4.7
Beginner
10h
Updated 1 month ago
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.
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.
This course offers a one-of-a-kind rich and interactive experience to learn the fundamentals and basics of Big Data. Throughout ...Show More
Content
1.
Hadoop
5 Lessons
Get familiar with Hadoop’s role in Big Data, its evolution, and core terminologies.
2.
YARN
3 Lessons
Walk through YARN's resource management, workflow, and scheduling for efficient cluster operation.
3.
Map Reduce
12 Lessons
Examine MapReduce's programming model, mapper, reducer, testing, execution, and resiliency in big data.
4.
HDFS
11 Lessons
Enhance your skills in HDFS architecture, from filesystem fundamentals to practical commands.
5.
Spark
11 Lessons
Deepen your knowledge of Spark’s architecture, APIs, RDDs, DataFrames, and execution workflow.
6.
Input & Output Formats
12 Lessons
Follow the process of exploring input and output format efficiencies through SequenceFile, Avro, and Parquet.
7.
Misc
5 Lessons
Master the steps to utilizing Zookeeper and Pig for managing distributed systems and parallel data processing.
8.
Quiz
6 Lessons
Get familiar with core Big Data and Hadoop concepts through structured quizzes.
9.
Reference: Replication
14 Lessons
Unpack the core of data replication techniques, consistency, latency, and conflict resolution in distributed systems.
10.
Reference: Partitioning
4 Lessons
Explore partitioning strategies to enhance scalability, fault tolerance, and query performance.
11.
Reference: Transactions
9 Lessons
Find out about database transaction concepts and strategies for maintaining data integrity.
12.
Reference: Issues in Distributed Systems
4 Lessons
Deepen your knowledge of complexities in distributed systems, network issues, and time synchronization.
Certificate of Completion
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Course Author:
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