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

1. Given the following Pig commands:

Which one of the following statements is true?

A) The severe relation is not valid
B) The $1 variable represents the first column of data in 'my.log'
C) The $1 variable represents the second column of data in 'my.log'
D) The grouped relation is not valid

2. In a MapReduce job, the reducer receives all values associated with same key. Which statement best describes the ordering of these values?

A) The values are in sorted order.
B) The values are arbitrary ordered, but multiple runs of the same MapReduce job will always have the same ordering.
C) The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
D) Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.

3. Identify the tool best suited to import a portion of a relational database every day as files into HDFS, and generate Java classes to interact with that imported data?

A) Hue
B) Sqoop
C) Oozie
D) Hive
E) fuse-dfs
F) Pig
G) Flume

4. Assuming the following Hive query executes successfully:

Which one of the following statements describes the result set?

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

5. You have just executed a MapReduce job. Where is intermediate data written to after being emitted from the Mapper's map method?

A) Into in-memory buffers that spill over to the local file system of the TaskTracker node running the Mapper.
B) Into in-memory buffers on the TaskTracker node running the Mapper that spill over and are written into HDFS.
C) Into in-memory buffers on the TaskTracker node running the Reducer that spill over and are written into HDFS.
D) Intermediate data in streamed across the network from Mapper to the Reduce and is never written to disk.
E) Into in-memory buffers that spill over to the local file system (outside HDFS) of the TaskTracker node running the Reducer

Solutions: