Sujoy Saraswati

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Atomic sections have been recently introduced as a language construct to improve the programmability of concurrent software. They simplify programming by not requiring the explicit specification of locks for shared data. Typically atomic sections are supported in software either through the use of optimistic concurrency by using transactional memory or(More)
Today there are plenty of frameworks to assist the development of Big-data applications. Computation and Storage are two major activities in these applications. Spark framework has replaced Map-Reduce in Hadoop, which is the preferred analytics engine for Big-data applications. Java Virtual Machine (JVM) is used as execution platform irrespective of which(More)
Now a day's data is growing very rapidly, where processing and analyzing data to get useful information is the main task. There are many big data processing tools and framework such as Hadoop, Hive, Cassandra etc. Spark is one of the fastest big data processing framework in cluster computation. Basic Idea is to analyze the performance of java virtual(More)
Distributed applications for data analytics have emerged to be a significant growth domain both in terms of technology as well as business relevance. With the advent of Hadoop MapReduce, several distributed execution frameworks have been developed for data analytics and machine learning applications. Many of these frameworks are written in Java, Scala or(More)
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