Abstract: The buzz-word big-data refers to the large-scale distributed data processing applications that operate on exceptionally large amounts of data. Google’s MapReduce and Apache’s Hadoop, its open-source implementation, are the defacto software systems for big-data applications. An observation of the MapReduce framework is that the framework generates a large amount of intermediate data. Such abundant information is thrown away after the tasks finish, because MapReduce is unable to utilize them. In this paper, we propose Dache, a data-aware cache framework for big-data applications. In Dache, tasks submit their intermediate results to the cache manager. A task queries the cache manager before executing the actual computing work. A nove...
For various types of enterprise and scientific applications as well as cyber-physical systems (such ...
Big data has been an imperative quantum globally. Gargantuan data types starting from terabytes to p...
In this paper, we investigate techniques to effectively orchestrate HDFS in-memory caching for Hadoo...
Abstract The buzz-word big-data refers to the large-scale distributed data processing applications t...
The Big-data refers to the huge scale distributed data processing applications that operate on unusu...
The demand for highly parallel data processing platform was growing due to an explosion in the numbe...
AbstractBig data refers to processing of enormous amount of unstructured data. The MapReduce and Had...
Big Data has come up with aureate haste and a clef enabler for the social business. Big Data is brin...
Many analytic applications built on Hadoop ecosystem have a propensity to iteratively perform repeti...
Map/reduce is a popular parallel processing framework for massive-scale data-intensive computing. Th...
The system for analyzing and eliciting public grievances serves its main purpose to receive and proc...
Data is being generated at an enormous rate, due to online activities and use of resources related t...
In the Big Data community, MapReduce has been seen as one of the key enabling approaches for meeting...
Abstract—The MapReduce platform has been widely used for large-scale data processing and analysis re...
Big data platform for equipment condition assessment is built for comprehensive analysis. The platfo...
For various types of enterprise and scientific applications as well as cyber-physical systems (such ...
Big data has been an imperative quantum globally. Gargantuan data types starting from terabytes to p...
In this paper, we investigate techniques to effectively orchestrate HDFS in-memory caching for Hadoo...
Abstract The buzz-word big-data refers to the large-scale distributed data processing applications t...
The Big-data refers to the huge scale distributed data processing applications that operate on unusu...
The demand for highly parallel data processing platform was growing due to an explosion in the numbe...
AbstractBig data refers to processing of enormous amount of unstructured data. The MapReduce and Had...
Big Data has come up with aureate haste and a clef enabler for the social business. Big Data is brin...
Many analytic applications built on Hadoop ecosystem have a propensity to iteratively perform repeti...
Map/reduce is a popular parallel processing framework for massive-scale data-intensive computing. Th...
The system for analyzing and eliciting public grievances serves its main purpose to receive and proc...
Data is being generated at an enormous rate, due to online activities and use of resources related t...
In the Big Data community, MapReduce has been seen as one of the key enabling approaches for meeting...
Abstract—The MapReduce platform has been widely used for large-scale data processing and analysis re...
Big data platform for equipment condition assessment is built for comprehensive analysis. The platfo...
For various types of enterprise and scientific applications as well as cyber-physical systems (such ...
Big data has been an imperative quantum globally. Gargantuan data types starting from terabytes to p...
In this paper, we investigate techniques to effectively orchestrate HDFS in-memory caching for Hadoo...