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which two resources should you expect to be bottlenecks?

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?

Will you be able to reuse your existing Reduces as your combiner in this case and why or why not?

You want to count the number of occurrences for each unique word in the supplied input data.
You’ve decided to implement this by having your mapper tokenize each word and emit a literal
value 1, and then have your reducer increment a counter for each literal 1 it receives. After
successful implementing this, it occurs to you that you could optimize this by specifying a
combiner. Will you be able to reuse your existing Reduces as your combiner in this case and why
or why not?

Determine the difference between setting the number of reduces to one and settings the number of reducers to z

You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses
TextInputFormat: the mapper applies a regular expression over input values and emits key-values
pairs with the key consisting of the matching text, and the value containing the filename and byte
offset. Determine the difference between setting the number of reduces to one and settings the
number of reducers to zero.


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