Many companies are looking for the candidates with knowledge on Big data. The candidates who learn big data are earning a decent package in MNCs. However, if you want to make a career in big data, you would need to get trained in the best IT skills Training Institute in Bangalore where they give you in-depth exposure to Big data by making you work on dummy projects. There are few institutes who are offering Hadoop online corporate training in Texas.
Apache Spark is altogether a new processing engine in Big Data. This is highly efficient when compared with the previous engine Map Reduce. If you are taking up machine learning projects, then it is suggested to use Apache Spark. You should have sound knowledge of this processing engine, without which it costs you high. It is important for you to implement this Spark properly in your project to boost the project speed.
To learn Apache Spark Scale, you need to undergo Hadoop certification course. In addition, you also need to work on a couple of real-time projects to gain exposure. Both Spark and Hadoop go hand in hand, since the latter is used to process data while the former one is used to process data into memory. Basically, Spark is replacing the processing engine of Hadoop, Map Reduce. Hadoop is important to understand about Big data, but to secure a job you would need to have knowledge on Spark and Scala. The best thing about Spark is that, it supports both machine learning and streaming data whereas Hadoop does not support. To implement Spark framework, you need to have knowledge of Scala programming language and for Hadoop you would need to use Java language.
Here is how Apache spark is helping to boost knowledge about Big data
Increase access to big data: When you know spark, this opens the door for you to explore more about big data and help organizations solve all the problems related to big data with ease. Spark is the technology that is used equally by data engineers and data scientists. This technology is used to carry out investigative and operational analysis. Many Data Scientists are showing interest to work on Spark as this is allowing them to store data in memory and boost up machine learning process done with Hadoop.
Use big data investments: Many organizations are investing high in doing research on big data. Both HDFS and YARN are common in Spark and Hadoop, but the only difference comes in processing engine and architecture. With the increase in the compatibility of spark with Hadoop, companies are hiring spark developers as they do not need to spend high on computing clusters, since this is integrated with Hadoop. This in turn is driving big data expertise to learn spark by undergoing big data Hadoop certification training.
Learn spark to keep up with the pace of evolving enterprise adoption: Many companies are embracing Hadoop and Spark technologies to develop projects. Spark which is a part of big data, has become an important technology to use in diverse industries. There are lucrative opportunities for aspirants with Hadoop and Spark skills.
Spark and Hadoop are interrelated: The connection of learning Scala and Hadoop is interrelated. For example, if you know the C language, you can learn Java and if you know Java, you can learn Advanced Java, which in turn lets you learn Scala programming language. When you know Hadoop, you can learn Spark with ease thereby enhance your career with Big data Hadoop Development with Spark and Scala