Name: Apache Hive for Data Engineers (Hands On) with 2 Projects
Availability: InStock

What You'll Learn

Understand Hive architecture and how queries are executed in a distributed environment.
Install Hive on both Linux (Ubuntu) and Windows (using Docker Desktop) with step-by-step guidance.
Learn the Hive Data Model: Tables, Partitions, and Bucketing.
Work with Hive Data Types (Primitive & Complex).
Master Hive DDL (Data Definition Language) and DML (Data Manipulation Language).
Perform data loading, insertion, updates, and deletes in Hive tables.
Use Hive built-in functions (date, math, string, tokenizing, and aggregation functions).
Work with Views, Metastore, Partitions, and Bucketing effectively.
Master Joins in Hive (Inner, Left, Right, and Full Outer Joins).
Handle XML and JSON data in Hive.
Learn how to improve performance using ORC file format, bucketing, partitioning, and CBO (Cost-Based Optimization).
Understand Hive limitations and when to use Hive vs. other big data tools.
Prepare for interviews with commonly asked Hive interview questions & answers.
Use Apache Zeppelin as a visualization and query execution tool with Hive.
Build two end-to-end projects to apply everything you’ve learned.

Requirements

Basic Knowledge of Hadoop
Basic Knowledge of SQL and Database
Desktop or Laptop with Ubuntu Operating System and Minimum 8 GB RAM is recommended
Knowledge of Regular Expression is necessary

Data Engineers looking to strengthen their Hive skills.
Big Data Developers working with Hadoop ecosystem.
SQL Developers who want to transition into Big Data.
Data Analysts who want to work with large-scale distributed data.
Students & Beginners interested in learning Hive from scratch with hands-on projects.

3.8 Instructor Rating

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134,469 Students

22 Courses

19.99 FREE 100% OFF

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