Pass the actual test with the help of C2090-103 study guide
Updated: Sep 02, 2026
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| Certification Vendor: | IBM |
|---|---|
| Exam Name: | Apache Spark 1.6 Developer |
| Exam Number: | C2090-103 |
| Passing Score: | 65% |
| Exam Price: | Approx. $200 USD |
| Available Languages: | English |
| Exam Format: | Multiple Select, Multiple Choice |
| Exam Duration: | 120 minutes |
| Certificate Validity Period: | No expiration (Retired exam) |
| Real Exam Qty: | 55-60 |
| Recommended Training: | IBM Recommended Training |
| Exam Registration: | Pearson VUE IBM Certification Registration |
| Exam Way: | Proctored at Pearson VUE test centers or online proctored |
| Pre Condition: | No formal prerequisites; recommended: hands-on Spark experience, Scala/Python, SQL, big data knowledge |
| Official Syllabus URL: | https://www.ibm.com/training/certification/ibm-certified-developer-apache-spark-16-50002101 |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Core Spark Development Skills | 48% | - Spark configuration and context setup - RDD creation and API usage - DataFrames and Spark SQL - Application submission with spark-submit - Accumulators, broadcast variables - Data ingestion from multiple sources/formats |
| Topic 2: Advanced Spark Components | 18% | - MLlib / Spark ML - Building multi-component data pipelines - GraphX - Spark Streaming |
| Topic 3: Performance and Troubleshooting | 22% | - Serialization and memory optimization - Shuffle operations identification - Caching, checkpointing and persistence - Partition management and strategies - Debugging, monitoring and runtime issue resolution |
| Topic 4: Spark Architecture | 12% | - Cluster deployment configuration - Spark vs Hadoop MapReduce - Transformations, actions and lazy evaluation - Master, driver, executor, stages, tasks concepts - Memory management |
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