Open source Big Data technologies can level the playing field for analysing customer sentiment and perception. Tools such as Hadoop and NoSQL not only make it possible to process and store large volumes of unst
Survey on improved scheduling in Hadoop mapreduce in cloud environments Int. J. Comput. Appl. (2012) Y. Kouki et al. SLA-driven capacity planning for cloud applications R.H. Weber et al. Internet of Things (2010) WuX. et al. Data mining with big data Knowl. Data Eng. IEEE Trans. ...
One such evolution is the Hadoop framework which is an open source distributed data processing system. A single alignment takes an amount of time that is not predictable and is a strong memory bound problem because of the irregular memory access patterns and limitations in memory-bandwidth. A ...
the computation power and massive storage.Through the analysis on our Hadoop platform, it is exhibited that our proposed methodology can significantly recede the time for error detection and location in big data sets generated by large scale sensor network systems with acceptable error detecting ...
We can summarize general frameworks, hadoop library, hadoop word count, Map reduce and we take employees database. In this paper first we take employee complex database for input then apply all the process then our application give result with good and bad ratingAnjali Pawar...
COSMOS is underpinned by a scalable Hadoop infrastructure and can support the rapid analysis of large data-sets and the orchestration of workflows between tools with limited human effort. We describe an architecture and scalability results for the computational analysis of social media data, and ...
In terms of big data storage, although some of the systems such as Hadoop (HDFS) seem to be feasible, it needs to be adapted and modified to fit the big data power grid; Real-time data processing technology for applications such as electricity consumption measurement with resolutions below ...
During the last decade, many studies used big data technologies to manage AFC systems around the world. There are currently several types of database management systems that can be suitable for handling these large volumes of information (e.g., Hadoop Distributed File System (HDFS), Hbase, ...