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Top 4 Apache Spark Certifications in 2024

Explore the best Apache Spark certifications to boost your data career. Learn about top programs, exam details, and tips for success.
Jul 2024  · 9 min read

Big data is a rapidly growing field with innovative tools and technologies making it even more promising each day. One such tool, Apache Spark, makes data processing and querying faster and more efficient. 

The demand for Apache Spark is expected to grow by 33% annually between now and 2030. This rising demand drives data professionals to seek Spark certifications and stand out in the job market. The certification not only validates your Spark skills but also opens doors to higher salaries and new career opportunities. 

This article will guide you through some of the best Spark certifications for data professionals at all levels. We’ll also provide tips and resources that help you crack these certification exams.

What is Apache Spark?

Is your model’s training data bigger than your machine can handle? Or have you been running SQL queries that take all night to run? Apache Spark is the solution to these scenarios.

Apache Spark is an open-source distributed computing engine for processing large-scale datasets. But what does ‘distributed computing’ mean here? Spark runs large datasets across multiple nodes in a cluster. These nodes execute different data processing tasks simultaneously and combine the results. 

Let’s look at some of Apache Spark's key features.

  • Speed: Spark offers high-speed execution by utilizing in-memory computing. This means it stores data in RAM instead of on disks during execution stages, allowing for faster access.
  • Built-in libraries: MLlib and GraphX are Spark’s machine learning and graph processing libraries. MLlib contains a wide array of machine learning algorithms, including regression, classification, clustering, and others. GraphX is a growing collection of graph algorithms for graph data processing tasks. 
  • Real-time processing: Spark streaming enables data engineers and data scientists to process real-time data from various sources such as Kafka, Flume, HDFS, and others. This processed data can be pushed to databases, live dashboards, file systems, and reports.
  •  Multi-language support: Though Spark is written in Scala, it also supports Python (PySpark) and Java natively. Moreover, it has SparkR for R programmers and SparkSQL to query data using SQL syntax.
  • Scalability: Spark is built on the concept of cluster computing. So, it is horizontally scalable as more nodes are added to the cluster to handle large datasets. 

Compared to Hadoop, another big data framework, Apache Spark is 100 times faster. 

However, Spark is faster than Hadoop because it uses RAM instead of reading and writing intermediate data to disks. Overall, Hadoop is best for batch processing, while Spark can do both batch processing and real-time streaming.

Benefits of Getting Spark Certified

For professionals looking to establish or advance their careers in the data field, the Spark certification is worth considering. The certification proves your expertise and dedication to the technology. Here are some benefits of pursuing Spark certification:

Apache Spark Certification

Source: Created by ChatGPT

Skill validation

Earning certifications involves a lot of learning effort and consistency. You’ll need to study diligently and pass certain exams for it. This overall process ensures you gain the necessary theoretical and practical Spark skills. 

Career advancement

Getting a job in machine learning or data science fields, especially as a fresher, is tough. However, Spark certification will help you stand out among your peers. These certifications enhance your credibility with employers, leading to better job opportunities or promotions.

Certification programs also provide access to their professional networks, allowing you to make friends with industry experts and uncover more job opportunities. 

Increase in pay

Having a reputable certification gives you an edge over other job applicants. This will give your recruiter another reason to hire you at a higher salary. 

Moreover, certifications show your commitment to continuous learning, making it easier to secure promotions during performance reviews.

Though you can do plenty of courses in Spark, earning certifications from reputable platforms adds significant value. Below, we mention popular Spark certification programs, associated costs, and study material suggestions.  

These details will help you choose the right course tailored to your learning goals and budget.

1. Databricks Certified Spark Developer for Apache Spark

This Databricks certification focuses on applying data manipulation skills using the Spark Dataframe API. They can be selecting, renaming, filtering, dropping, and sorting DataFrame columns. 

Moreover, it emphasizes combining, reading, writing, and partitioning DataFrames with schemas and gives you the ability to work with Spark SQL functions. This certification also assesses your basic Spark architecture knowledge. 

Who it’s for: Data engineers who want to demonstrate their skills in designing, developing, and maintaining data pipelines. The certification is also popular among data scientists using Spark for data processing and building machine learning models.  

Duration: There will be 60 multiple-choice questions in the exam. You’ll have 120 minutes to solve them.

Key topics: Here is the weightage of different topics for the exam.

  • Spark architecture concepts - 10/60
  • Spark architecture applications, including Adaptive Query Execution - 7/60
  • Spark DataFrame API for data manipulation tasks like filtering, sorting, joining tables, and more - 43/60

Cost: $200 per attempt

2. Cloudera Spark and Hadoop Developer Certification

The CCA Spark and Hadoop certification is for data professionals who want to specialize in both Spark and Hadoop. While Spark is known for its computing speed, Hadoop is still in its place for developers needing scalability at a lower cost. 

This certification emphasizes two required skills. The first one is the ability to extract, load, and transform data on HDFS using the Spark API. The second is proficiency in using SparkSQL for data analysis. 

Who it’s for: Ideal for data professionals working in or aspiring to roles that involve both Spark and Hadoop frameworks.

