Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume
that the two tables are formatted as comma-separated files in HDFS.

You’ve written a MapReduce job that will process 500 million input records and generated 500
million key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a
significant amount of intermediate data that it needs to transfer between mappers and reduces
which is a potential bottleneck. A custom implementation of which interface is most likely to reduce
the amount of intermediate data transferred across the network?

You want to populate an associative array in order to perform a map-side join. You’ve decided to
put this information in a text file, place that file into the DistributedCache and read it in your
Mapper before any records are processed.
Indentify which method in the Mapper you should use to implement code for reading the file and
populating the associative array?

Which best describes how TextInputFormat processes input files and line breaks?

Identify the MapReduce v2 (MRv2 / YARN) daemon responsible for launching application
containers and monitoring application resource usage?

You are developing a MapReduce job for sales reporting. The mapper will process input keys
representing the year (IntWritable) and input values representing product indentifies (Text).
Indentify what determines the data types used by the Mapper for a given job.

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

You want to understand more about how users browse your public website, such as which pages
they visit prior to placing an order. You have a farm of 200 web servers hosting your website. How
will you gather this data for your analysis?