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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2018
عنوان انگلیسی مقاله:
In-Mapper combiner based MapReduce algorithm for processing of big climate data
ترجمه فارسی عنوان مقاله:
الگوریتم MapReduce مبتنی بر ترکیب Mapper در پردازش داده های آب و هوایی بزرگ
منبع:
Sciencedirect - Elsevier - Future Generation Computer Systems, Corrected proof: doi:10:1016/j:future:2018:02:048
نویسنده:
Gunasekaran Manogaran a, Daphne Lopez b, Naveen Chilamkurti c,*
چکیده انگلیسی:
Big data refers to a collection of massive volume of data that cannot be processed by conventional data
processing tools and technologies. In recent years, the data production sources are enlarged noticeably,
such as high-end streaming devices, wireless sensor networks, satellite, wearable Internet of Things (IoT)
devices. These data generation sources generate a massive volume of data in a continuous manner. The
large volume of climate data is collected from the IoT weather sensor devices and NCEP. In this paper, the
big data processing framework is proposed to integrate climate and health data and to find the correlation
between the climate parameters and incidence of dengue. This framework is demonstrated with the help
of MapReduce programming model, Hive, HBase and ArcGIS in a Hadoop Distributed File System (HDFS)
environment. The following weather parameters such as minimum temperature, maximum temperature,
wind, precipitation, solar and relative humidity are collected for the study are Tamil Nadu with the help
of IoT weather sensor devices and NCEP. Proposed framework focuses only on climate data for 32 districts
of Tamil Nadu where each district contains 1,57,680 rows and so there are 50,45,760 rows in total. Batch
view precomputation for the monthly mean of various climate parameters would require 50,45,760 rows.
Hence, this would create more latency in query processing. In order to overcome this issue, batch views
can precompute for a smaller number of records and involve more computation to be done at query time.
The In-Mapper based MapReduce framework is used to compute the monthly mean of climate parameter
for each latitude and longitude. The experimental results prove the effectiveness of the response time for
the In-Mapper based combiner algorithm is less when compared with the existing MapReduce algorithm.
Keywords: Big data ، Internet of Things ، Weather sensor devices ، MapReduce programming ،Model ، Hadoop distributed file system
قیمت: رایگان
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