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Broadcom 250-608 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Database Objects & Data Organization | 10% | - Tables, indexes, constraints - Data distribution and partitioning |
| Greenplum Foundational Concepts | 5% | - Distributed database fundamentals - Architecture and components |
| Data Loading & External Data Access | 12% | - External tables and protocols - ETL pipelines and utilities |
| Security & Access Control | 7% | - Authentication and authorization - Data encryption and compliance |
| Advanced Analytics & Extensions | 12% | - Spatial data processing (PostGIS, H3) - Vector databases and similarity search - Text analytics (GPText) - In-database ML (MADlib) |
| SQL Fundamentals & Functions | 5% | - Basic and advanced SQL - Built-in functions and extensions |
| Cluster Management & Monitoring | 10% | - Resource groups and workload management - Monitoring tools and health checks |
| Troubleshooting & Maintenance | 8% | - Upgrades and patching - Common issues and resolution |
| Query Optimization & Performance | 11% | - Tuning strategies and best practices - Query planning and execution |
| Data Protection & High Availability | 10% | - Mirroring and fault tolerance - Backup and recovery strategies |
Broadcom Tanzu Greenplum v7 Technical Specialist Sample Questions:
1. What is the function of the gpstop utility in Greenplum?
A) Terminates a single user session
B) Uninstalls all Greenplum extensions
C) Stops replication on standby master
D) Shuts down all Greenplum cluster components
2. What SQL keyword is used to invoke a MADlib function in Greenplum?
A) EXECUTE
B) MADRUN
C) SELECT
D) CALL
3. What does the Greenplum Master host primarily manage?
A) User connections, query planning, and dispatching
B) Parallel processing of queries across segments
C) Storage and memory allocation
D) Execution of machine learning models
4. Which two metrics are commonly visualized in GPCC to evaluate cluster performance?
(Choose two)
A) Query execution time
B) CPU utilization
C) Number of PostgreSQL extensions
D) Network broadcast domains
5. A data architect is designing a Greenplum database for an e-commerce company handling large datasets with frequent joins on customer_id. To optimize performance and ensure even data distribution across segments, what should the architect do?
A) Apply random distribution for all tables
B) Define hash distribution on customer_id for related tables
C) Use replicated tables on all segments
D) Store all tables on the master node for centralized access
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: A,B | Question # 5 Answer: B |






