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NEW QUESTION: 1
A laptop with server 2012 OS, you need to ensure that server 2012 can use wireless network adapter. what should you do first?
A. use server manager to install the Wireless Network Role
B. use server manager to install the Wireless Network Feature
C. use server manager to install the Wireless Lan Service Role
D. use server manager to install the Wireless Lan Service Feature
Answer: D
Explanation:

http://www.win2012workstation.com/wireless-networking/

NEW QUESTION: 2
A company's employees were victims of a spear phishing campaign impersonating the CEO. The company would now like to implement a solution to improve the overall security posture by assuring their employees that email originated from the CEO. Which of the following controls could they implement to BEST meet this goal?
A. Digital certificates
B. Antivirus software
C. Spam filter
D. Digital signatures
Answer: D
Explanation:
A digital signature is a mathematical technique used to validate the authenticity and integrity of a message, software, or digital document. The digital equivalent of a handwritten signature or stamped seal, but offering far more inherent security, a digital signature is intended to solve the problem of tampering and impersonation in digital communications. Digital signatures can provide the added assurances of evidence to origin, identity and status of an electronic document, transaction or message, as well as acknowledging informed consent by the signer. Digital signatures are based on public key cryptography, also known as asymmetric cryptography. Using a public key algorithm such as RSA, one can generate two keys that are mathematically linked: one private and one public. To create a digital signature, signing software (such as an email program) creates a one-way hash of the electronic data to be signed. The private key is then used to encrypt the hash. The encrypted hash -- along with other information, such as the hashing algorithm -- is the digital signature. The reason for encrypting the hash instead of the entire message or document is that a hash function can convert an arbitrary input into a fixed length value, which is usually much shorter. This saves time since hashing is much faster than signing.

NEW QUESTION: 3
Refer to the exhibit:

Which command is used to complete this configuration for QoS class-based marking?
A. PE-A(config -pmap-c)#priority
B. PE-A(config-pmap-c)#set dscp ef
C. PE-A(config-pmap-c)#random-detect
D. PE-A(config-pmap-c)#fair-queue
Answer: B

NEW QUESTION: 4
What types of algorithms are difficult to express in MapReduce v1 (MRv1)?
A. Algorithms that require applying the same mathematical function to large numbers of individual binary records.
B. Text analysis algorithms on large collections of unstructured text (e.g, Web crawls).
C. Large-scale graph algorithms that require one-step link traversal.
D. Algorithms that require global, sharing states.
E. Relational operations on large amounts of structured and semi-structured data.
Answer: D
Explanation:
Explanation/Reference:
See 3) below.
Limitations of Mapreduce - where not to use Mapreduce
While very powerful and applicable to a wide variety of problems, MapReduce is not the answer to every problem. Here are some problems I found where MapReudce is not suited and some papers that address the limitations of MapReuce.
1. Computation depends on previously computed values
If the computation of a value depends on previously computed values, then MapReduce cannot be used.
One good example is the Fibonacci series where each value is summation of the previous two values. i.e., f(k+2) = f(k+1) + f(k). Also, if the data set is small enough to be computed on a single machine, then it is better to do it as a single reduce(map(data)) operation rather than going through the entire map reduce process.
2. Full-text indexing or ad hoc searching
The index generated in the Map step is one dimensional, and the Reduce step must not generate a large amount of data or there will be a serious performance degradation. For example, CouchDB's MapReduce may not be a good fit for full-text indexing or ad hoc searching. This is a problem better suited for a tool such as Lucene.
3. Algorithms depend on shared global state
Solutions to many interesting problems in text processing do not require global synchronization. As a result, they can be expressed naturally in MapReduce, since map and reduce tasks run independently and in isolation. However, there are many examples of algorithms that depend crucially on the existence of shared global state during processing, making them difficult to implement in MapReduce (since the single opportunity for global synchronization in MapReduce is the barrier between the map and reduce phases of processing) Reference: Limitations of Mapreduce - where not to use Mapreduce