Hadoop: Map Reduce
This course allows beginners to learn the basics of Hadoop Map Reduce, a powerful interactive charting technique. With Seaborn and Cufflinks, you will learn the basics of data visualization and create interactive charts.
What you learn in Hadoop: Map Reduce ?
About this Free Certificate Course
This Hadoop Map Reduce course is designed for beginners to learn the basics of data processing technology. The course will give you an understanding of the Map Reduce programming model and the underlying logical data flow. It also comprehends record reader, mapper, sort, shuffle, and reducer techniques and helps you understand the MapReduce framework. You will then gain skills to implement Cufflinks and Seaborn library to learn data visualization techniques using interactive charting techniques.
The free online course is easy to follow and provides a detailed introduction to the fundamentals of Hadoop Map Reduce. After completion, learners will receive a free certificate to demonstrate their mastery of the subject.
A Data Science certificate course is a great way to learn data processing tools and technologies and get up-to-speed with the industry's most influential technology.
Course Outline
This section explains how Hadoop MapReduce serves as a framework for writing codes for applications that process vast amounts of data on large clusters. It also discusses its programming model that processes massive datasets across computer clusters and its application feature that stores data in distributed form.
This section demonstrates how Hadoop Map Reduce assigns data across nodes in the cluster, splits the data into chunks, and uses an algorithm to process them in parallel. This section also explains how it increases the pace of handling vast-size data in petabytes while processing on multiple machines.
This section explains how Hadoop 1,x uses HDFS to store data. It also discusses the role of MapReduce in Resource Management and Data Processing. It then compares Hadoop 2, YARN, with HSFS in Resource Management and data storage.
This section guides you in configuring files located in extracted tar.gz files in the etc/Hadoop/directory. It then discusses HADOOP-ENV.sh specifications of the platform variables affecting JDK used by Hadoop Daemon (bin/Hadoop).
With this course, you get
Free lifetime access
Learn anytime, anywhere
Completion Certificate
Stand out to your professional network
2.0 Hours
of self-paced video lectures
Frequently Asked Questions
What are the prerequisites required to learn MapReduce in Hadoop?
This is a beginner-level course and requires no prior knowledge to learn from it. The course teaches Hadoop Map Reduce from basics.
How long does it take to complete this free Hadoop Map Reduce course?
This is a 2-hour-long free course. You can, however, take the course at your leisure and complete the quiz to gain a course completion certificate.
Will I have lifetime access to this free Hadoop Map Reduce online course?
Yes. You will have lifetime access to this free online course. Enroll in the course today and come back at your leisure to revise the course.
What are my next learning options after this course?
Data Science and Big Data Analytics course will escalate your learning to a professional
Why is it essential to learn MapReduce?
MapReduce is an essential tool for processing and analyzing large datasets. It is used for data analysis tasks such as sorting, aggregating and joining big data sets. It is used to process data in a distributed computing environment, which means it can use parallel processing to speed up the analysis. It is also used for Machine Learning applications such as clustering and classification. In addition, MapReduce can be used to build efficient distributed applications.
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Hadoop: Map Reduce
Hadoop: Map Reduce is a key component of the Hadoop ecosystem, providing a distributed computing framework for processing large amounts of data. Map Reduce is designed to process big data in a parallel and distributed manner, making it a powerful tool for data engineers, data scientists, and business analysts.
The free course on Hadoop: Map Reduce will introduce you to the fundamentals of Map Reduce, including the map-reduce approach and the different phases of the map-reduce process. You'll also learn about HDFS (Hadoop Distributed File System), including the differences between HDFS in Hadoop 1.x and Hadoop 2.x, as well as YARN (Yet Another Resource Negotiator), a key component of Hadoop 2.x.
Additionally, the course will cover HDFS configuration files, giving you the knowledge and skills you need to effectively configure and manage HDFS in a Hadoop cluster. You'll also see a demonstration of Map-Reduce in action, allowing you to gain hands-on experience with one of Hadoop's most powerful tools.
Whether you're a beginner or an experienced data professional, this course will provide you with the knowledge and skills you need to effectively use Hadoop: Map Reduce for big data processing. With its focus on hands-on learning, you'll be able to immediately apply what you've learned to real-world problems and make a real impact in your work.
In conclusion, the free course on Hadoop: Map Reduce is an excellent starting point for anyone looking to gain a deeper understanding of Hadoop and big data processing. Don't miss this opportunity to expand your skill set and advance your career.