With the ever-increasing volumes of data being generated in the world today, businesses are constantly in need of more robust analysis tools as the traditional tools lack the capacity to analyze big data effectively. Some big data analytics solutions developed so far include Hadoop, which is best suited for batch processing. Apache Spark, Apache Storm, and Apache Splunk for real-time and stream processing. Apache Drill for interactive processing, primarily used for analyzing social media data from posts, comments, and other forms of interaction.
At the basic, a big data professional should pursue a Big Data Hadoop and Spark Developer course, as these are the most in-demand skills. Apache Spark has been gaining attention over the years as data trends are changing. The high velocity with which data is being generated continues to pressure businesses to seek an analytics solution of equal measure, thus the need for effective stream processing tools like Spark.
Why Apache Spark is popular
Apache Spark is a powerful open-source in-memory data analytics software designed to perform both batch and stream analytics on large datasets on the Hadoop platform; thus, it is well compatible with Hadoop and therefore works well with Hadoop Distributed File System (HDFS) and others. It features high-level APIs on Java, Scala, R, and Python and supports Spark SQL for structured data processing, GraphX for graph processing, MLib for machine learning, as well as structured streaming.
In essence, Spark is an upgrade to Hadoop’s analytics capabilities. Spark employs a cluster-computing model that guarantees fast parallel computing and fault-tolerance. It has been built, like MapReduce, as a processing layer on top of Hadoop. However, it comes with faster performance compared to MapReduce thanks to its in-memory processing.
Apache Spark Developer Salary in India & United States (US)
In India, an entry-level Spark Developer earns between Rs 500,000 to Rs 1,000,000 per annum, while an experienced level Spark Developer, the salary ranges between Rs 2,500,000 to Rs 4,000,000 per annum.
A beginner-level Spark Developer’s salary is $70,000 to $100,000 per annum in the USA. An experienced level Spark developer, the salary ranges between $140,000 to $175,000 per annum.
Becoming an Apache Spark Developer
Due to its consistently superior computational performance and reliability, the demand for Spark skills is high and rising. Spark has been adopted by big names like Yahoo, NASA, Adobe, and Alibaba for various purposes, including stream processing, real-time monitoring, and advanced analytics. Thus, with the demand for Apache Spark skills, Spark developers are highly sought. How does one become a Spark developer?
Here are a step-by-step guide and valuable tips to help you as a beginner curve your career path as a Spark developer.
What do you know about Spark?
The resourceful Spark documentation on Apache Spark’s website contains information about Spark, how it works, its features, functionalities, and some illustrations to help you understand Spark concepts. This should be your starting point to learning about Spark.
The Apache Spark official YouTube channel also has some valuable tutorials on how Spark works.
Build your programming language skills
Spark supports a range of high-level languages like Scala, Python, R, and Java. If you are considering building your programming skills, these are the languages to start with. After learning programming languages, go ahead and learn how to work with PySpark, Spark’s interface that allows you to write applications in Spark and perform several other functions.
You already know your way around Spark Architecture; it is time to get deeper learning about the various components of Spark and their functionalities. These include SparkSQL for structured data processing, SparkML-Lib, the machine learning module, Spark GraphX for graph processing, and Spark streaming.
Take some training to learn about core Apache Spark concepts
It is not enough to have general knowledge. Get the required training for Spark developers to advance your knowledge and application. Cloudera’s CCA-175 Spark and Hadoop developer certification should be your top priority.
Your project portfolio
It is important to remember that hands-on skills are more valuable in the spark developer job market. Recruiters are keen on hiring developers that can apply their knowledge effectively. Once you take up the certification training, familiarize yourself with Spark terminology and begin working on your projects. Spark’s developer building block is the Resilient Distributed Datasets (RDDs). Learn about various data frames like PySpark and how to use them to develop RDDs.
More knowledge, Spark Resources
There are plenty of books, tutorials, and blogs online and offline for all Spark skill levels to help you get in-depth knowledge about Spark. Books like Learning Spark by Holden Karau, High-Performance Spark: Best Practices for Scaling and Optimizing Apache Spark by Holden Karau, and Mastering Apache Spark: For Beginners are packed with easy-to-understand content, practical, real-life illustrations, and Spark use cases to help you gain an in-depth understanding of Spark.
Another valuable resource to check out is the video recordings from Spark summits that take place annually. These videos will keep you updated on industry trends, expert opinion, and Spark new features.
Spark is a powerful and versatile processing engine built to handle a range of tasks on large volumes of data. It is compatible with Hadoop HDFS and features an impressive computational speed thanks to its in-memory data. Acquiring Spark developer skills will give you an edge because more and more companies across various domains are adopting Spark as their core processing engine. However, before taking a leap into learning Spark, consider having some basic knowledge of statistics, machine learning, databases like NoSQL, the Hadoop ecosystem, Scala, and Java programming languages that are core to Spark developers and application engineers. The bottom line is that a world of opportunities awaits, but you will have to keep demonstrating practical knowledge.
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