Deserializing JSON data in hadoop

0Citations
Citations of this article
1Readers
Mendeley users who have this article in their library.
Get full text

Abstract

MapReduce provides an efficient programming framework for processing big data in parallel in Hadoop. On the other hand, as the digitalized data becomes bigger as the advances information of technology, deserializing big JSON data into paths in advance can benefit queries on the data. Therefore, using MapReduce framework to deserialize big JSON data into JSON paths is applicable. In this paper, we propose an efficient JSON data processing mechanism based on MapReduce framework. The mechanism includes a redesign of JSONInputFormat class and the other two Map and Reduce functions.

Author supplied keywords

Cite

CITATION STYLE

APA

Chen, S. Y., Chen, H. M., Chen, I. H., & Huang, C. C. (2015). Deserializing JSON data in hadoop. In Lecture Notes in Electrical Engineering (Vol. 329, pp. 79–85). Springer Verlag. https://doi.org/10.1007/978-94-017-9558-6_10

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free