5 Reasons to Learn Apache Spark Now

Anyone who has worked in Big Data most likely already knows about Spark. Spark is a cluster computing framework for data analytics which handles just about every sort of query on all sorts of data types in a blazing fast speed. The market is budding for spark, with more and more companies now showing interest in adopting Spark. Here are 5 reasons to why you should learn Apache Spark Scala Training the revolutionary latest generation technology.

1# Integration with Hadoop

Spark can be easily and efficiently integrated with Hadoop and that’s a huge advantage for those who are well-versed with Hadoop. In principle, a standalone project, Spark is designed in such a way that it can run on Hadoop Distributed File System, inside MapReduce. It can promptly work with MapR. It can also run on the same cluster along with MapReduce jobs, as it is deployed on YARN.

2# Meets Global Standards

Spark is speculated as the future of global Big Data Processing. The standards of Big Data Analytics seem to be rising enormously with Spark. By learning Spark, you can meet current global standards to assure compatibility between next generation of Spark distributions and applications by becoming a part of Spark Developer’s Community. If you are a tech-junkie, then contributing in the development of Spark technology in its budding stage can give a boost up your career. This way, you can stay abreast with the up-to-the-minute advancements that take place in Spark.

3# Vanishing MapReduce and glinting Spark

Spark is the latest in-memory data processing framework, and it is all set to take charge of all the primary processing for Hadoop jobs in future. Currently, Spark is among the top-level Apache projects as it is much faster and easier to program as compared to MapReduce. Spark is a multi faceted query tool which can help in democratizing the use of big data. The end of MapReduce era is speculated with the growth of Apache Spark training Pune.

4# Spark being readily used in Production

Many companies are already using Spark or are in the planning stage to start using it. In recent past there’s been a massive growth in the popularity of Spark, the reason is its matured open-source components, and the growing community of users. The reason for Spark’s popularity is its embedded high-performance tools and its quick and effortless programming interface in Scala, Python or Java.

Spark is being deployed in production by major Hadoop and even non-Hadoop vendors in multiple sectors, like financial services, media houses, retail, telecommunications and public sector.

5# Massive Demand for Spark Professionals

Spark is still a new technology and it is yet to fully sprawl in the big data market. The use of Spark is growing quickly among many top-notch companies, like Yahoo, Adobe and NASA to name a few. Aside from those who belong to Spark community, there are a handful of professionals who are well-versed with Spark and can work on it. This has created a soaring demand for erudite Spark professionals. In such state of affairs, learning Spark can give you a competitive edge. By learning Spark now you can exhibit the recognized validation for your skills.