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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Big Data Offline Batch Processing Scenario-based Solution | 25% | - Data ingestion and lakehouse formats - Hive development: UDF/UDAF/UDTF, ACID, optimization - Spark development: RDD, DataFrame, Catalyst, AQE |
| Topic 2: Big Data Real-time Retrieval Scenario-based Solution | 30% | - GaussDB(DWS) data warehouse - Elasticsearch, SolrCloud, CarbonData usage - HBase design, coprocessors, optimization - Apache Phoenix SQL and indexing |
| Topic 3: Big Data Application Development Overall Guide | 15% | - Security framework: Kerberos, Ranger, ZooKeeper - Big data architecture: Lambda and Kappa - FusionInsight HD architecture and components - HDFS advanced features and YARN scheduling |
| Topic 4: Big Data Real-time Stream Computing Scenario-based Solution | 30% | - Flink SQL and CEP - Apache Flink: event time, windowing, state, checkpoint - Kafka integration and transactions - Spark Structured Streaming |
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