request-class>
< /work-manager>
< work-manager>
< name>highpriority_workmanager</name>
< fair-share-request-class>
< name>high_priority</name>
< fair-share>100</fair-share>
< /fair-share-request-class>
< /work-manager>
Note:
* A request class expresses a scheduling guideline that WebLogic Server uses to allocate threads to requests. Request classes help ensure that high priority work is scheduled before less important work, even if the high priority work is submitted after the lower priority work.
Incorrect:
Not C: response-time-request-class-Specifies a response time goal in milliseconds. Response time goals are not applied to individual requests. Instead, WebLogic Server computes a tolerable waiting time for requests with that class by subtracting the observed average thread use time from the response time goal, and schedules requests so that the average wait for requests with the class is proportional to its tolerable waiting time.
Not A, D: Not related to thread constraints.
For example, assume that WebLogic Server is running two modules. The Work Manager for ModuleA specifies a fair-share-request-class of 80 and the Work Manager for ModuleB specifies a fair-share- request-class of 20.