In this Apache Spark tutorial you will learn Spark from the basics to get a clear idea of this top big data processing engine. Apache Spark is a fast in-memory big data processing engine that helps to compute and analyze streaming data in real-time and it is up to 100 times faster than MapReduce. It is a complete engine that is equipped with the capabilities of Machine Learning as well.
This Spark tutorial is meant for Big Data analytics professionals, software developers, IT administrators, Data Scientists and graduates who want to make a career in big data analytics domain.
There are no prerequisites for learning from this Spark tutorial. You can learn Spark better if you have a basic understanding of Java or any other programming language.
|Speed||100 times faster than MapReduce||Equal to the speed of MapReduce|
|Processing type||Stream processing||Batch processing|
|Latency||Low latency due to in-memory processing||High latency due to disk-oriented processing|
Learn Spark in 15 hrs from experts
Spark is a revolutionary big data analytics tool that takes off from where MapReduce left. MapReduce was good up to a certain time, but today the kind of data that we are seeing increasingly getting complex and coming in real fast. So that is where Spark takes on a new role of being the big data processing engine of choice. It has some excellent features like in-memory processing, ability to do massive parallel processing, work for machine learning applications and so. So due to all these features we are seeing a huge deployment of large and small companies constantly deploying Spark and this Spark deployment will only increase in the future.
Spark is a highly versatile big data processing engine. Here we list some of the top applications of Spark cutting across industry verticals.
Spark is the preferred engine of choice for big data problems. Now would be the right time to learn Spark since the market for Spark is just heating up. As we all know Hadoop is slowly being replaced with Spark. Also, Spark has some excellent features making it triumph over Hadoop. Spark works on streaming data, it is very powerful, it has machine learning component and so on. All this makes learning Spark that much more exciting and promising as well. Also, the salaries for Spark professionals are among the best in the technology industry.
As it is widely known in the big data analytics industry, Apache Spark is known as the “Swiss Army Knife” of big data analytics. So from this it is obvious that Spark is an extremely versatile big data engine. It can work for stream processing, batch processing, iterative processing and also used for caching data for better access to data. We can use Spark for machine learning applications as well. The Spark GraphX is an API that is used for graph parallel processing.
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