Hortonworks Apache-Hadoop-Developer pass test : Hadoop 2.0 Certification exam for Pig and Hive Developer

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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:

1. Which project gives you a distributed, Scalable, data store that allows you random, realtime read/write access to hundreds of terabytes of data?

A) HBase
B) Hive
C) Hue
D) Pig
E) Sqoop
F) Oozie
G) Flume

2. In a large MapReduce job with m mappers and n reducers, how many distinct copy
operations will there be in the sort/shuffle phase?

A) m+n (i.e., m plus n)
B) mn (i.e., m to the power of n)
C) m
D) mXn (i.e., m multiplied by n)
E) n

3. Which two of the following statements are true about Pig's approach toward data? Choose 2 answers

A) Accepts data whether it has metadata or not
B) Accepts only data that is defined by metadata tables stored in a database
C) Accepts only data that has a key/value pair structure
D) Accepts any data: structured or unstructured
E) Accepts tab-delimited text data only

4. Which Two of the following statements are true about hdfs? Choose 2 answers

A) An HDFS file that is larger than dfs.block.size is split into blocks
B) Block sizes for all files must be the same size
C) HDFS works best when storing a large number of relatively small files
D) Blocks are replicated to multiple datanodes

5. What is the disadvantage of using multiple reducers with the default HashPartitioner and distributing your workload across you cluster?

A) You will longer be able to take advantage of a Combiner.
B) There are no concerns with this approach. It is always advisable to use multiple reduces.
C) By using multiple reducers with the default HashPartitioner, output files may not be in globally sorted order.
D) You will not be able to compress the intermediate data.

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