Key topics:

  • Spark Dataframe API 
  • Reading and writing different file formats to HDFS/Hive

Duration: The exam is 120 minutes long and involves solving 8-12 hands-on tasks on the Cloudera platform. It will be graded immediately, and if you score above 70%, you will receive the certificate.

Cost: $295 

3. MapR Certified Spark Developer

MapR Spark certification solidifies your Spark conceptual knowledge and programming capabilities. 

Although the exam contains objective-type questions, there’ll be a lot of code snippets given in Scala, and you have to pick the correct option. This will test your understanding of Spark programming.

Note: This certification strictly demands programming in Scala, not Python.

Who it’s for: This program is ideal for data professionals working in or aspiring to roles that involve both Spark and Hadoop frameworks.

Key topics: 

  • Creating and using Resilient Distributed Datasets (RDDs)
  • Creating and executing simple Spark applications 
  • Pair RDDs
  • DataFrame operations
  • Understanding the Spark execution model and configurations for optimization
  • Spark Streaming
  • Machine learning concepts in Spark  

Duration: 120 minutes

Cost: $250

4. HDP Certified Developer (HDPCD) Spark certification

Hortonworks was a data company that developed open-source platforms around Apache Hadoop for storing and processing large datasets. In 2019, Hortonworks merged with Cloudera. 

Their product, HDP (Hortonworks Data Platform), is designed to process big data in a distributed computing environment. If you decide to earn this certification, familiarize yourself with the HDP environment, as the exam will be conducted on this platform. 

This Hortonworks certification tests your proficiency in Spark Scala Application, RDD, Broadcast Variables, Accumulators, RDD transformations, RDD Actions, DataFrames, SparkSQL, and more.

Who it’s for: This certification helps all the analytics, Spark developers, data engineers, and data scientists in various industries.

Key topics:

  • Spark sessions and RDDs
  • Broadcast variables and accumulators
  • Configure Spark properties
  • Create simple Spark applications in Python or Scala
  • Create SparkSQL applications 
  • Read and write Hive tables using SparkSQL 

Duration: 120 min

Cost: $250

Comparison of Spark Certifications

We’ve collated all the essential information about the Spark certifications in the table below, helping you choose the one that’s right for you: 


Who it's for

Key Topics



Databricks Certified Spark Developer for Apache Spark

Data engineers and data scientists

- Spark architecture concepts - Spark architecture
- Spark DataFrame API for data manipulation tasks 

60 multiple-choice questions 120 minutes


Cloudera Spark and Hadoop Developer Certification

Data professionals working with or aspiring to work with Spark and Hadoop frameworks

- Spark DataFrame API
- Reading and writing different file formats to HDFS/Hive

8-12 hands-on tasks 120 minutes


MapR Certified Spark Developer

Data professionals working with or aspiring to work with Spark and Hadoop frameworks

- Creating and using Resilient Distributed Datasets
- Creating and executing simple Spark applications
- Pair RDDs
- DataFrame operations
- Understanding the Spark execution model and configurations for optimization
- Spark Streaming
- Machine learning concepts in Spark

Objective-type questions with code snippets 120 minutes


HDP Certified Developer (HDPCD) Spark Certification

Analytics, Spark developers, data engineers, and data scientists in various industries

- Spark sessions and RDDs
- Broadcast variables and accumulators
- Configure Spark properties
- Create simple Spark applications in Python or Scala
- Create SparkSQL applications
- Read and write Hive tables using SparkSQL

120 minutes


Preparing for Spark Certification Exams

Now you know what exams to clear for becoming a certified Spark developer. Preparing for these exams involves learning core Spark concepts, SparkSQL topics, and hands-on programming with sample data. 

Many online courses, books, and tutorials can help you prepare for Spark certification. Here are some popular resources you can use to study Spark.

Online courses

DataCamp offers an array of courses on Spark. Below are some course recommendations from various platforms.

Tips for effective preparation

Including the following tips during preparation increases your chances of clearing the exam or even scoring higher. 

Know the exam format

Before you start preparing, research the exam format, the weightage of different topics, and the marks distribution. Knowing the entire outline of the exam paper gives you a clear target for what to study. 

Find answers to questions like the different formats of questions asked, the duration of the exam, the passing score, and other criteria.

Make a study plan

An effective study plan helps you achieve your learning goals by the exam time. The first thing you should do is to block your work commitments and personal activities in your calendar. This will give you an estimate of how much time you’re left with to prepare for the certification. 

Now adjust the topics, practice exams, and study sessions into your free time blocks and put a reminder to notify you every day when it's your focus study time. This way, you can break down the entire syllabus into manageable chunks. 

Practice exams

Most professional certifications, like HDP Spark certification or Cloudera Spark certification, test your practical skills. So, practicing what you’ve learned through multiple mock tests is as important as studying the material. 

Through these exams, you can assess your weak points and identify strong areas. Adjust your learning based on these insights for effective exam preparation. 

Join study groups

Joining different study groups and discussing queries there helps you understand where you stand among your peers. 

You can also find a study partner through these groups. Having a study partner keeps your preparation enthusiastic and accountable.

How to Register and Take the Exam?

