Updated 27 Aug
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Introduction to Big Data and Hadoop
Delve into Big Data essentials, explore data types, and gain insights into Hadoop components like YARN, MapReduce, HDFS, and Spark. Discover foundations to excel in the growing Big Data field.
4.5
96 lessons
1 AI mock interview
10h
Created by DataJek
What's included
- 96 lessons across 12 modules
- 30 quizzes with instant feedback
- 1 AI mock interview with scoring rubrics
- AI Tutor on every lesson
Join 3.1 million developers at
What You'll Learn
- Define Big Data using volume, velocity, variety, veracity, and value
- Differentiate structured, semi-structured, and unstructured data in SQL and NoSQL contexts
- Compare Big Data systems and data warehouses to choose appropriate use cases
- Explain YARN components and workflow for container allocation, scheduling, and high availability
- Build, test, and run MapReduce jobs on HDFS with mappers, reducers, partitioners, and combiners
- Use HDFS architecture and CLI/admin commands to store, replicate, and manage distributed files
- Develop and monitor Spark applications using RDDs, DataFrames, Datasets, and YARN deployment modes
Learning Roadmap
1.
Hadoop
Hadoop
Get familiar with Hadoop’s role in Big Data, its evolution, and core terminologies.
2.
YARN
YARN
Walk through YARN's resource management, workflow, and scheduling for efficient cluster operation.
3.
Map Reduce
Map Reduce
12 Lessons
12 Lessons
Examine MapReduce's programming model, mapper, reducer, testing, execution, and resiliency in big data.
4.
HDFS
HDFS
11 Lessons
11 Lessons
Enhance your skills in HDFS architecture, from filesystem fundamentals to practical commands.
5.
Spark
Spark
11 Lessons
11 Lessons
Deepen your knowledge of Spark’s architecture, APIs, RDDs, DataFrames, and execution workflow.
6.
Input & Output Formats
Input & Output Formats
12 Lessons
12 Lessons
Follow the process of exploring input and output format efficiencies through SequenceFile, Avro, and Parquet.
7.
Misc
Misc
5 Lessons
5 Lessons
Master the steps to utilizing Zookeeper and Pig for managing distributed systems and parallel data processing.
8.
Quiz
Quiz
6 Lessons
6 Lessons
Get familiar with core Big Data and Hadoop concepts through structured quizzes.
9.
Reference: Replication
Reference: Replication
14 Lessons
14 Lessons
Unpack the core of data replication techniques, consistency, latency, and conflict resolution in distributed systems.
10.
Reference: Partitioning
Reference: Partitioning
4 Lessons
4 Lessons
Explore partitioning strategies to enhance scalability, fault tolerance, and query performance.
11.
Reference: Transactions
Reference: Transactions
9 Lessons
9 Lessons
Find out about database transaction concepts and strategies for maintaining data integrity.
12.
Reference: Issues in Distributed Systems
Reference: Issues in Distributed Systems
4 Lessons
4 Lessons
Deepen your knowledge of complexities in distributed systems, network issues, and time synchronization.
Certificate of Completion
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About this course
WHY I WROTE THIS COURSE
This course offers a one-of-a-kind rich and interactive experience to learn the fundamentals and basics of Big Data. Throughout this course, you will have plenty of opportunities to get your hands dirty with functioning Hadoop clusters.
You will start off by learning about the rise of Big Data as well as the different types of data like structured, unstructured, and semi-structured data. You will then dive into the fundamentals of Big Data such as YARN (yet another resource manager), MapReduce, HDFS (Hadoop Distributed File System), and Spark.
By the end of this course, you will have the foundations in place to start working with Big Data, which is a massively growing field.
ABOUT THE AUTHOR
DataJek
A bay area tech outfit, throwing lots of good ideas on the wall to see what sticks!
Trusted by 3.1 million developers working at companies
A
Anthony Walker
@_webarchitect_
E
Evan Dunbar
ML Engineer
S
Software Developer
Carlos Matias La Borde
S
Souvik Kundu
Front-end Developer
V
Vinay Krishnaiah
Software Developer
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