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Spark is an open source processing engine built around speed, ease of use, and analytics. Apache Spark, a fast moving apache project with significant features and enhancements being rolled out rapidly is one of the most in-demand big data skills along with Apache Hadoop. A Spark project contains various components such as Spark Core and Resilient Distributed Datasets or RDDs, Spark SQL, Spark Streaming, Machine Learning Library or Mllib, and GraphX. With businesses generating big data at a rapid pace, analysing the data to leverage meaningful business insights is the need of the hour.


What is Big Data?

It is a huge volume of data that can not be processed with traditional databases like relational databased.

The reason is,

• The data that are collected is very very huge

• It is completely unstructured (i.e.) chats, etc.

Let’s consider this example,

• If you running a e-commerce website, imagine how many orders are placed every second and how many visitors are viewing different products every second. All this data are captured by our back end.


Top Reasons and Advantages to Learn Apache Spark Online

To Increase Access to Big Data Technologies


Apache Spark is opening up various opportunities for big data exploration and making it easier for

organizations to solve different kinds of big data problems. Spark is the hottest technology now, not just

among the data engineers but even majority of data scientists prefer to work with Spark. Apache Spark is a fascinating platform for data scientists with use cases spanning across investigative and operational analytics.

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Data scientists are exhibiting interest in working with Spark because of its ability to store data resident in

memory that helps speed up machine learning workloads unlike Hadoop MapReduce. Apache Spark has

witnessed continuous upward trajectory in the big data ecosystem.


To witness an increasing demand for Spark Developers

Similar to Hadoop, Apache Spark also requires technical expertise in object oriented programming

concepts to program and run- thus opening up job opportunities for those who have hands-on working

experience in Spark. Industry-wide Spark skills shortage is leading to a number open jobs and contracting

opportunities for big data professionals. 

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Benefits of Apache Spark and Scala to Professionals 

• Provides highly reliable fast in memory computation.

• Efficient in interactive queries and iterative algorithm.

• Fault tolerance capabilities because of immutable primary abstraction named RDD.

• Inbuilt machine learning libraries.

• Provides processing platform for streaming data using spark streaming.

• Highly efficient in real time analytics using spark streaming and spark sql.

• Graphx libraries on top of spark core for graphical observations.

• Compatibility with any api JAVA, SCALA, PYTHON, R makes programming easy.

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Real-Time Stream Processing

Apache Spark has a provision for real-time stream processing in Big Data environment. Earlier the

problem with Hadoop MapReduce was that it can handle and process data which is already present, but

not the real-time data. By using the Spark Streaming we can solve this problem easy and quickly 


It Supports Multiple programming Languages

In Spark Application, there is Support for multiple programming development languages like Java, R, Scala, Python. Thus, it provides dynamicity and overcomes the limitation of Hadoop that it can build applications only in Java.



In conclusion, Apache Spark is the most advanced and popular product of Apache Community that provides the provision to work with the streaming data, has various Machine learning library, can work on structured and unstructured data, deal with graph etc.


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