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HDFS Architecture Tutorial | HDFS Tutorial for Beginners | HDFS Training Video
Hello & welcome to Online Hadoop Tutorial conducted by ACADGILD. This video talks about Hadoop Distribution File System in which you will learn,
• What is HDFS?
• What is the design of HDFS?
• What is the motivation of using HDFS?
• How is data stored in HDFS?

Before getting into the important design of HDFS, Understand HDFS and its Characteristics.
If we talk about Big Data, there are some important challenges in Big Data. And these Important challenges include the velocity, volume, and the variety.

Velocity: The rate of data ingestion, as you receive the data from multiple sources and you have to design some framework Which has to take care of this large data ingestion.

Volume: The amount of data that is growing every day. So having terabytes of data or petabytes of data is very usual nowadays.

Variety: Handling different formats of file i.e. Doc file, PDFs, JSON, XML files, RDBMS etc. If we categorize the data, it can be an unstructured which does not have any schema, it can be a semi-structured or a structured data.

So considering the 3 Vs of the data, we need to store the data which has got the challenges of velocity, volume, and variety into some persistence store.

What is the motivation behind using HDFS?
• The Challenges of Big Data
• Cost Effective
• Failure Tolerant

Introduction to HDFS:
• The file store in HDFS provides scalable, fault-tolerant storage at low cost
• The HDFS Software detects and compensates for hardware issues including disk problems and server failure.
• HDFS stores file across the collection of servers in a cluster
• Files are decomposed into blocks and each block is written to more than one of the servers.
• The replication provides both fault-tolerance and performance

HDFS has been designed keeping in the view of following features:
• Very Large Files: Files that are megabytes, gigabytes, terabytes or petabytes of size
• Streaming Data access: HDFS is built around the idea that data is written once but read many times. A dataset is copied from source and then the analysis is done on that dataset over time.
• Commodity hardware: Hadoop does not require expensive highly reliable hardware as it is designed to run on clusters of commodity hardware.

Go through the entire video to learn the HDFS concepts in-depth. Happy Learning!

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