Skripsi

PERBANDINGAN METODE MAPREDUCE BERBASIS SINGLE NODE HADOOP PADA APLIKASI WORD COUNT

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Penilaian

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Word Count is a type of task used to count the occurrences of unique words in a text file. Processing time is an important factor to consider in meeting the standards of Big Data processing. In the context of Big Data processing, Hadoop MapReduce serves as a framework used to develop software and process large-scale data in parallel. The conducted research involved the processing of text files using the MapReduce method on the Hadoop Distributed File System (HDFS) using a single node, comparing the results of word count processing with and without the use of MapReduce. The research findings indicate that the implementation of Word Count without using MapReduce offers better speed and scalability in processing Indonesian language text data on a Hadoop single node. Additionally, the comparison of processing time between the Word Count program with Hadoopbased MapReduce and the Word Count program without MapReduce shows that the latter has faster processing time. A significant reduction in processing time, up to 95% for a 5 MB file, can be achieved by using the Word Count method without MapReduce, although the level of reduction decreases with increasing file size. Keywords : Big Data, Word Count, MapReduce, HDFS, Hadoop Single Node.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307005460	T120932	T1209322023	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1209322023

Publisher

Indralaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xv, 53 hlm.; Illus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Metode
Jurusan Teknik Informatika

Specific Detail Info

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Statement of Responsibility

FIRA

Other version/related

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