Getting Started with HDFS
|
Learning to work with Hadoop Distributed File System (HDFS) is a baseline skill for anyone administering or developing in the Hadoop ecosystem. In this course, you will learn how to work with HDFS, Hive, Pig, Sqoop and HBase from the command line.
Getting Started with Hadoop Distributed File System (HDFS) is designed to give you everything you need to learn about how to use HDFS to read, store, and remove files. In addition to working with files in Hadoop, you will learn how to take data from relational databases and import it into HDFS using Sqoop. After we have our data inside HDFS, we will learn how to use Pig and Hive to query that data. Building on our HDFS skills, we will look at how use HBase for near real-time data processing. Whether you are a developer, administrator, or data analyst, the concepts in this course are essential to getting started with HDFS.
Author Name: Thomas Henson
Author Description:
Thomas is a Senior Software Engineer and Certified ScrumMaster. During his career he has been involved in many projects from building web applications to setting up Hadoop clusters. Thomas’s specialization is with Hortonworks Data Platform and Agile Software Development. Thomas is a proud alumnus of the University of North Alabama where he received his BBA – Computer Information System and his MBA – Information Systems. He currently resides in north Alabama with his wife and daughter, where … more
Table of Contents
- Understanding HDFS
19mins - Creating, Manipulating, and Retrieving HDFS Files
47mins - Transferring Relational Data to HDFS Using Sqoop
22mins - Querying Data with Pig and Hive
36mins - Processing Sparse Data with HBase
24mins - Automating Basic HDFS Operations
18mins
User Reviews
Be the first to review “Getting Started with HDFS”
Related Products
IBM: NoSQL Database Basics
This course introduces you to the fundamentals of NoSQL, including the four key non-relational database categories. By the end of the course you will have hands-on skills for working with MongoDB, Cassandra and IBM Cloudant NoSQL databases.
AdelaideX: Programming for Data Science
Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems.
Data Science in Production: Building Scalable Model Pipelines
Learn how to build scalable model pipelines for data science in production environments, focusing on best practices for deployment and management.
An Introduction to Apache Airflow
Learn the basics of Apache Airflow for workflow management, focusing on scheduling, monitoring, and orchestrating data pipelines.
IBM: Introduction to Data Science
Learn about the world of data science first-hand from real data scientists.
EdinburghX: Data Ethics, AI and Responsible Innovation
Our future is here and it relies on data. Medical robots, smart homes and cities, predictive policing, artificial intelligences – all are fuelled by data and all promise new benefits to society. But will these innovations benefit everyone? Who stands to gain and who is put at risk? How can we ensure that data is part of a just and sustainable world?
There are no reviews yet.