Hive and HQL

Why should you attend?

Dive into the world of big data processing with Hive, a data warehouse infrastructure built atop Apache Hadoop for providing data summarization, query, and analysis. This course offers a deep dive into the intricacies of managing and manipulating large datasets using Hive Query Language (HQL). Starting with an introduction to the Hadoop ecosystem, you will gain insights into MapReduce, the framework for processing vast amounts of data in parallel across clusters. ' ' You'll explore Hive's role in this system, learning how to interact with data through the Hive Command Line Interface (CLI). As you progress, you'll master various data types and file formats that Hive supports and understand the concept of schema on read. The course also covers detailed aspects of HQL, including data definition operations like creating databases and tables (both managed and external), as well as advanced manipulations such as querying, casting, sampling, and unions. ' ' Further enhancing your skillset, you will learn about views for simplifying queries and indexes to optimize search. Schema design principles like partitioning and bucketing are discussed to structure your data efficiently. Performance tuning techniques will help you optimize query execution times. Additionally, the course touches upon integrating Hive with cloud services like AWS EMR and addresses security measures within Hive. Real-world case studies provide practical insights into applying what you've learned in actual scenarios.