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| Section | Weight | Objectives |
|---|---|---|
| Big Data Real-time Retrieval Scenario-based Solution | 30% | - Real-time retrieval optimization - Elasticsearch and real-time search - HBase architecture and development - GaussDB(DWS) and distributed query |
| Big Data Real-time Stream Computing Scenario-based Solution | 30% | - Flink stream processing framework - Flume and Kafka data ingestion - Stream solution deployment and tuning - Spark Streaming and Structured Streaming |
| Big Data Offline Batch Processing Scenario-based Solution | 25% | - Data ingestion tools: Loader, Sqoop, Kettle - Spark SQL and batch processing - HDFS and Hive principles and usage - Offline solution design and optimization |
| Big Data Application Development Overall Guide | 15% | - Application development fundamentals - Big data concepts and architecture - Scenario-based big data solutions overview - Mainstream big data technologies and ecosystems |
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