Duration
2 days
Overview
This training course is designed to learn Apache Hive in the most efficient way to run analytical queries on big data.
The course begins with basics of Hive including architecture, understanding Yarn, HDFS, running Hive with different execution engines- Spark, Tej & MapReduce. From there, students will learn about the Hive basic operations; how to work with the right data format & compressions; working with Hive Functions; understanding how to do analytics with Hive and dealing with various kinds of Joins. The course concludes by exploring Hive advance features and various Optimization techniques to run queries faster.
This course is designed for Business analysts, Big data developers, Testers who want to run analytics queries on big data systems.
Prerequisites
Basic Knowledge of SQL
Course Objectives
After this course, you will be able to:
- Run analytics queries using Apache Hive
- Tune and optimize the Hive system to run queries faster.
Course Outline
Hive Overview
- Understanding Hadoop File System
- Yarn Overview
- Hive Overview & Architecture
- Hive Execution Engines overview - Apache Spark, Tej & MapReduce
Hive Basic Operations
- Hive Databases
- Hive Managed/External Tables
Working with different File formats
- Working with Parquet Files
- Parquet versus Orc Files
- Understanding Avro
- Schema Evolution with Avro
Hive Functions
- Conditional Functions
- String Functions
- Date Functions
Hive Joins
- Sort Merge Joins
- Broadcast Joins
- Bucket Joins
- Multi Joins
Hive Analytics
- Aggregations
- Grouping
- Subquery
- Conditional statements
Hive Advance
- Views/Lateral Explode
- Windowing
- Materialized view
Hive Optimization
- File Partitioning
- Bucketing
- Dynamic Partition Pruning
Programme scope, delivery arrangements and suitability are confirmed during enquiry.