Impala training

• Explain Impala and its role in Hadoop Ecosystem
• Explain Partitioning of Impala tables and its benefits
• Query data using impala SQL
• Describe the complete flow of a SQL query execution in the Impala
• List the factors affecting the performance of the Impala

• SQL developers
• Analysts
• Database administrators and developers
• Data warehouse developers
• Data scientists
• Hadoop administrator and developers

• Fundamental Knowledge of programming language and Hadoop component
• Basic knowledge of SQL commands

1. An Introduction to Impala

• An overview to the Impala
• What is Impala?
• The benefits of Impala
• Exploratory Business Intelligence
• The Impala Installation
• Starting and Stopping Impala
• Data Storage
• Managing Metadata
• Controlling Access to Data
• Impala Shell Commands and Interface

2. Querying with Hive and Impala

• Querying with Hive and Impala
• SQL Language Statements
• DDL Statements
• CREATE the DATABASE
• CREATE the TABLE
• Internal and External Tables
• Loading Data in Impala Table
• The ALTER TABLE
• The DROP TABLE
• What is DROP DATABASE?
• Describing the Statement
• Explaining the Statement
• SHOW the TABLE Statement
• INSERT Statement
• SELECT Statement
• Data Type 
• The Operators
• About the Functions
• The CREATE VIEW in Impala
• Hive and Impala Query Syntax

3. Data Storage and File Format

• About the Data Storage and File Format
• The Partitioning Tables
• SQL Statements for Partitioned Tables
• File Format and Performance Considerations
• Choosing the File Type and Compression Technique

4. Working with the Impala

• Working with the Impala
• Know Impala Architecture
• What is Impala Daemon?
• About the Impala Statestore
• Impala Catalog Service
• Query Execution Flow in Impala
• User - Defined Functions
• Hive UDFs with Impala
• Improving Impala Performance