… Analysing the network data features provide a means for … analysis of network data using
Spark streaming technology which focuses on real time stream processing, built on top of Spark. …

… It is clear from table 2 that when we used dataset-1 using spark then the Accuracy of Random
… (93.08%) algorithms was equally high so both were the winners in Accuracy using spark. …

… Then we propose a Spark-based framework for learning deep models for time-efficient MBD
analytics within large-scale mobile systems. We present experimental analysis using a real-…

… to process large size of network traffic data as quickly as possible in … used Apache Spark,
a big data processing tool for detecting and analysis of intrusion in the communication network …

… For example, the social network Twitter generated in January 2013, 7 terabytes of … article
we used Apache Spark for analysis Twitter data. As obtained in our experimental setup, Spark …

… In particular, we focus on Spark and Flink as representative data analytics frameworks… Spark
lies in the mandatory settings for the network buffers, used to store records or incoming data …

… Recently updated for Spark 1.3, this book introduces Apache Spark, the open source … data
analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through …

… The main goal of this work is to propose architecture and workflow able to process social
network data in near real-time. The primary purpose of the introduced modern architecture …

… using the internally defined library of Spark, or the MLP can be generated by creating the
Artificial Neural Network … -propagation network to continuously train the network and reduce the …

… Spark. We introduce recursion operators and data structures to efficiently implement the
technique in Spark… Nodes of the cluster are connected with 1Gbit network. Our implementation is …