期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2018
卷号：9
期号：6
DOI：10.14569/IJACSA.2018.090607
出版社：Science and Information Society (SAI)
摘要：A Hadoop HDFS is an organized and distributed collection of files. It is created to store a huge part of data and then retrieve it and analyze it efficiently in a less amount of time. To retrieve and analyze data from the Hadoop HDFS, MapReduce Jobs must be created directly using some programming languages like Java or indirectly using some high level languages like HiveQL and PigLatin. Everyone knows that creating MapReduce programs using programming languages is a difficult task that requires a remarkable effort for their creation and also for their maintenance. Writing MapReduce code by hand needs a lot of time, introduce bugs, harm readability, and impede optimizations. Profiles working in the field of big data always try to avoid hard and long programs in their work. They are always looking for much simpler alternatives like graphical interfaces or reduced scripts like PIG Latin or even SQL queries. This article proposes to use a MapReduce Query API inspired from Hibernate Criteria to simplify the code of MapReduce programs. This API proposes a set of predefined methods for making restrictions, projections, logical conditions and so on. An implementation of the Word Count example using the Query Criteria API is illustrated in this paper.
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