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Preparation for MapReduce recitation
This paper was published at the biennial Usenix Symposium on
Operating Systems Design and Implementation (OSDI) in 2004, one of the
premier conferences in computer systems. (OSDI alternates with the
equally prestigious ACM Symposium on Operating Systems Principles
(SOSP), at which appeared Eraser, the paper you already read in a
previous recitation.)
As you read the paper, keep the following questions in mind,
and submit a short answer to any one of these questions (except
for the first one) via the submission web site:
- At first glance, the map/reduce model of computation seems
limited. Did the paper persuade you that their model of
computation has practical use?
- Are the authors trying to solve a technological problem (one that
will be solved with faster computation), or an intrinsic
problem?
- What assumptions do the authors make about how machines fail,
what machines fail, and what they do when they fail? What happens
to the system when a given machine fails?
- What exactly would happen if one block of one hard drive got
erased during a map/reduce computation? What parts of the system
would fix the error (if any), and what parts of the system would
be oblivious (if any)?
- How do the authors evaluate the performance of their system? What
are "Input," "Output," and
"Shuffle?"
- How do "stragglers" impact performance?
Here are some points to keep in mind as you read:
- In the functional programming notation used in Section 2.2, the
function takes the arguments shown to the left of the arrow and
returns the type shown to the right of the arrow.
- After you read Section 3.1, you should be able to instantly
recall the following terms: "split," "map
worker," "reduce worker," "master."
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