Apache Hive: Design, Query & Optimize Big Data

Overview

Learners will be able to design Hive databases and tables, implement partitions and bucketing, apply joins, configure SerDe, create custom UDFs, and optimize queries for efficient big data processing. By the end of the course, participants will not only understand Hive fundamentals but also apply advanced operations such as indexing, views, Slowly Changing Dimensions (SCDs), XML data handling, variable substitution, and performance tuning. This course provides a step-by-step pathway from beginner to advanced Hive skills, ensuring a solid foundation in HiveQL while introducing real-world scenarios that mirror enterprise big data challenges. Unlike generic SQL courses, this program is specifically tailored to Hive within the Hadoop ecosystem, highlighting its schema-on-read model, distributed query execution, and integration with Hadoop’s scalability. Learners will gain hands-on practice with query optimization, compression, and Hive architecture, making them confident in handling large-scale datasets. Upon completion, they will be able to analyze, transform, and optimize big data effectively, preparing for careers in data engineering, analytics, and Hadoop ecosystem management.

Syllabus

Hive Fundamentals

This module introduces Apache Hive and its core fundamentals, including databases, tables, partitions, and bucketing. Learners will explore how Hive enables SQL-like queries on Hadoop, manage datasets, and apply key commands for efficient data handling.

Joins, SerDe, and UDFs

This module focuses on Hive joins, serialization and deserialization (SerDe), and user-defined functions (UDFs). Learners will practice how to extend HiveQL functionality and apply advanced data transformation techniques.

Hive Operations and Partitioning

This module covers Hive operations, functions, and expressions, along with advanced partitioning strategies. Learners will gain hands-on experience with sorting, joins, alter commands, and table sampling for data optimization.

Views, Indexing, and Variables

This module explores Hive views, indexing techniques, and configuration of Hive variables. Learners will learn to create reusable query structures, apply compact and bitmap indexes, and configure variable substitution for query optimization.

Hive Architecture and Advanced Features

This module introduces Hive’s internal architecture, execution modes, and advanced features. Learners will explore SCDs, XML data handling, immutable tables, compression techniques, and performance configurations.