Apache Spark provides a platform for big-data developers intending to bring in one of the most well-rounded systems. It is designed to be used with programming languages like Java, Scala and Python. Spark was created to lessen the workload of people working with vast data.
It can be challenging for developers to process multiple quantities of real-world data. Furthermore, it can get tricky to train an algorithm based on machine learning. Choosing the right course when learning Spark can be a task. Hence, we must devise a way to find out the method that best suits our interests. After all, to learn Spark, you must choose a Big Data Certification course that caters to your best interests.
An Overview of Apache Spark
Apache Spark is a trademark software developed in UC Berkeley's AMPLab in 2009 on account of releasing one of the most significant source communities in big data.
Over 1,000 experts came forward to contribute to this project, thereby making it a successful product. The Apache Software Foundation offers trademark software catering to a large group of developers. Its features include the capacity for multilingual data engineering, machine learning, and data science over single-node machines/clusters.
It supports linking five languages —Python, SQL, Scala, Java and R. You can find SQL analytics and real-time data streaming among its extended features. Spark is renowned for using in-memory caching and optimizing query execution in making fast analytic queries for any data size. It is used explicitly in the distributed processing system for big data workloads.
Top 5 Free Apache Spark Courses to Learn in 2022
If you are wondering how to learn Spark, make it a choice to weigh a few options. After all, different courses have different advantages to offer. While one course may only provide an in-depth understanding of the Spark system, another may have to do with a basic understanding that extends for six months.
It may hinder your progress, making you wait longer to get a certification in Apache's Spark. These reasons can also convince you to look further into what's best. Keeping that in mind, we have curated a list of Apache courses that can simultaneously guide you and enhance your learning experience.
To learn Spark online, you can refer to these courses.
A good thing about Spark is that it supports Scala. Learn Spark and Scala through this model. Spark 2 utilizes Scala as the primary language in a pool of programming languages. Apart from Scala, Python and R remain popular languages that can be adopted by data scientists when working with Apache Spark. In addition, developers using Scala can use Apache Spark since it offers a wide scale of functions.
Spark utilizes high-level APIs in Scala. With features like Spark SQL for SQL and MLib for machine learning, it associates education and programming faster than ever. Using Spark 2, you can develop just about any application for your purpose.
System - You need a computer with a minimum of 4GB RAM and a 64-bit Operating system. All in all, you need a version compatible with Scala 2.11.x.
Skills - You can start with basic programming skills and Scala experience and move on from thereon.
From what is expected of this course, you can get to learn about the big data industry through a parallel between Scala and Spark. Scala and Spark 2, when brought together, bring out the essence of the software. This course analyses Spark's programming model in-depth by differentiating it from other programming models.
Learn Spark programming through this model. A hands-on approach is followed, which ensures areas like distribution and network communication are covered with utmost diligence. Furthermore, you can address these areas using improved performance from Spark. The best way to learn Spark is through a hands-on approach.
- Install Java and JDK
- Setup IntelliJ and add Scala plugin
- Setup Development environment for building Scala and Spark applications
- Integrating IntelliJ using Spark
- Setup sbt to b build scale applications
- Develop a simple scala program
- Build jar file using sbt
- Setup winytils for reading files on windows
- Setup and run Spark job
The main focus of this course is the fundamentals and data structures which find their base in all successful programming. Although most constructs face a depreciation in Spark 2, Scala and Spark still go hand-in-hand. The primary highlight of this course is that it features IntelliJ integration as IDE and uses Scala for amplified performance. Some topics covered across the system are type inference, pattern matching, Scala collections, and standard operations. You can also find Scala types like case classes, options, and tuples, using Spark shell(interpreter, and a guide on avoiding common mistakes.
If you're looking for ways to learn Spark online, here is your chance. One of the most fundamental courses out there, this one boasts an introductory lesson that teaches you the hooks and nooks of Apache. It is a starter kit that introduces you to Apache Spark's mechanism. The main aim of this course is to bring together developers and systems that go hand in hand. The internet holds various crucial information regarding the work-about of Apache Spark. However, it can sometimes get confusing owing to the extensive data.
