Apache Hadoop is an open-source software library used for processing large sets of data across computer clusters using simple programming models. A wide range of companies use Hadoop for production and research. It allows organizations to advance from a single server to thousands of machines while maintaining local storage and computation. Here's some information on how to learn Hadoop and prepare for a job interview once you've mastered your skills.
Udacity's School of Artificial Intelligence and School of Development offer several free courses focused on learning Hadoop:
- Intro to Hadoop and MapReduce – This course gives you a foundation in the fundamental principles of Apache Hadoop and how you can use it to process big data. You also learn how to write MapReduce code to power a web server. The course is taught through Cloudera and takes about a month to complete.
- Deploying a Hadoop Cluster – Continue your study of Hadoop and MapReduce by using them to analyze data. Learn how to use cloud-based Hadoop clusters to gain insights from large datasets. This is a 3-week course.
- Real-Time Analytics With Apache Storm – This could be considered the next step in learning Apache Hadoop, as it focuses on Apache Storm, the "Hadoop of real-time." The 2-week course is taught by Twitter, teaching how Apache Storm processes any big data stream, including tweets, in real-time.
Strengthening Your Job Search Skills
Courses from the Udacity catalog also help prepare you to land the job you're hoping for. Along with several courses that teach interview skills for specific career choices, Udacity's career advancement courses also include the following to help you prepare for your Hadoop interview:
- Refresh Your Resume
- Craft Your Cover Letter
- Optimize Your GitHub
- Strengthening Your LinkedIn Network and Brand
Each course is designed to take from 1 day to 1 week, and they are all free.
Hadoop Interview Questions
Here are the top two Hadoop interview questions (and answers) that you can expect during your interview:
What is big data?
Big data is a very large amount of data that poses problems for the processing capacity of standard databases because it is too big and grows too rapidly. An alternative tool – such as Hadoop – needs to be used to process it. The five Vs of big data are:
- Volume – Large amounts of data grow at an exponential rate, as measured in petabytes and exabytes.
- Velocity – Data is flowing very rapidly due to platforms like social media, streaming, and batch/real-time.
- Variety – Data is available in a variety of structured, unstructured, and semi-structured formats such as audio, video, and CSV.
- Veracity – Data is sometimes incomplete or inconsistent, often due to inaccuracies caused by volume.
- Value – Data is good, but it needs to add benefits to an organization, especially profits.
What Is Hadoop?
Apache Hadoop is a solution to big data. It provides for the efficient and effective distribution of large amounts of data across thousands of machines while detecting and taking care of failures at the application layer. The two main components of Hadoop are HDFS for storage and MapReduce/YARN for processing.