Posted on Aug 14
Everything You Should Know About Apache Spark for Careers
Introduction
The world is gradually starting to understand the need to analyze and process data. Data processing and analysis are needed in different areas to identify patterns and trends that affect consumer behaviour and patterns. This is why the Apache Software Foundation has created Apache Spark which we will look into in the coming sections of this article.
In this article, you will learn what Apache Spark is and how it works. You will also learn about Apache Spark’s relevance in the modern workplace. Keep reading to find out more.
What is Apache Spark?
Apache Spark is an open-source analytics framework useful in large-scale data processing and machine learning. It also provides a platform for real-time stream processing and data grouping. Apache Spark is fast and handles these processes in no time just as its name implies.
The grouping nature of Apache Spark makes it easy for the framework to handle large-scale data fast. Companies such as Apple, Visa, TikTok, and Salesforce use Apache Spark to manage and analyze their data.
Apache Spark is a multi-language system that helps people practice data science and data engineering.
How Apache Spark Works and Its Relevance in the Modern Workplace?
Apache Spark operates a unified data-processing system. Here is a step-by-step description of how Apache Spark works;
- Apache Spark takes the large-scale data it is fed with and divides them into small ‘bits’. This is so that it works the data easily when they are in small groups.
- The system sends these groups of data to different nodes or computers. Each computer will work in its group simultaneously for speed and efficiency.
- Once the data is split, users can perform actions on each group. This is called transformations or actions in Spark.
- Apache Spark can handle problems or issues by moving difficult work to another node. This further proves that Apache Spark can handle issues without crashing.
Apache Spark also has a reliable memory that can keep data. It performs in-memory processing which makes it faster and efficient.
Learning Apache Spark
Learning Apache Spark skill may be a herculean task but it is achievable. If you are into learning online, you can learn Apache Spark on Coursera or Udemy. Different courses are available for you whether you are looking at a beginner-friendly or advanced level.
Another platform to learn Apache Spark is the Spark Offical Documentation. They have detailed tutorials and guidelines that you can leverage on. Anything from basic to advanced level will be available on the platform.
You can also get books on Apache Spark. An example is Learning Spark" by Holden Karau, Andy Konwinski, Patrick Wendell, and Matei Zaharia. You can get it on Amazon or Google Books.
There are online Spark communities that you can connect with to learn and ask questions. You may also get opportunities from there.
Career Paths and Prospects for Apache Spark Skills
If you are thinking of the career paths and prospects that you can use Apache Spark skills, here is a list of them below;
- Data Scientist
- Data Engineer
- Big Data Analyst
- Solution Architect
- iOS Engineer
- Software Engineer
- Cloud Field Engineer
- Brokerage Operations Associate
Remote Jobs for Apache Spark
W
Internet Software & Services Company
Tech Lead, Wikidata PlatformSummaryThe Foundation is looking for a collaborative technical lead to guide the sustainment, develo
Apr 22
N
Financial Services / FinTech Company
Senior Data EngineerRemote (Kenya, Nigeria, USA) Who We AreOur software is an AI-driven platform transforming clima
Apr 15
K
Financial Services / FinTech Company
Data Scientist - Financial Fraud DetectionLagos, Lagos, Nigeria Summary Our software is a money app for Africans on a mission to mak
Mar 27
N
Financial Services / FinTech Company
Senior Data ScientistRemote (Nigeria, Kenya, USA) Who We AreOur software is an AI-driven platform transforming clima
Mar 25
P
Advertising Company
AI EngineerLocation Algeria, Angola, Cameroon, Egypt, Democratic Republic of the Congo, Ethiopia, Ghana, Kenya,
Mar 13
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