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IBM C2090-103 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Performance and Troubleshooting | 22% | - Debugging, monitoring and runtime issue resolution - Partition management and strategies - Shuffle operations identification - Serialization and memory optimization - Caching, checkpointing and persistence |
| Core Spark Development Skills | 48% | - RDD creation and API usage - Accumulators, broadcast variables - Data ingestion from multiple sources/formats - Application submission with spark-submit - DataFrames and Spark SQL - Spark configuration and context setup |
| Spark Architecture | 12% | - Transformations, actions and lazy evaluation - Spark vs Hadoop MapReduce - Memory management - Master, driver, executor, stages, tasks concepts - Cluster deployment configuration |
| Advanced Spark Components | 18% | - MLlib / Spark ML - GraphX - Building multi-component data pipelines - Spark Streaming |
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