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NEW QUESTION: 1
During implementation, there are various additional things that need to be considered for RFQs and Quotations. There are seven documented areas to consider, as well as some common sense considerations.
Select five options that accurately depict these. (Choose five.)
A. Data Mapping from the legacy RFQs and Quotes is important.
B. Quotation Usage and RFQ Usage does not matter because RFQs cannot be converted.
C. Data Cleanup of legacy RFQs and Quotes is important.
D. Data Cleanup is not important.
E. The method by which RFQs are delivered to potential suppliers (Printed Forms) is important.
F. Training on RFQ and Quotations is not necessary because the quotations are automatically created into Requisitions.
G. You should just create new RFQs in the new system so that the linkage between RFQs and Requisitions can be maintained.
H. RFQ and Quotation Usage is important.
I. RFQ and Quotation Conversion strategy is important.
J. Data Mapping for RFQs Open Interface is important.
Answer: A,C,E,H,I

NEW QUESTION: 2
You administer a Microsoft SQL Server 2016 server.
You plan to deploy new features to an application.
You need to evaluate existing and potential clustered and non-clustered indexes that will improve
performance.
What should you do?
A. Query the sys.dm_db_index_usage_stats DMV.
B. Use the Database Engine Tuning Advisor.
C. Query the sys.dm_db_missing_index_columns DMV.
D. Query the sys.dm_db_missing_index_details DMV.
Answer: B
Explanation:
Explanation/Reference:
Explanation:
The Microsoft Database Engine Tuning Advisor (DTA) analyzes databases and makes recommendations
that you can use to optimize query performance. You can use the Database Engine Tuning Advisor to
select and create an optimal set of indexes, indexed views, or table partitions without having an expert
understanding of the database structure or the internals of SQL Server. Using the DTA, you can perform
the following tasks.
Troubleshoot the performance of a specific problem query
Tune a large set of queries across one or more databases
Perform an exploratory what-if analysis of potential physical design changes
Manage storage space
References: https://docs.microsoft.com/en-us/sql/relational-databases/performance/database-engine-
tuning-advisor

NEW QUESTION: 3

Refer the exhibit. Which of the following is the correct output of the above executed command?
A)

B)

C)

D)

A. Option C
B. Option A
C. Option B
D. Option D
Answer: A

NEW QUESTION: 4
What types of algorithms are difficult to express in MapReduce v1 (MRv1)?
A. Relational operations on large amounts of structured and semi-structured data.
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. Algorithms that require applying the same mathematical function to large numbers of
individual binary records.
Answer: D
Explanation:
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