#FILE2FOLDER GUI INSTALL#
#FILE2FOLDER GUI CODE#

#FILE2FOLDER GUI CODE#

 In output, keys should be sorted in ascending key order (ASCII code value). Do NOT modify any files that we have provided including Map() and Reduce(). The number of threads must not exceed the value specified as input in the multi-threaded version.– The test program must pass the function pointer of hash function as an argument in  You do NOT need to implement the MR_DefaultHashPartition() function.– You need to give the number of partitions as shown in 2.4 Output. Target files instead of passing all the file names. – When executing the executable files, we will pass only a folder name including all the  The difference between this project and the original project described in 2.1 Concept:. 5) Print (key, count) pairs and the execution time.  2) After you have made your own files. Execution time: the time for execution. Count: the number of words corresponding to the given key. Key: words separated by blank characters.The user applications, single_mapreduce and multi_mapreduce, will print the following:  the number of partitions: the number of partitions we will use. folder name: the folder we will use to test.The following arguments will be passed as input:  If you run the programs, the result and execution time will be shown. The compiling outputs are as follows:.– To compile wordcount.c for the multi-threaded version. – To compile wordcount.c for the single-threaded version. – To compile wordcount.c for both single- and multi-threaded versions.  We provide a Makefile which you can use to compile your program. When implementing the multi-threaded version, you should use the pthread APIs for. You need to complete the functions of MR_Emit() and MR_Run().– multi_mapreduce.c: Contains your functions for the multi-threaded MapReduce – single_mapreduce.c: Contains your functions for the single-threaded MapReduce  Your task is to complete the following files which will be compiled with the test file wordcount.c.  You are expected to describe the concept of MapReduce in your report. Use the pthread APIs for this project. The general idea of MapReduce is described at the following link.– input_long_unbalanced: A complex test set that is unbalanced.– input_long_balanced: A complex test set that is balanced.– wordcount.c: The C file to test your functions.(It is different from the file mapreduce.h provided in the link given in 2.1 Concept.) – mapreduce.h: The header file for implementing your functions.– Makefile: Use this file to compile wordcount.c with your functions. Three files and three folders will be given. Evaluation will be carried out in Ubuntu environment with AMD Ryzen Threadripper 1950X.

#FILE2FOLDER GUI INSTALL#

 You can install Ubuntu or use a virtual machine to carry out your project. The project should be performed in Ubuntu 16.04 environment.By accomplishing this project, you will be able to understand what MapReduce is and use threads and the related functions to realize concurrency. Construct functions that efficiently treat data and work concurrently for the given application wordcount.c. Furthermore, you will have to correctly understand and implement concurrency for this project. In this project, your task is to understand Map Reduce and build a simplified version of it. It is generally used in the domain of databases.

MapReduce is a new paradigm for large-scale parallel data processing introduced by Google engineers in 2004.

File2folder gui