Accessing Hadoop Data Using Hive
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Discover how to access and query Hadoop data using Apache Hive. Learn the basics of HiveQL and its integration with the Hadoop ecosystem for data analysis.
At a Glance
Hive is a data warehousing tool built on top of Hadoop. Learn how to easily query and analyze your Big Data projects with this course on Apache Hive.
About This Course
Writing MapReduce programs to analyze your Big Data can get complex. Hive can help make querying your data much easier. Apache Hive, first created at Facebook, is a data warehouse system for Hadoop that facilitates easy data summarization, ad-hoc queries, and the analysis of large datasets stored in Hadoop compatible file systems. Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. This course will get you started so that you can use Hive for Data Warehousing tasks on your Big Data projects.
What will I get after passing this course?
- You will receive a completion certificate.
Course Syllabus
- Lesson 1 – Introduction to Hive
- Describe what Hive is, what it’s used for and how it compares to other similar technologies
- Describe the Hive architecture
- Describe the main components of Hive
- List interesting ways others are using Hive
- Lesson 2 – Hive DDL
- Create databases and tables in Hive, while using a variety of different Data Types
- Run a variety of different DDL commands
- Use Partitioning to improve performance of Hive queries
- Create Managed and External tables in Hive
- Lesson 3 – Hive DML
- Load data into Hive
- Export data out of Hive
- Run a variety of different HiveQL DML queries
- Lesson 4 – Hive Operators and Functions
- Use a variety of Hive Operators in your queries
- Utilize Hive’s Built-in Functions
- Explain ways to extend Hive functionality
General information
- This course is self-paced.
- It can be taken at any time.
- It can be taken as many times as you wish.
Recommended skills prior to taking this course
- Have taken the Hadoop Foundations I course
- Basic understanding of Apache Hadoop and BigData.
- Working knowledge of SQL
- Basic Linux Operating System knowledge
Grading scheme
- The minimum passing mark for the course is 70%, where the review questions are worth 50% and the final exam is worth 50% of the course mark.
- You have 1 attempt to take the exam with multiple attempts per question.
Requirements
None.
Course Staff
Aaron Ritchie
Aaron Ritchie has worked in the Information Management
division of IBM for over 11 years and has held a variety of roles
within the Center of Excellence and Education groups. Aaron has
worked as an IT Specialist, Learning Developer, and Project
Manager. He is certified in multiple IBM products and enjoys
working with an assortment of open-source technologies. Aaron
holds a Bachelor of Science in Computer Science degree from
Clarkson University and a Master of Science in Information
Technology degree from WPI.
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