Course Outline

Introduction to Impala

  • What is Impala?
  • How Impala Differs from Relational Databases
  • Limitations and Future Directions
  • Using the Impala Shell
  • The Impala Daemon, Statestore and Catalogue service

Loading Impala

  • Explore a New Impala Instance
  • Load CSV Data from Local Files
  • Point an Impala Table at Existing Data Files

Analyzing Data with Impala

  • Describe the Impala Table
  • Basic Syntax and Querying
  • Data Types
  • Filtering, Sorting, and Limiting Results
  • Joining and Grouping Data
  • Data Loading and Querying Examples
  • Improving Impala Performance
  • How Impala works with Hadoop file formats
  • Hands-On Exercise: Interactive Analysis with Impala

Programming Impala Applications

  • Overview of the Impala SQL Dialect
  • Overview of Impala Programming Interfaces

Troubleshooting Impala

  • Troubleshooting Impala SQL Syntax Issues
  • Troubleshooting I/O Capacity Problems
  • Impala Web User Interface for Debugging




  • knowledge of SQL
  21 Hours


Related Courses

Alluxio: Unifying Disparate Storage Systems

 7 hours

Alluxio is an open-source virtual distributed storage system that unifies disparate storage systems and enables applications to interact with data at memory speed. It is used by companies such as Intel, Baidu and Alibaba. In this instructor-led,

Administrator Training for Apache Hadoop

 35 hours

Audience: The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment Goal: Deep knowledge on Hadoop cluster

Apache Hadoop: Manipulation and Transformation of Data Performance

 21 hours

This course is intended for developers, architects, data scientists or any profile that requires access to data either intensively or on a regular basis. The major focus of the course is data manipulation and transformation. Among the tools

Hadoop Administration

 21 hours

The course is dedicated to IT specialists that are looking for a solution to store and process large data sets in distributed system environment Course goal: Getting knowledge regarding Hadoop cluster

Hadoop For Administrators

 21 hours

Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. In this three (optionally, four) days course, attendees will learn about the business benefits and use cases for Hadoop and its ecosystem, how to plan

Hadoop for Business Analysts

 21 hours

Apache Hadoop is the most popular framework for processing Big Data. Hadoop provides rich and deep analytics capability, and it is making in-roads in to tradional BI analytics world. This course will introduce an analyst to the core components of

Hadoop for Developers (4 days)

 28 hours

Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. This course will introduce a developer to various components (HDFS, MapReduce, Pig, Hive and HBase) Hadoop

Advanced Hadoop for Developers

 21 hours

Apache Hadoop is one of the most popular frameworks for processing Big Data on clusters of servers. This course delves into data management in HDFS, advanced Pig, Hive, and HBase.  These advanced programming techniques will be beneficial to

Hadoop for Developers and Administrators

 21 hours

Hadoop is the most popular Big Data processing framework.

Hadoop for Project Managers

 14 hours

As more and more software and IT projects migrate from local processing and data management to distributed processing and big data storage, Project Managers are finding the need to upgrade their knowledge and skills to grasp the concepts and

Hadoop Administration on MapR

 28 hours

Audience: This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand.

HBase for Developers

 21 hours

This course introduces HBase – a NoSQL store on top of Hadoop.  The course is intended for developers who will be using HBase to develop applications,  and administrators who will manage HBase clusters. We will walk a developer

Impala for Business Intelligence

 21 hours

Cloudera Impala is an open source massively parallel processing (MPP) SQL query engine for Apache Hadoop clusters. Impala enables users to issue low-latency SQL queries to data stored in Hadoop Distributed File System and Apache

Apache Avro: Data Serialization for Distributed Applications

 14 hours

Audience Developers Format of the Course Lectures, hands-on practice, small tests along the way to gauge understanding

Samza for Stream Processing

 14 hours

Apache Samza is an open-source near-realtime, asynchronous computational framework for stream processing.  It uses Apache Kafka for messaging, and Apache Hadoop YARN for fault tolerance, processor isolation, security, and resource