Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: RDD-Eclat: Approaches to Parallelize Eclat Algorithm on Spark RDD
  Framework   Initially, a number of frequent itemset mining (FIM) algorithms have been
designed on the Hadoop MapReduce, a distributed big data processing framework.
But, due to heavy disk I/O, MapReduce is found to be inefficient for such
highly iterative algorithms. Therefore, Spark, a more efficient distributed
data processing framework, has been developed with in-memory computation and
resilient distributed dataset (RDD) features to support the iterative
algorithms. On the Spark RDD framework, Apriori and FP-Growth based FIM
algorithms have been designed, but Eclat-based algorithm has not been explored
yet. In this paper, RDD-Eclat, a parallel Eclat algorithm on the Spark RDD
framework is proposed with its five variants. The proposed algorithms are
evaluated on the various benchmark datasets, which shows that RDD-Eclat
outperforms the Spark-based Apriori by many times. Also, the experimental
results show the scalability of the proposed algorithms on increasing the
number of cores and size of the dataset.

12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
22
The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat