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NEW QUESTION: 1
You are developing an ASP.NET MVC application. The application is deployed in a web farm and is accessed by many users.
The application must handle web server failures gracefully. The servers in the farm must share the state information.
You need to persist the application state during the session.
What should you implement?
A. A state server
B. Cookieless sessions
C. A web garden on the web servers
D. An InProc session
Answer: A
Explanation:
Explanation
ASP.NET session state service provides a somewhat slower service than the in-process variant as we need to make calls to a remote server. All session data is stored in memory so shutting down the state machine will wipe out all session data as well.
Incorrect:
Not D: The InProc option is particularly dangerous in a web farm environment. For example imagine one farm machine which stores the session state but not the other. Subsequent web requests from the same user may not read the correct session state.
References: https://dotnetcodr.com/2013/07/01/web-farms-in-net-and-iis-part-5-session-state-management/
NEW QUESTION: 2
An engineer needs to create a volume in the web GUT Explorer view. The volume needs to automatically present to a specific server when created. How should the engineer create this volume?
A. right-click on the Servers group icon and select Create volume
B. right-click on the Storage icon and select Create volume
C. right-click on the Storage icon and select Create volumes
D. right-click on the intended server and select Create volumes
Answer: D
NEW QUESTION: 3
Examine the structure of the PROMOS table:
You want to display the list of promo names with the message 'Same Day' for promos that started and ended on the same day.
Which query gives the correct output?
A. SELECT promo_name, NVL(TRUNC(promo_end_date - promo_start_date), 'Same
Day') FROM promos;
B. SELECT promo_name, NVL2(TO_CHAR(TRUNC(promo_end_date-promo_start_date)),
NULL,'Same Day')
FROM promos;
C. SELECT promo_name, DECODE((NULLIF(promo_start_date, promo_end_date)),
NULL,'Same day') FROM promos;
D. SELECT promo_name, NVL(NULLIF(promo_start_date, promo_end_date), 'Same Day')
FROM promos;
Answer: C
Explanation:
The NULLIF Function The NULLIF function tests two terms for equality. If they are equal the function returns a null, else it returns the first of the two terms tested. The NULLIF function takes two mandatory parameters of any data type. The syntax is NULLIF(ifunequal, comparison_term), where the parameters ifunequal and comparison_term are compared. If they are identical, then NULL is returned. If they differ, the ifunequal parameter is returned ANSWER A - date and String incompatibl;a datatypes for NVL function The Date TRUNC Function The date TRUNC function performs a truncation operation on a date value based on a specified date precision format. The date TRUNC function takes one mandatory and one optional parameter. Its syntax is TRUNC(source date, [date precision format]). The source date parameter represents any value that can be implicitly converted into a date item. The date precision format parameter specifies the degree of truncation and is optional. If it is absent, the default degree of truncation is day. This means that any time component
NEW QUESTION: 4
You need to use the Python language to build a sampling strategy for the global penalty detection models.
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: import pytorch as deeplearninglib
Box 2: ..DistributedSampler(Sampler)..
DistributedSampler(Sampler):
Sampler that restricts data loading to a subset of the dataset.
It is especially useful in conjunction with class:`torch.nn.parallel.DistributedDataParallel`. In such case, each process can pass a DistributedSampler instance as a DataLoader sampler, and load a subset of the original dataset that is exclusive to it.
Scenario: Sampling must guarantee mutual and collective exclusively between local and global segmentation models that share the same features.
Box 3: optimizer = deeplearninglib.train. GradientDescentOptimizer(learning_rate=0.10) Incorrect Answers: ..SGD..
Scenario: All penalty detection models show inference phases using a Stochastic Gradient Descent (SGD) are running too slow.
Box 4: .. nn.parallel.DistributedDataParallel..
DistributedSampler(Sampler): The sampler that restricts data loading to a subset of the dataset.
It is especially useful in conjunction with :class:`torch.nn.parallel.DistributedDataParallel`.
References:
https://github.com/pytorch/pytorch/blob/master/torch/utils/data/distributed.py