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NEW QUESTION: 1
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. Large-scale graph algorithms that require one-step link traversal.
C. Algorithms that require applying the same mathematical function to large numbers of individual binary records.
D. Algorithms that require global, sharing states.
E. Text analysis algorithms on large collections of unstructured text (e.g, Web crawls).
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
NEW QUESTION: 2
Which of the following service scenarios is the most suitable for terminal to implement DRX? _SC
A. Intelligent meter reading
B. video on-live
C. VR gaming
D. Automated driving
Answer: A
NEW QUESTION: 3
Refer to the exhibit.
An engineer must connect a fork lift via a WGB to a wireless network and must authenticate the WGB certificate against the RADIUS server. Which three steps are required for this configuration? (Choose three.)
A. Configure WLAN to authenticate using ISE.
B. Configure WGB as a network device in ISE.
C. Configure the access point with the root certificate from ISE.
D. Configure the certificate on the WLC.
E. Configure a policy on ISE to allow devices to connect that validate the certificate.
F. Configure the certificate, WLAN, and radio interface on WGB.
Answer: A,E,F
NEW QUESTION: 4
Azure Event Gridに接続するカスタムAzure関数アプリを構築しています。
リソースが関数アプリに動的に割り当てられるようにする必要があります。請求はアプリの実行に基づいている必要があります。
関数アプリを作成するときに何を設定する必要がありますか？
A. Dockerコンテナーと、B1価格ティアを使用するApp Serviceプラン
B. WindowsオペレーティングシステムとApp Serviceプランのホスティングプラン
C. Windowsオペレーティングシステムと消費計画ホスティングプラン
D. Dockerコンテナーと、S1価格設定層を使用するApp Serviceプラン
Answer: C
Explanation:
Explanation
References:
https://docs.microsoft.com/en-us/azure/azure-functions/functions-scale
