Nowadays, MapReduce has become an effective tool for large scale data analysis. It is naturally designed for group-by aggregation tasks rather than join operator which is common in real analysis works. The existing join methods in MapReduce may earn different performances in different cases, which makes how to choose a good join plan from a join list difficult. The current static optimization can't generate an efficient evaluation plan for a given join list. In this paper, we will introduce some custom join technologies and then propose an adaptive join plan generator for multiple join depending on both rule-based model and cost-based model considering the intermediate data. ? 2012 IEEE.EI
AbstractJoin-aggregate is an important and widely used operation in database system. However, it is ...
The MapReduce framework is increasingly being used to analyze large volumes of data. One important t...
Multiway join queries incur high-cost I/Os operations over large-scale data. Exploiting sharing join...
AbstractFor over a decade, MapReduce has become a prominent programming model to handle vast amounts...
For over a decade, MapReduce has become the leading programming model for parallel and massive proce...
MapReduce has become an attractive and dominant model for processing large-scale datasets. However, ...
ABSTRACT: In the current technological world, there is generation of enormous data each and every da...
The MapReduce framework has been widely used to process and analyze large-scale datasets over large ...
For over a decade, Map/Reduce has become a prominent programming model to handle vast amounts of raw...
MapReduce is a programming model which is extensively used for large-scale data analysis. The join o...
International audienceMapReduce has become an increasingly popular framework for large-scale data pr...
In the era of data deluge, Big Data gradually offers numerous opportunities, but also poses signific...
This paper introduced a method for producing immediate and result in multi-join query, in homogeneou...
International audienceMapReduce model is a new parallel programming model initially developed for la...
Abstract — Adaptive join algorithms have recently attracted a lot of attention in emerging applicati...
AbstractJoin-aggregate is an important and widely used operation in database system. However, it is ...
The MapReduce framework is increasingly being used to analyze large volumes of data. One important t...
Multiway join queries incur high-cost I/Os operations over large-scale data. Exploiting sharing join...
AbstractFor over a decade, MapReduce has become a prominent programming model to handle vast amounts...
For over a decade, MapReduce has become the leading programming model for parallel and massive proce...
MapReduce has become an attractive and dominant model for processing large-scale datasets. However, ...
ABSTRACT: In the current technological world, there is generation of enormous data each and every da...
The MapReduce framework has been widely used to process and analyze large-scale datasets over large ...
For over a decade, Map/Reduce has become a prominent programming model to handle vast amounts of raw...
MapReduce is a programming model which is extensively used for large-scale data analysis. The join o...
International audienceMapReduce has become an increasingly popular framework for large-scale data pr...
In the era of data deluge, Big Data gradually offers numerous opportunities, but also poses signific...
This paper introduced a method for producing immediate and result in multi-join query, in homogeneou...
International audienceMapReduce model is a new parallel programming model initially developed for la...
Abstract — Adaptive join algorithms have recently attracted a lot of attention in emerging applicati...
AbstractJoin-aggregate is an important and widely used operation in database system. However, it is ...
The MapReduce framework is increasingly being used to analyze large volumes of data. One important t...
Multiway join queries incur high-cost I/Os operations over large-scale data. Exploiting sharing join...