Hortonworks HDPCD Hortonworks Data Platform Certified Developer Exam Practice Test

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Total 108 questions
Question 1

In Hadoop 2.2, which one of the following statements is true about a standby NameNode?

The Standby NameNode:



Answer : B


Question 2

Which one of the following statements describes a Pig bag. tuple, and map, respectively?



Answer : B


Question 3

What are the TWO main components of the YARN ResourceManager process? Choose 2 answers



Answer : C, D


Question 4

What types of algorithms are difficult to express in MapReduce v1 (MRv1)?



Answer : C

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)


Question 5

Given the following Hive command:

INSERT OVERWRITE TABLE mytable SELECT * FROM myothertable;

Which one of the following statements is true?



Answer : B


Question 6

To use a lava user-defined function (UDF) with Pig what must you do?



Answer : C


Question 7

Which one of the following statements is false about HCatalog?



Answer : C


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