12,510 research outputs found
Multiplicity fluctuations in heavy-ion collisions using canonical and grand-canonical ensemble
We report the higher order cumulants and their ratios for baryon, charge and
strangeness multiplicity in canonical and grand-canonical ensembles in ideal
thermal model including all the resonances. When the number of conserved quanta
is small, an explicit treatment of these conserved charges is required, which
leads to a canonical description of the system and the fluctuations are
significantly different from the grand canonical ensemble. Cumulant ratios of
total charge and net-charge multiplicity as a function of collision energies
are also compared in grand canonical ensemble.Comment: 7 pages, 5 Figs, Published versio
Observations on Factors Affecting Performance of MapReduce based Apriori on Hadoop Cluster
Designing fast and scalable algorithm for mining frequent itemsets is always
being a most eminent and promising problem of data mining. Apriori is one of
the most broadly used and popular algorithm of frequent itemset mining.
Designing efficient algorithms on MapReduce framework to process and analyze
big datasets is contemporary research nowadays. In this paper, we have focused
on the performance of MapReduce based Apriori on homogeneous as well as on
heterogeneous Hadoop cluster. We have investigated a number of factors that
significantly affects the execution time of MapReduce based Apriori running on
homogeneous and heterogeneous Hadoop Cluster. Factors are specific to both
algorithmic and non-algorithmic improvements. Considered factors specific to
algorithmic improvements are filtered transactions and data structures.
Experimental results show that how an appropriate data structure and filtered
transactions technique drastically reduce the execution time. The
non-algorithmic factors include speculative execution, nodes with poor
performance, data locality & distribution of data blocks, and parallelism
control with input split size. We have applied strategies against these factors
and fine tuned the relevant parameters in our particular application.
Experimental results show that if cluster specific parameters are taken care of
then there is a significant reduction in execution time. Also we have discussed
the issues regarding MapReduce implementation of Apriori which may
significantly influence the performance.Comment: 8 pages, 8 figures, International Conference on Computing,
Communication and Automation (ICCCA2016
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