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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Troubleshooting and Tuning | 8% | - Query plans and execution analysis - Performance optimization |
| Topic 2: Using Spark SQL | 12% | - Querying data with Spark SQL - Working with views and tables - Supported file formats and data sources |
| Topic 3: Structured Streaming | 8% | - Streaming concepts and operations - Output modes and triggers |
| Topic 4: Developing DataFrame API Applications | 44% | - Reading/writing data and partitioning - User-defined functions (UDFs) - Filtering, sorting, aggregation - Column and row manipulation - Handling missing data and duplicates |
| Topic 5: Apache Spark Architecture and Components | 28% | - Driver and executor architecture - Spark execution model and hierarchy - Lazy evaluation, transformations vs actions - Fault tolerance and shuffle operations |
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