The registration process for exams differs depending on the certification provider you choose. Here’s a general guide on how to register, using the Databricks Spark certification exam as an example.

Step 1: Open the Databricks website.

Step 2: Click on the certification platform link provided under the ‘Registration’ section.

Databricks Spark Certification platform

Source: Databricks

Step 3: Open the link as shown in the picture below and fill in all your details to create a new account on the platform.

Databricks Spark Certification

Source: Databricks 

Step 4: Now login to your account, and click on ‘Register for an Assessment’, and schedule your exam. 

When the exam day arrives, make sure you log in to the test platform early with all the system requirements satisfied. 

Most certification exams give you insights into the type of questions and study materials you should use. If you have covered those concepts and practiced the exam format questions well, you’re more likely to pass the test.

If your exam includes hands-on tasks along with objective questions, practice using the provider's platform to familiarize yourself with the environment. This will help avoid any surprises on exam day.

Post-Certification: Next Steps

Certified candidates have approximately a 25% higher probability of finding a job. Professional certifications are a testament to your expertise and show your commitment to your field. They keep you updated with the latest trends and best practices in the industry. 

Once you receive your certification, post it on your LinkedIn profile. This way, the world out there will know that you are certified in Spark, and there is a probability that a recruiter will reach you if there is a vacancy in their firm. However, it depends on your LinkedIn connections and overall LinkedIn profile as well.

Additionally, add the certification to your resume. Create a dedicated section for this and highlight your professional certificates there. 

Alongside your resume, having a relevant portfolio increases your chance of getting hired. You can use Datacamp’s free portfolio builder to make professional-looking portfolios. The tool has a separate section for adding your professional certificates.

This is not the end of your learning. Continuously expand your skill set within the data field and get certified in them as well. You can also prepare for more advanced certifications in Spark. The more professional certifications you earn, the more valuable you are to the industry.

DataCamp Learning Resources as an Alternative

Of course, there are plenty of other alternatives to Spark certifications that may fit your time, budget, and ambitions much better. 

DataCamp Certifications

While traditional certifications offer a broad perspective, role-based certifications, like those from DataCamp, deliver focused learning paths customized for distinct job roles.

DataCamp provides certifications in Python, SQL, and R, specifically tailored for various professional roles. These certifications are comprehensive and rigorous, honing in on the critical skills necessary for each position:

  • Data Scientist (Associate & Professional): This certification assesses competencies in data management, programming, statistical experimentation, exploratory analysis, model development, and communication—skills vital for data scientists.
  • Data Analyst (Associate & Professional): For data analysts, the certification evaluates abilities in data management, exploratory analysis, visualization, analytics fundamentals, and communication.
  • Data Engineer (Associate): Concentrating on the backend of data pipelines, this certification tests skills in data management, programming for data engineering, and exploratory analysis.

DataCamp’s role-specific certifications not only provide a structured learning path but also offer a benchmark for learners to measure their skills against industry standards.

Advantages of DataCamp courses

DataCamp offers courses with a comprehensive curriculum, including both video tutorials and blogs that cover all aspects of Apache Spark. The platform also features an interactive integrated development environment (IDE), allowing you to write and execute code directly from your browser.

  • Beginner-friendly approach: DataCamp courses are designed to be accessible for beginners. They start with fundamental concepts and gradually progress to the level specified by the course, whether it is introductory or intermediate.
  • Highly structured learning paths: DataCamp provides well-organized tracks, such as the Spark track, which sequences courses in an optimal order for effective learning.
  • Flexibility and practical application: These courses are self-paced, enabling you to learn at your convenience from anywhere and at any time. Additionally, each course includes real-world projects to help you apply your knowledge to practical scenarios.
  • Certification and community access: Upon completing a course or track, you will receive a certificate instantly. Moreover, you will have access to DataCamp's global community, enhancing your learning experience and networking opportunities.

Key DataCamp courses for Spark

How can DataCamp help with Spark Certification Preparation?

At DataCamp, all video tutorials are developed by industry experts, ensuring the courses cover all the necessary details to prepare you for most certifications. The courses emphasize hands-on learning with interactive coding exercises, which are invaluable for mastering the practical components of certification exams.

DataCamp Spark courses

Another significant advantage of DataCamp courses is the vibrant community. Unlike other online tutorials or YouTube channels, where resolving doubts can be challenging, DataCamp offers community support and discussion forums. These platforms enable you to discuss and resolve queries effectively.

DataCamp courses include skill assessment tests, allowing you to track your learning progress and build confidence. These tests also familiarize you with the exam environment, enhancing your readiness for certification exams.


The Spark certification offers a unique opportunity to demonstrate your skills to the world. So, be wise when choosing a certification program. For maximum recognition, we recommend getting certified by a reputable platform. You may also choose the certification program based on the weightage of different Spark topics. 

If you are starting out your Spark journey today, DataCamp's introduction to PySpark course is an excellent starting point.

Photo of Srujana Maddula
Srujana Maddula

Srujana is a freelance tech writer with the four-year degree in Computer Science. Writing about various topics, including data science, cloud computing, development, programming, security, and many others comes naturally to her. She has a love for classic literature and exploring new destinations.


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