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Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:

1. MapReduce v2 (MRv2/YARN) is designed to address which two issues?

A) Ability to run frameworks other than MapReduce, such as MPI.
B) HDFS latency.
C) Reduce complexity of the MapReduce APIs.
D) Single point of failure in the NameNode.
E) Resource pressure on the JobTracker.
F) Standardize on a single MapReduce API.

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

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

3. What does the following WebHDFS command do?
Curl -1 -L "http://host:port/webhdfs/v1/foo/bar?op=OPEN"

A) Make a directory /foo/bar
B) List a directory /foo
C) Read a file /foo/bar
D) Delete a directory /foo/bar

4. You are developing a combiner that takes as input Text keys, IntWritable values, and emits Text keys,
IntWritable values. Which interface should your class implement?

A) Combiner <Text, Text, IntWritable, IntWritable>
B) Reducer <Text, IntWritable, Text, IntWritable>
C) Reducer <Text, Text, IntWritable, IntWritable>
D) Mapper <Text, IntWritable, Text, IntWritable>
E) Combiner <Text, IntWritable, Text, IntWritable>

5. You need to create a job that does frequency analysis on input data. You will do this by writing a Mapper
that uses TextInputFormat and splits each value (a line of text from an input file) into individual characters.
For each one of these characters, you will emit the character as a key and an InputWritable as the value.
As this will produce proportionally more intermediate data than input data, which two resources should
you expect to be bottlenecks?

A) Processor and network I/O
B) Disk I/O and network I/O
C) Processor and disk I/O
D) Processor and RAM

Solutions: