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⏱ 2 jam 36 mnt📚 26 pelajaran
DynamoDB Scan and Query Operations for Beginners
Master data retrieval in DynamoDB by learning when to use scan versus query, optimizing for performance, and managing read costs effectively.
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Tentang kursus ini
When building applications with DynamoDB, retrieving your data quickly and cost-effectively is crucial for success. Many developers struggle with high read costs and slow response times because they choose the wrong data retrieval strategy. This course provides a clear, text-based guide to understanding exactly how data retrieval works in NoSQL databases, helping you write efficient queries from day one.
You will transition from basic database concepts to confidently selecting and executing the right retrieval operations for your application's specific access patterns.
What you'll learn:
- Understand the core differences between Scan and Query operations, including how they impact performance and read capacity units (RCUs).
- Apply primary keys, partition keys, and sort keys to fetch precise datasets without scanning the entire table.
- Implement secondary indexes, including Global Secondary Indexes (GSIs) and Local Secondary Indexes (LSIs), to enable flexible querying.
- Configure filter expressions to refine your results while understanding their impact on billing and latency.
- Practice pagination and parallel scans to handle large datasets efficiently without exhausting database resources.
- Avoid common anti-patterns that lead to expensive, slow database operations.
This course begins with fundamental DynamoDB architecture concepts and key terminology, then guides you through step-by-step written explanations of query execution, indexing strategies, and cost optimization techniques.
This course is designed for beginner backend developers, cloud enthusiasts, and database administrators who are new to NoSQL or DynamoDB. No prior experience with DynamoDB is required, though a basic understanding of database tables is helpful.
Start reading today to build faster, more cost-efficient cloud applications.
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