Greenplum Architecture, Administration, and Implementation

Objectives

• Greenplum features, benefits, and architecture in terms of shared nothing and the Massively Parallel Processing (MPP) design
• Support redundancy and high availability with Greenplum
• Data models used in data warehousing and how data is stored in Greenplum
• Install, initialize, validate, and configure Greenplum Database
• Manage database objects and workload management processes by defining and managing roles, privileges, and resource queues
• Use table partitioning as a design methodology for handling large tables
• Load data into a Greenplum database instance using external tables, SQL copy, insert commands, and parallel load utilities
• Use data manipulation language and data query language to access, manage, and query data
• Perform system administrative tasks, including managing and checking the state of the Greenplum database, its data, and the distribution of data
• Perform backup and restoration of Greenplum data
• Distribute and store data in Greenplum using a distribution key and partitioning
• Use EXPLAIN and EXPLAIN ANALYZE to help the Greenplum query plan optimizer determine how to handle a submitted query
• Improve query performance by keeping statistics up to date and tuning the database for sampling size and error conditions
• Determine when it's best to use an index and what type of index to use
• Improve query performance by following a number of performance enhancement tips