Last Updated: Jul 28, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Transform, Stage, and Store Data | 35% | - Read/write various file formats (CSV, JSON, Avro, Parquet, etc.) - Write transformed results back to HDFS - Load data from HDFS into Spark - Perform ETL operations using Spark API |
| Topic 2: Application Configuration and Execution | 10% | - Use Spark Shell (Scala/PySpark) for interactive analysis - Set memory, cores, and execution parameters - Submit Spark applications via spark-submit |
| Topic 3: Data Analysis | 35% | - Perform aggregations and calculations - Create and query temporary views and tables - Join multiple datasets - Filter and sort datasets - Use Spark SQL and interact with Hive metastore |
| Topic 4: Data Ingestion | 20% | - Import/export data between relational databases and HDFS - Ingest data into HDFS using Flume - Ingest data into HDFS using Sqoop |
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