AbstractThe MapReduce framework has been generating a lot of interest in a wide range of areas. It has been widely adopted in industry and has been used to solve a number of non-trivial problems in academia. Putting MapReduce on strong theoretical foundations is crucial in understanding its capabilities. This work links MapReduce to the BSP model of computation, underlining the relevance of BSP to modern parallel algorithm design and defining a subclass of BSP algorithms that can be efficiently implemented in MapReduce
In this paper, we study the MapReduce framework from an algorithmic standpoint and demonstrate the u...
We regard the MapReduce mechanism as a unifying principle in the domain of computer science. Going b...
AbstractMapReduce, the de facto standard for large scale data-intensive applications, is a remarkabl...
AbstractThe MapReduce framework has been generating a lot of interest in a wide range of areas. It h...
Abstract. The MapReduce framework has been generating a lot of interest in a wide range of areas. It...
Data abundance poses the need for powerful and easy-to-use tools that support processing large amoun...
International audienceData abundance poses the need for powerful and easy-to-use tools that support ...
MapReduce is a data processing approach, where a single machine acts as a master, assigning map/redu...
have become so complex, and thus computation tools play an important role. In this paper, we explore...
The MapReduce framework has firmly established itself as one of the most widely used parallel comput...
In this paper, we describe efficient MapReduce simulations of parallel algorithms specified in the B...
The emergence of big data has brought a great impact on traditional computing mode, the distributed ...
AbstractRecent innovations in Big Data have enabled major strides forward in our ability to glean im...
MapReduce is a programming model and an associated implementation for processing and generating larg...
In the last two decades, the continuous increase of computational power has produced an overwhelming...
In this paper, we study the MapReduce framework from an algorithmic standpoint and demonstrate the u...
We regard the MapReduce mechanism as a unifying principle in the domain of computer science. Going b...
AbstractMapReduce, the de facto standard for large scale data-intensive applications, is a remarkabl...
AbstractThe MapReduce framework has been generating a lot of interest in a wide range of areas. It h...
Abstract. The MapReduce framework has been generating a lot of interest in a wide range of areas. It...
Data abundance poses the need for powerful and easy-to-use tools that support processing large amoun...
International audienceData abundance poses the need for powerful and easy-to-use tools that support ...
MapReduce is a data processing approach, where a single machine acts as a master, assigning map/redu...
have become so complex, and thus computation tools play an important role. In this paper, we explore...
The MapReduce framework has firmly established itself as one of the most widely used parallel comput...
In this paper, we describe efficient MapReduce simulations of parallel algorithms specified in the B...
The emergence of big data has brought a great impact on traditional computing mode, the distributed ...
AbstractRecent innovations in Big Data have enabled major strides forward in our ability to glean im...
MapReduce is a programming model and an associated implementation for processing and generating larg...
In the last two decades, the continuous increase of computational power has produced an overwhelming...
In this paper, we study the MapReduce framework from an algorithmic standpoint and demonstrate the u...
We regard the MapReduce mechanism as a unifying principle in the domain of computer science. Going b...
AbstractMapReduce, the de facto standard for large scale data-intensive applications, is a remarkabl...