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author | Andrea Smith <smit9523@umn.edu> | 2020-10-05 23:02:05 -0500 |
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committer | Andrea Smith <smit9523@umn.edu> | 2020-10-05 23:02:05 -0500 |
commit | 76b38027ed1fa2f5f5888b5f390214c8e615a929 (patch) | |
tree | 6246da224c4a755ed6cd4fec5313fd85162ca5b8 /P1 | |
parent | Maybe #6 is done? (diff) | |
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Updated README
Diffstat (limited to 'P1')
-rw-r--r-- | P1/README.md | 20 |
1 files changed, 19 insertions, 1 deletions
diff --git a/P1/README.md b/P1/README.md index 0266e65..ea3f362 100644 --- a/P1/README.md +++ b/P1/README.md @@ -1 +1,19 @@ -Add your project details as mentioned in Section Deliverables.
\ No newline at end of file +test machine: apollo.cselabs.umn.edu +date: 10/3/2020 +name: Andrea Smith , Matt Strapp +x500: smit9523, strap012 + +The purpose of this program is to recreate the mapreduce programming model for Big Data Analytics. In order to compile this program, simply run the included Makefile, which takes no arguments. + +Program structure: +mapreduce.c: + Mapreduce is the master phase of this program. It is responsible for calling the mapper and reducer processes. It will wait for each process to finish executing before exiting the code. + +mapper.c: + Mapper receives a chunk of data and emits it into an intermediate data structure, which is a two-level linked list. writeIntermediateDS() formats the data, writing each word and its associated "1's" in the form "word 1 1 1..." to its own file, word.txt. + +reducer.c: + Reducer receives the word.txt files and "reduces" them into n files (where n is an input) containing the words and amount of 1's associated with the word in the format "word number_of_1's" + +Team Contributions: +As can be seen by the number of back-and-forth GitHub commits, this project was thoroughly a team effort. However, for the purposes of appropriating (what I am sure will be) praise from the professors and TA's (just kidding!), Matt wrote mapreduce, Andrea wrote reducer, and mapper was written by both of us.
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