This self-paced course covers the architecture and capabilities of Vertica Analytics in Enterprise mode. This course is a prerequisite to all advanced courses and will prepare you for the operational success of your deployment.
Highlights:
- Describe the Vertica data architecture
- Manage data within a Vertica database, including loading and removing data
- Describe how SQL queries are executed
- Modify the database structure for optimal query execution
- Manage database users
Requesting a lab environment:
To request access to a lab, send an email message to learn@rocketsoftware.com including the following information:
- The course ID
- The course name
- Your first and last name
- Your local time zone
Labs are assigned in the order that the requests are received and are generated Monday-Friday between 10AM and 4PM UST (excluding public holidays). You will have access to the lab for 30 hours over a 20-day period, and your exercises must be completed within that time period. Once a lab has been assigned to you, you will receive an email message including your access credentials.
This self-paced course teaches you how Vertica executes queries, and how they can improve the performance of query execution by identifying execution issues in execution plans, and creating projection designs that address those issues. The content in this course is covered in the Vertica Analyst certification exam.
Highlights:
- Reading and interpreting a query execution plan
- Automatic projection optimization using the Database Designer
- Manual table and projection design to optimize for specific query execution
- Overriding default configurations to improve query performance
This self-paced course teaches students how to manually build projections that aggregate or rearrange data on disk, thereby improving performance of queries that reference aggregated data. These projection types are not created by the Database Designer. The content in this course is covered in the Vertica Analyst certification exam.
Highlights:
- How to build and test the following projection types: Projections with expressions, Live aggregate projections, TopK projections, and Partition range projections
- The advantages and disadvantages of each of these projection types