Big Data Greenplum DBA Training
Introduction to Greenplum
Greenplum is an open-source, massively parallel processing (MPP) data warehouse platform based on PostgreSQL. This module introduces Greenplum, covering its architecture, core features, and use cases for handling big data analytics.
Greenplum Architecture
Learn about Greenplum's architecture, including its components such as master, segment instances, and the role of the master node. Understand how Greenplum distributes data and queries across segments to achieve high performance and scalability.
Installation and Configuration
Explore the process of installing and configuring Greenplum. This section covers installation prerequisites, setting up the Greenplum database, configuring system parameters, and optimizing settings for performance.
Data Management and Administration
Gain insights into managing and administering Greenplum databases. Learn how to create and manage databases, schemas, tables, and other database objects. Understand data loading techniques, backups, and recovery processes.
Performance Tuning and Optimization
Discover methods for tuning and optimizing Greenplum performance. Learn about query optimization, indexing strategies, and system resource management. Explore techniques for monitoring and improving query execution and data loading performance.
Advanced Query Techniques
Delve into advanced querying techniques in Greenplum. Learn about complex SQL queries, joins, aggregations, and window functions. Understand how to leverage Greenplum's MPP architecture for efficient query processing.
Data Distribution and Partitioning
Understand data distribution and partitioning strategies in Greenplum. Learn how to distribute data across segments and partition large tables to enhance performance and manageability.
Security and Compliance
Learn about security features and compliance in Greenplum. Explore user roles, privileges, and authentication mechanisms. Understand how to implement security policies and ensure compliance with data protection regulations.
Monitoring and Troubleshooting
Explore tools and techniques for monitoring and troubleshooting Greenplum databases. Learn how to use system views, logs, and performance monitoring tools to identify and resolve issues.
Integration with Other Tools
Learn how to integrate Greenplum with other tools and platforms. Explore integration with ETL tools, business intelligence (BI) tools, and data visualization platforms. Understand how to leverage these integrations for enhanced data processing and analysis.
Case Studies and Real-World Applications
Review case studies and real-world applications of Greenplum. Learn from practical examples of how organizations use Greenplum for big data analytics and data warehousing.
Career Development and Certifications
Greenplum Certifications Overview: Paths and preparation tips for Greenplum-related certifications
Building a Career with Greenplum: Skills development and career opportunities
Interview Preparation: Common interview questions and scenarios related to Greenplum DBA
Big Data Greenplum DBA syllabus
1. Introduction to Greenplum DBA
- Overview of Greenplum Database: Features, Architecture, and Advantages
- Comparison with Traditional RDBMS and Other Big Data Solutions
2. Greenplum Architecture Overview
- Greenplum Components: Master Node, Segment Nodes, and Interconnects
- MPP (Massively Parallel Processing) Architecture: Distribution and Parallelism Concepts
3. Installing and Configuring Greenplum
- Preparing for Installation: System Requirements and Prerequisites
- Greenplum Installation: Single-Node and Multi-Node Cluster Setups
- Configuration Management: gpconfigs, gpseginstall, and gpexpand Commands
4. Greenplum Database Objects
- Tables and Views: Creating, Altering, and Dropping Tables/Views
- Indexes: Types of Indexes and Their Usage
- Partitioning: Range, List, and Hash Partitioning Strategies
5. Data Loading and Management
- Data Loading Techniques: Using gpload, COPY Command, and External Tables
- Managing Data Distribution: Distribution Keys and Distribution Policies
- Vacuum and Analyze: Maintaining Data Consistency and Optimizing Query Performance
6. Query Optimization and Performance Tuning
- Query Execution Plans: Understanding Query Planning and Execution
- Query Optimization Techniques: Indexes, Statistics, and Tuning
7. High Availability and Fault Tolerance
- Greenplum Fault Tolerance: Segment Mirroring and Data Redundancy
- Backup and Recovery: Strategies for Backup, Restore, and Disaster Recovery
- Monitoring and Alerting: Using Greenplum Command Center (GPCC) and SNMP Alerts
8. Greenplum Security
- Authentication and Authorization: Role-Based Access Control (RBAC) and LDAP Integration
- Encryption: Data at Rest and Data in Transit Encryption Options
- Auditing and Compliance: Monitoring User Activity and Enforcing Security Policies
9. Advanced Greenplum Features
- Advanced Analytics: Using Greenplum for Machine Learning and Data Science
- Integration with Big Data Ecosystem: Hadoop, Spark, and Kafka Integration
- Greenplum Extensions: Adding Functionality with PL/pgSQL, PL/Python, and UDFs
10. Greenplum Monitoring and Maintenance
- Performance Monitoring: Using Greenplum Command Center (GPCC) and System Views
- Capacity Planning: Scaling Greenplum Clusters and Adding Nodes
- Patching and Upgrading: Best Practices for Maintaining Greenplum Installations
11. Greenplum in Production Environment
- Best Practices for Production Deployment: Configuration, Tuning, and Monitoring Tips
- Troubleshooting Common Issues: Diagnosing Performance Bottlenecks and System Failures
- Disaster Recovery Planning: Strategies for Data Protection and Business Continuity
12. Real-world Projects and Case Studies
- Implementing Greenplum Solutions: Industry-Specific Case Studies and Success Stories
- Best Practices and Lessons Learned from Real-world Implementations
13. Career Development and Certification
- Building a Career as a Greenplum DBA: Skills Development and Certification Paths
- Interview Preparation: Common Greenplum-Related Interview Questions and Scenarios
Training
Basic Level Training
Duration : 1 Month
Advanced Level Training
Duration : 1 Month
Project Level Training
Duration : 1 Month
Total Training Period
Duration : 3 Months
Course Mode :
Available Online / Offline
Course Fees :
Please contact the office for details