SURVEY OF SIMILARITY JOIN ALGORITHMS BASED ON MAPREDUCE
Journal: MATTER: International Journal of Science and Technology (Vol.2, No. 1)Publication Date: 2016-01-01
Authors : Amer Al Badarneh; Amnah - Al Abdi; Sana'a Al Shboul; Hassan Najadat;
Page : 214-234
Keywords : Hadoop; MapReduce; Similarity Join;
Abstract
Similarity Join is a data processing and analysis operation that retrieves all data pairs whose their distance is less than a pre-defined threshold. The similarity join algorithms are used in different real world applications such as finding similarity in documents, images, and strings. In this survey we will explain some of the similarity join algorithms which are based on MapReduce approach. These algorithms are: Set-Similarity Join, SSJ-2R, MRSimJoin, Pair-wise similarity, multi-sig-er method, Trie-join, and PreJoin algorithm. We then make a comparison between these algorithms according to some criteria and discuss the results.
Other Latest Articles
- THE BEING EXAMINED OF YESÂRÎ ÂSIM ARSOY'S HIS SONG IN HÜZZAM MAQAM NAMED “ÖMRÜM SENI SEVMEKLE NIHAYET BULACAKTIR” IN TERM OF THE PERFORMANCE STYLE DIFFERENCES FROM THREE SINGERS (YESÂRÎ ÂSIM ARSOY, MÜNIR NURETTIN SELÇUK, BEKIR SIDKI SEZGIN)
- INDEX-BASED JOIN IN MAPREDUCE USING HADOOP MAPFILES
- EARLY CHILDHOOD SCIENCE EDUCATION TRENDS IN TURKEY: WHERE FROM? WHERE TO?
- SOCIO-ECONOMIC AND ENVIRONMENTAL ATTRIBUTES OF WASTE ELECTRICAL AND ELECTRONIC EQUIPMENT (WEEE) RECYCLING IN ASIA
- DEVELOPMENT OF A SOFTWARE BASED SYSTEM TO APPLY TURKISH BUILDING ENERGY PERFORMANCE DIRECTIVE
Last modified: 2018-04-26 17:33:44