Figure 3 - uploaded by Mohammed Elmogy
Content may be subject to copyright.
Download
View publication
The MapReduce architecture.  MapReduce Algorithm There are four steps to implement MapReduce framework, which includes reading a large dataset, implementing the map function, implementing the reduce function, and returning the resulting data from the map and reduce. The mapper receives masses of data and produces intermediate results. The reducer reads the intermediate results and emits a final result.  

The MapReduce architecture.  MapReduce Algorithm There are four steps to implement MapReduce framework, which includes reading a large dataset, implementing the map function, implementing the reduce function, and returning the resulting data from the map and reduce. The mapper receives masses of data and produces intermediate results. The reducer reads the intermediate results and emits a final result.  

Source publication
Figure 1. The Big data in IoT. The essential thought of IoT is to...
Table 1 : The comparison between KM, Optics, EM, DBSCAN, and our...
Figure 2. The Big data 4Vs and data sequence. Figure 2 observes the big...
Table 2 : The Positive and Negative matrix for the proposed system.
+5 Figure 3. The MapReduce architecture.  MapReduce Algorithm There are...
A BIG DATA PROCESSING FRAMEWORK BASED ON MAPREDUCE WITH APPLICATION TO INTERNET OF THINGS
Article
Full-text available
  • Jul 2016
Massive and various data from the Internet of Things (IoT) generate enormous storage challenges. The IoT applications caused an extensive development. In the past two decades, the expansion of computational asset had a significant effect on the flow of the data. The vast flow of data is identified as \"Big data,\" which is the data that cannot be m...
Cite
Download full-text