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

1. 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) Package your code and the Apache Commands Math library into a zip file named JobJar.zip
B) When submitting the job on the command line, specify the -libjars option followed by the JAR file path.
C) 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.
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.

2. To process input key-value pairs, your mapper needs to lead a 512 MB data file in memory. What is the best way to accomplish this?

A) Place the data file in the DistributedCache and read the data into memory in the configure method of the mapper.
B) Serialize the data file, insert in it the JobConf object, and read the data into memory in the configure method of the mapper.
C) Place the data file in the DataCache and read the data into memory in the configure method of the mapper.
D) Place the data file in the DistributedCache and read the data into memory in the map method of the mapper.

3. 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 RAM
D) Processor and disk I/O

4. Analyze each scenario below and indentify which best describes the behavior of the default partitioner?

A) The default partitioner computes the hash of the value and takes the mod of that value with the number of reducers. The result determines the reducer assigned to process the key-value pair.
B) The default partitioner implements a round-robin strategy, shuffling the key-value pairs to each reducer in turn. This ensures an event partition of the key space.
C) The default partitioner assigns key-values pairs to reduces based on an internal random number generator.
D) The default partitioner computes the hash of the key. Hash values between specific ranges are associated with different buckets, and each bucket is assigned to a specific reducer.
E) The default partitioner computes the hash of the key and divides that valule modulo the number of reducers. The result determines the reducer assigned to process the key-value pair.

5. Assuming the following Hive query executes successfully:

Which one of the following statements describes the result set?

A) An 80-value ngram of sentences that contain the words "you" or "are" in the lines column of the inputdata table.
B) A trigram of the top 80 sentences that contain "you are" followed by a null space in the lines column of the inputdata table.
C) A bigram of the top 80 sentences that contain the substring "you are" in the lines column of the input data A1 table.
D) A frequency distribution of the top 80 words that follow the subsequence "you are" in the lines column of the inputdata table.

Solutions: