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

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

2. Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which is 100MB in size. The InputFormat for your job is TextInputFormat. Determine how many Mappers will run?

A) 640
B) 200
C) 100
D) 64

3. For each input key-value pair, mappers can emit:

A) As many intermediate key-value pairs as designed, as long as all the keys have the same types and all the values have the same type.
B) As many intermediate key-value pairs as designed, but they cannot be of the same type as the input key-value pair.
C) As many intermediate key-value pairs as designed. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
D) One intermediate key-value pair, but of the same type.
E) One intermediate key-value pair, of a different type.

4. For each intermediate key, each reducer task can emit:

A) As many final key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
B) As many final key-value pairs as desired, as long as all the keys have the same type and all the values have the same type.
C) As many final key-value pairs as desired, but they must have the same type as the intermediate key-value pairs.
D) One final key-value pair per value associated with the key; no restrictions on the type.
E) One final key-value pair per key; no restrictions on the type.

5. You need to perform statistical analysis in your MapReduce job and would like to call methods in the Apache Commons Math library, which is distributed as a 1.3 megabyte Java archive (JAR) file. Which is the best way to make this library available to your MapReducer job at runtime?

A) Have your system administrator copy the JAR to all nodes in the cluster and set its location in the HADOOP_CLASSPATH environment variable before you submit your job.
B) Package your code and the Apache Commands Math library into a zip file named JobJar.zip
C) When submitting the job on the command line, specify the -libjars option followed by the JAR file path.
D) Have your system administrator place the JAR file on a Web server accessible to all cluster nodes and then set the HTTP_JAR_URL environment variable to its location.

Solutions: