Top 5 Apache Spark Certifications to Pursue for Career Benefit

Apache Spark’s future is one of significant adoption by businesses of all types and kinds for their personal big data needs. In reality, Apache Spark might merge with other tools that businesses now use to evolve into a necessary big data technology that’s accessible via cloud services.

Alt-Text: Top 5 Apache Spark Certifications to Pursue for Career Benefit

Before Dwelling into The Top 5 Certifications Apache Spark has to offer  let’s first understand What is meant by the term Apache Spark!!

What is meant by the term, “Apache”?

A data processing framework called Apache Spark has the ability to handle very big data sets quickly. 

It can also distribute data processing jobs over a number of computers, either by itself or in conjunction with other distributed computing technologies. 

These two characteristics are essential to the fields of big data and machine learning, which both call for immense computing resources to be mobilized in order to process enormous data warehouses. 

Apache Spark is an open-source platform for quickly and easily processing large amounts of data (big data). It is appropriate for big data analytics applications.

It can also be utilized independently, in the cloud, or in a Hadoop environment. It was created at the University of California, after which the Apache Software Foundation was presented with it.

Also, it is open-source and has a high potential for cost-effectiveness, making it even easier for inexperienced developers to work with Spark’s major objective is to provide developers with an application framework that revolves around a specific data structure. 

Additionally, it  is incredibly strong and naturally adept at processing vast volumes of data in a short amount of time, making it an incredibly powerful tool.

A user-friendly API provided by Spark that abstracts away most of the tedious labor associated with distributed computing and large data processing relieves developers of some of the programming burdens associated with these activities.

A platform for quicker and more versatile data processing is offered by Spark. 

Programming with Spark is up to 100 times faster in memory or 10 times faster on disc than with Hadoop. 

Additionally, Spark allows you to write code more quickly because it has over 80 high-level operators.

Last year, Spark overtook Hadoop as the fastest open source engine for sorting a petabyte of data by finishing the 100 TB Daytona GraySort competition 3 times faster on a tenth as many machines.

Now that you know what is Apache Spark, it is now the time for yet another question:

Why study Apache Spark?

The top Big Data framework, Apache Spark, is currently and for the foreseeable future in high demand. Spark Training is recommended for a rewarding career in this field.

It will represent the following development in the data processing environment because it offers batch and streaming capabilities. 

This would be the perfect framework for you if you’re seeking for quick data analysis. 

Companies are eager to integrate Hadoop and Spark into their systems these days, which will increase the number of chances.

  • HDP Certified Apache Spark Developer

Earning the accreditation of HDP Certified Apache Spark Developer requires extensive knowledge of Python or Scala. As long as they have a reliable internet connection and a camera handy, professionals can sign up to take the exam remotely whenever they choose.

This test evaluates your Hadoop skills by having you execute tasks in a cluster in addition to requiring you to demonstrate your proficiency with Spark.

  • MapR Certified Spark Developer

There is no specified education requirement for the MapR certification. You are permitted to take this exam even if you are not a developer, engineer, or programmer but are interested in working with Spark. The number of questions on programming will range from 60 to 80 in this test.

  • Apache Spark Databricks Certified Developer

To assist people in enhancing their current skill sets, Databricks also offers instructor-led training sessions. Due to the in-depth programming questions that are included on the test, professionals with substantial Scala and Python experience frequently pursue this certification. This test usually takes 90 minutes to complete.

  • Hadoop and Spark Developer for Cloudera

This certification is the best for individuals who are prepared to work with Spark and Hadoop. Your knowledge of subjects like Avro, Sqoop, Impala, Spark with Scala and Python, Flume, HDFS, and Avro will be tested on this exam. Depending on your ability for programming, there will be between 10 and 15 questions.

  • The O’Reilly Developer Apache Spark Certification 

The O’Reilly Developer Apache Spark Certification test includes 40 numerous questions and normally takes 90 minutes to finish. The exam covers best practices operation theory, and computer languages like Java, Python, SQL, and Scala.

Reasons to Choose Apache Spark Certification

  • Apache Spark is expanding the possibilities for exploring large data and making it simpler for businesses to address diverse big data challenges. The majority of data scientists choose to work with Spark, making it the hottest technology right now, not just among data engineers. With applications in both investigative and operational analytics, Apache Spark is an intriguing platform for data scientists.
  • Spark developers are so in-demand that businesses are willing to waive hiring requirements, pay alluring bonuses, and allow flexible work hours in order to secure their services. As of  reports the typical pay for a Spark Developer in San Francisco is $128,000.
  • Businesses are rapidly adopting a variety of complementary big data technologies that work in conjunction with Hadoop and Spark as a result of this. The preferred big data solution for businesses across numerous industries, Spark is no longer only a part of the big data Hadoop ecosystem.
  • According to the survey’s findings, 68% of the firms that have used Apache Spark are utilizing it to handle BI workloads. Enterprise use of Spark is increasing as a result of its distinct value proposition, creating lucrative prospects for big data engineers with Spark and Hadoop expertise.

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