Impala training

  • Overview
  • Course Content
  • Drop us a Query

For those who aspire to understand the basic concepts of Massively Parallel Processing or MPP SQL query engine, the Impala-an Open Source SQL Engine for Hadoop’ is the best course for them. This course focuses on the basics of the Impala. On the completion of this course, the learners will be able to interpret the role of Impala in the Big Data Ecosystem.  The Impala training also provides an overview of the superior performance of Impala, against other popular SQL-on-Hadoop systems.

The professionals who get proper training in Impala will be able to do the following:

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

The following are the prerequisites for Impala training:

  • 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
  • Internal and External Tables
  • Loading Data in Impala 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

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