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.
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.
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.