This course aims to bridge the gap between developers and systems. By introducing learners to key concepts such as Spark's execution engine, this course aims to bring light to the efficient workings of the system. You can expect questions like:
- What is the difference between Hadoop and Apache Spark?
- How does RDD extraction work?
- How does Apache Spark manage to reach fast computation compared to other systems?
- A focus on Hadoop and Spark similarities and differences
- Challenges addressed by Spark
- Strong foundation in RDD
- Program translation in Spark cluster
- Simulation of Master fault tolerance
- Explore Scala's functions and features
Spark and Python H3
One of the most tricky situations can be setting up your local development environment. It is where this course comes to the rescue. If you want to learn spark python, you can go for this API. Python and Spark work together to achieve faster execution and cater to the developer's demands. The Spark Python API, also called PySpark, aims to expose Spark's programming model to Python's programming language. To learn the basics of Scala, we must first refer to a Scala programming guideline. The best way to learn Spark with Python is through a guided approach to both models.
This course takes into account the key differences between Scala and Python APIs. Furthermore, this course effectively lets you install and configure PySpark and indulge in interactive usage. You can also use IPython for PySpark. One advantage of having both Python and Spark together is that you can access API documentation and MLib. The MLib guide can take you through some example applications. Thus, you can learn Spark and Python both through this course.
- Running a single command and waiting for a running distributed environment for cluster deployment
- Python coding for Spark Transformations, Actions and Monitoring
- Automating software installation across multiple Virtual Machines.
4. Apache Spark Fundamentals
What better way to learn about Apache Spark than to read about its foundational course? This program enables you to learn Spark from scratch. This course aims to understand how Big data works and how Hadoop's framework is incompetent in controlling it. It starts with the history of Spark and then continues to form a Wikipedia analysis application.
In doing so, it renders a competitive field to Spark. In turn, this helps learn Apache Spark Core API. Understanding the core library enables you to gain better insight into areas like Spark libraries and SQL APIs. Learn Spark SQL using this course.
- History of Apache Spark
- Apache Spark Core Library
- Spark libraries like Streaming and SQL APIs
- Mistakes to avoid
Hadoop Platform deals with big data and can effectively handle a connection with Spark. Apache's Spark offers a medium for Hadoop Framework to work without causing any significant delay in running the applications. This course provides a hands-on introduction to crucial Hadoop components such as Spark. In this online course, you come eye to eye with 12+ real-world examples using Big data.
- Hadoop Stack and basics
- Introduction to Map/Reduce
- Overview of Apache Spark architecture
- RDD abstraction
- Learn writing Spark applications using PySpark
If you want to learn Spark by example, you can utilize these real-world examples of Big Data simulations.
- Aggregation of NASA Apache Weblogs using different sources
- Exploring price trends by examining real estate Data in California
- Extracting the median salary of developers in remote countries
This list features one of the best free online courses to learn Apache Spark. However, one can always do their research and choose their forte. Spark is one of the most popular and fast-developing systems that gives as much as it boasts. Moreover, it is essential to look for a course that elegantly describes the mannerism of this course.
Since it was developed to provide a smooth platform for people to work on, it has gained massive popularity since its inception. You can find similar courses of your liking by browsing through this list. Alternatively, you can go for this KnowledgeHut Big Data Certification Course if you're searching for versatile options.
Frequently Asked Questions (FAQs)
1. Is it challenging to learn Spark?
Learning Spark can be quite a struggle if you aren't already familiar with a basic understanding of programming languages like Python. However, it can be effortless if you're well-versed with Java, Scala and Python.
2. What is the best way to learn Spark?
To learn Spark, you must follow a guide that ensures the best outcome for you. To achieve this, you can refer to books, online courses, blogs, tutorials and online videos, among other options. You can also choose a range of alternatives, such as certifications and hands-on exercises that track your progress and reward you.
3. How long will it take to learn Spark?
Compared to other learning mediums, Apache Spark only takes about 1.5 to 2 months of rigorous learning. The learning curve for Apache Spark is significantly less compared to other systems. Some people claim to have learned it in a matter of 3 months. It suffices to say that learning Spark won't take up much time.